From 4071f47b53568f85cd5f95ef79e961adc293e6b0 Mon Sep 17 00:00:00 2001 From: Cheril Shah <79891166+Cheril311@users.noreply.github.com> Date: Fri, 15 Oct 2021 10:08:58 +0530 Subject: [PATCH 1/3] Add files via upload --- datarobot_CherilShah.ipynb | 2185 ++++++++++++++++++++++++++++++++++++ 1 file changed, 2185 insertions(+) create mode 100644 datarobot_CherilShah.ipynb diff --git a/datarobot_CherilShah.ipynb b/datarobot_CherilShah.ipynb new file mode 100644 index 0000000..5d6a190 --- /dev/null +++ b/datarobot_CherilShah.ipynb @@ -0,0 +1,2185 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DataRobot Internship Task" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Loading the dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "data = pd.read_csv(r'sampled_data2.csv')\n", + "df = data.copy()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Noting the feature names for directly manipulating or analyzing these. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['step' 'customer' 'age' 'gender' 'merchant' 'category' 'amount' 'fraud']\n" + ] + } + ], + "source": [ + "print(data.columns.values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "preview the data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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stepcustomeragegendermerchantcategoryamountfraud
02021-07-16C132659335336to45MaleM1823072687Transportation15.780
12021-08-22C48391213126to35FemaleM1198415165Beauty&Wellness608.321
22021-06-03C168158960026to35FemaleM348934600Transportation43.760
32021-07-01C125174929436to45FemaleM1823072687Transportation41.570
42021-03-06C170534621636to45MaleM348934600Transportation42.970
52021-03-27C3467668626to35MaleM348934600Transportation32.610
62021-03-18C76036840536to45MaleM980657600Sports&Toys410.671
72021-07-16C165503714726to35FemaleM480139044Health16.451
82021-05-13C178945787226to35FemaleM3697346Leisure300.621
92021-07-23C47754287426to35FemaleM85975013Groceries47.470
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" + ], + "text/plain": [ + " step customer age gender merchant category \\\n", + "0 2021-07-16 C1326593353 36to45 Male M1823072687 Transportation \n", + "1 2021-08-22 C483912131 26to35 Female M1198415165 Beauty&Wellness \n", + "2 2021-06-03 C1681589600 26to35 Female M348934600 Transportation \n", + "3 2021-07-01 C1251749294 36to45 Female M1823072687 Transportation \n", + "4 2021-03-06 C1705346216 36to45 Male M348934600 Transportation \n", + "5 2021-03-27 C34676686 26to35 Male M348934600 Transportation \n", + "6 2021-03-18 C760368405 36to45 Male M980657600 Sports&Toys \n", + "7 2021-07-16 C1655037147 26to35 Female M480139044 Health \n", + "8 2021-05-13 C1789457872 26to35 Female M3697346 Leisure \n", + "9 2021-07-23 C477542874 26to35 Female M85975013 Groceries \n", + "\n", + " amount fraud \n", + "0 15.78 0 \n", + "1 608.32 1 \n", + "2 43.76 0 \n", + "3 41.57 0 \n", + "4 42.97 0 \n", + "5 32.61 0 \n", + "6 410.67 1 \n", + "7 16.45 1 \n", + "8 300.62 1 \n", + "9 47.47 0 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "get basic information of the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 25200 entries, 0 to 25199\n", + "Data columns (total 8 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 step 25200 non-null object \n", + " 1 customer 25200 non-null object \n", + " 2 age 25200 non-null object \n", + " 3 gender 25200 non-null object \n", + " 4 merchant 25200 non-null object \n", + " 5 category 25200 non-null object \n", + " 6 amount 25200 non-null float64\n", + " 7 fraud 25200 non-null int64 \n", + "dtypes: float64(1), int64(1), object(6)\n", + "memory usage: 1.5+ MB\n" + ] + } + ], + "source": [ + "data.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that we have 8 columns, each column has 25200 non-null rows, this can mean that their is a high probability that the dataset has no null values, but it's better to check. Of the 8 columns/features only 2 are numerical while the rest are categorical." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "checking for null values" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "step 0\n", + "customer 0\n", + "age 0\n", + "gender 0\n", + "merchant 0\n", + "category 0\n", + "amount 0\n", + "fraud 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "this shows that there are no null values in the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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amountfraud
count25200.00000025200.000000
mean174.2125060.285714
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" + ], + "text/plain": [ + " amount fraud\n", + "count 25200.000000 25200.000000\n", + "mean 174.212506 0.285714\n", + "std 501.116240 0.451763\n", + "min 0.000000 0.000000\n", + "25% 17.720000 0.000000\n", + "50% 36.340000 0.000000\n", + "75% 109.180000 1.000000\n", + "max 8329.960000 1.000000" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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stepcustomeragegendermerchantcategory
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" + ], + "text/plain": [ + " step customer age gender merchant category\n", + "count 25200 25200 25200 25200 25200 25200\n", + "unique 180 4061 8 4 48 14\n", + "top 2021-06-18 C1350963410 26to35 Female M1823072687 Transportation\n", + "freq 177 147 7984 14596 9192 15925" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe(include = 'O')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It can be noticed that the age column has varied values thus scaling is required. Also the gender column might have an unknown attribute as it has 4 unique values or it might be some human error which needs to be corrected. Also there are many values of the same attribute (female in gender and transportation in category) which might lead to skewed results without techniques for addressing overfitting." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Male' 'Female' 'Enterprise' 'Unknown']\n" + ] + } + ], + "source": [ + "#checking the attributes of gender\n", + "print(data.gender.unique())" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'corr': step customer age gender merchant category \\\n", + " step 1.000000 0.390616 0.014808 0.010605 0.107360 0.057168 \n", + " customer 0.605403 1.000000 1.000000 1.000000 0.508105 0.458672 \n", + " age 0.004728 0.205996 1.000000 0.019601 0.003319 0.001807 \n", + " gender 0.001423 0.086573 0.008237 1.000000 0.002983 0.003207 \n", + " merchant 0.046917 0.143268 0.004542 0.009716 1.000000 1.000000 \n", + " category 0.016173 0.083724 0.001601 0.006763 0.647370 1.000000 \n", + " amount 0.099530 0.470454 0.028884 0.043971 0.811395 0.805309 \n", + " fraud 0.067233 0.796446 0.038085 0.105551 0.944918 0.870595 \n", + " \n", + " amount fraud \n", + " step 0.099530 0.067233 \n", + " customer 0.470454 0.796446 \n", + " age 0.028884 0.038085 \n", + " gender 0.043971 0.105551 \n", + " merchant 0.811395 0.944918 \n", + " category 0.805309 0.870595 \n", + " amount 1.000000 0.450215 \n", + " fraud 0.450215 1.000000 ,\n", + " 'ax': }" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#correlation plot of features using theil's u method to correlate both categorical and numerical features \n", + "from dython.nominal import associations\n", + "associations(data, theil_u=True, figsize=(20, 20))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The correlation plot shows some expected and some weird properties. Both Customer and Merchant are highly correlated with the target column, this might mean that some merchants have repeatedly conned people and some customers have been repeatedly cheated. Also very strangely enough the customer column is 100% corelated with age which seems to be a mistake. Also amount of a purchase is moderately correlated to fraud against my initial thought. And the column age is very weakly correlated to fraud against the common beleif that old people are more likely to cheated" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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categoryfraud
7Leisure1.000000
13Travel0.993127
10Sports&Toys0.971569
6HotelServices0.935154
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5Home0.870317
4Health0.796992
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" + ], + "text/plain": [ + " category fraud\n", + "7 Leisure 1.000000\n", + "13 Travel 0.993127\n", + "10 Sports&Toys 0.971569\n", + "6 HotelServices 0.935154\n", + "8 OtherServices 0.908367\n", + "5 Home 0.870317\n", + "4 Health 0.796992\n", + "11 Technology 0.738318\n", + "0 Beauty&Wellness 0.605907\n", + "9 Restaurants&Bars 0.405405\n", + "2 Fashion 0.362500\n", + "12 Transportation 0.017582\n", + "1 Contents 0.000000\n", + "3 Groceries 0.000000" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[[\"category\", \"fraud\"]].groupby(['category'], as_index=False).mean().sort_values(by='fraud', ascending=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This shows that high spending categories like leisure, travel, sports and toys have been involved in fraud most number of times, with leisure purchases always being fraud. This means that fraud is likely to be nicely correlated to a combination of category and amount" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "sns.distplot(data['amount'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The distanceplot of amount is extremely left skewed and the frequency of values starts becoming very less from around 1000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As seen in the data description, the age column has object values of a particular age band, let us replace that with the upper limit of the groups " + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:670: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " iloc._setitem_with_indexer(indexer, value)\n" + ] + } + ], + "source": [ + "for i in range(0, len(data)):\n", + " if (data['age'].loc[i] == '36to45'):\n", + " data['age'].loc[i] = 45\n", + " if (data['age'].loc[i] == '26to35'):\n", + " data['age'].loc[i] = 35\n", + " if (data['age'].loc[i] == '56to65'):\n", + " data['age'].loc[i] = 65\n", + " if (data['age'].loc[i] == '19to25'):\n", + " data['age'].loc[i] = 25\n", + " if (data['age'].loc[i] == '46to55'):\n", + " data['age'].loc[i] = 55\n", + " if (data['age'].loc[i] == 'gt65'):\n", + " data['age'].loc[i] = 100\n", + " if (data['age'].loc[i] == 'Unknown'):\n", + " data['age'].loc[i] = 0\n", + " if (data['age'].loc[i] == 'lt18'):\n", + " data['age'].loc[i] = 18\n", + "data['age'] = data['age'].astype(int)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Feature Engineering" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "data['meramt'] = data.groupby('merchant')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "data['catamt'] = data.groupby('category')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "data['custamt'] = data.groupby('customer')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(0,len(data)):\n", + " data['customer'].loc[i] = data['customer'].loc[i].replace(\"C\",\"\")\n", + " data['customer'].loc[i] = int(data['customer'].loc[i])\n", + "\n", + "for i in range(0,len(data)):\n", + " data['merchant'].loc[i] = data['merchant'].loc[i].replace(\"M\",\"\")\n", + " data['merchant'].loc[i] = int(data['merchant'].loc[i])" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "data['mercat'] = data.groupby('category')['merchant'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "data['custcat'] = data.groupby('category')['customer'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "data['catage'] = data.groupby('category')['age'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first three features are based on previous observations of dependence of amount with the other features. The last three features might seem funny but are based on correlation and might make sense mathematically.
\n", + "Let's revisualize the correlation plot" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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633WY/e9wODQtK0tfLVqk/33yiZYuWRKUuIMlf2uhnI0OTBt2NoxX/tZC5W/ZLmfDA/sTG9ZV/tbCUIR4xGonNNIu16aS7d35m3VMQqMybRqqaVo7rZ4wvfw/YK3SXn1aXd57RSf17hbocAMi0ZmgjT7XfpcrX84y53X9+vW0o3BHybnvcuWXjP//jh2nliedqM+/yFXWzCkaPuLJiCriJSQ2kstVULKd7ypQYsLh/QDeps2ZmjT5Hf3738+rZcvImX0oSYmJCcrLOzBzyuXKV+Jh/AKiqseHWmJiYqnCVKXjf0eZ8e/05PjDDyvVubPnB5qzzz5Txx+fpKSkyPhskJjYWHku374rUGJi+R/gKpOQ0FgZ6Sn64INJgQgvoLj2c+1PTExUns/n3jyXq4L866vQN/88lxJ9Pvufc04bZc2cqrffeUMnnxxZt4+FA7fsUfkVifxdxDND0kNl9nWtYF/QGJly+yq7EJ351/PUsfdleqTfjaX21zqmth4Y9bzefuoF7dm1KyBxBkL5zMvnboz/359I5E9+/rS58MIL1KfPVbqi95Xl2oarivpfh5F7cXGxMrt1U534eL02ZoxOOeUU/fTTTwGINDQqGubGmAov0RV+L8OZH2P63Afu0JKX3pAtLi7Xdu6Ae7Vn0xbVrF9PHV57WoW/rNemRd8FLNxAOOJz3zsCLmnfTit++FH9+t2g5s1P0H/GvqEeX1+unTsj4z2g4vz9P37FipVK73iFdu/eo/btL9DLo59U1y6Rsw5UBekf1ntbVY8Ptaq+9/37329o8OCHNW3aR1q5cpVWrPhRRUXuwARb3ao49gc9cq+ef/4VFVdwbQx7XPu59lfx3F/+/Qq1uzhVu3fvVmpqiv495lV1SMso1x6IBActYBhjbpd0h6QTjTHLfF6qI6n8dIYDx90q6VZJapvYTMn1qn965pb8AjXymfbfwJmgrQWbyrVrfsrJun3EYD1+613auW17yf6Y2Fg9MOp5fTItS1/Ozan2+ALJ5XKpSVJSyXZSUpIK8kvfy+/Ky1OTJk1Ktp1Op/ILChTJrrv+OvW9+mpJ0tJly9SkyYHvgdOZpPyC0t+DrVu3Kj4+XjExMXK73UpKcqog/8D34LTTTtPTzzytAf1v0LYIuqXG5XIpyaf/nUlJyq+k//ffBVtR/+8oLNQXn3+u9qmpR1UBw9kwXq7NB85115ZCJdSvo31Fbrm2HNifv2W7EhrEhyLEI7Ynf5OOdR74jeMxiY20Z9OWUm0anHGyLn5mkCSpZr26atLufFm3Wxvmf1bS9o/ft2nD/P+p4ZmnRsSH2Guv66s+3vt4v1v2nZokOX3GdqLy80uP7a1bf1ed+Dol575vmyuuuFyvvfaGJGndul+1Yf0GnXjiiVq2LHy/D32v6aUrr8iUJH33/Q8lv02XPL+VLNi02e9/a9eu3SV/X7jwCw0e8g/Vq1dX23zeH8NNv2v7qI/3PvZl3y0vNWPA6UxUQQXv/ZVxuQqqdHwoXHvt1erT5wpJ0nfffa8mTZz61nsCVDr+65Qd/54cd+7cpYceOrBuRm7ubG3YsCE4iRyBa665Qldedakk6bvvVijJ6dt3CYfVd2eeebpGjhwhSapXv57ap1ykoqIiZWcvrN6gA4Brf3Re+6+7rp+u7utZsHXZ0mVK8vncm+R0VpD/VsX75p/kVIH3s9/OnTtL2i1YkKsRjw9T/fr19fvvvwchE6B6HeoWkvckZUqa6v1z/9e51tprKzvIWjvGWnuetfa8QBQvJGn1d8uV1LyZEo5voti4WLXr1lnf5JS+DaBRklMPvPy8Rj00WHlrfy312h2PD9GGNb9o2jvjAhJfIC1dulQtkpPVtFkzxcXFKTMzU3Pnzi3VZu68eerV27NoV9u2bbVjxw5tivACxn/H/lfdunVXt27dNWfOHPXq7flA27ZtG29+5T/IfP75F+rWraskqXfv3prj/T41adJEr/37Vd1773365ZdfgpdENVhWpv97ZGYqu0z/z5s3T5d7+7+NT/83aNBAdeI9P7TXrFlTF7drpzWrVwc9h0DqcP7p+njBYllrtWTlr6pzTC0lNIjXWS2P19q8zVqfv1V/7ivSjE+XqcP5kfX0mS3LV6rOCcfr2CZOOWJj1bxzqn7L/bxUm6ndr9fUbtdparfrtH7eJ/r6yZe1Yf5niqlVS7HH1JYkxdSqJeeF52r76rUhyOLwvfvf95XZo5cye/TSnLnZuvxyzw80bdqc7RnbFfwA/8UXX6lrV8+aN716X6Z58zyF6o0b83TRRRdIkho2aqjkE5O1fv36IGVyZN5/b1LJopvZ2Z/o0ku7SJLObt1KO3bs1OYyP8gcTKNGDUr+ftZZp8thHGFdvJCkce9+qJ49+6hnzz6aN3e+LrvcU8xp0+Ys7dixs8L+r0x29oIqHR8K7777gTIzr1Bm5hWaMydHl1/eU9L+8V9x/KXGf69LS8Z/nTp1Sp5I0qdPb3399bdh/Rvo9977SJdfdp0uv+w6Zc9bqEsv87yft259pjd3/8d+esfL1dH7NWd2joY/9lxEFC8krv3Reu3/73/HlSy6OWfOPPXqdZkkqc3+z72byn/u/eLzL9W1m+c9onfvXpo7Z54kqZHPeiGtW58tYxwULxCxDjoDw1q7XdJ2SX2NMTGSEr3HHGeMOc5a++vBjg+kYrdbb4x4RoPffEUOh0M5E6dq/eqf1amP54e2OR9O1JV33KI69erqliEDJXmePvLQFdfqtHPaKPWyHlq3cpWen/y+JOm9F0drUQVrZIQjt9utIUOGaOzYsYqJidH48eO1atUq9evXT5I0btw4zc/JUVpamnIXLtSePXv0wP0HVqofNWqULrjwQtWvX1+ff/GFXnzxRY3/8MNQpXNE5ufM9+a3wJvfgdXI337nLT304MMqKCjQ0089rZdHv6x/3P8PLV++QuM/HC9J+vvdf1f9+vX1+AjPb2OK3EXqmXlpSHI5XG63W48NGaJ3xo6VIyZGH3n7v6+3/98fN04LcnKUmpamnIULtXfPHj3k7f/GCQl6buRIxTgccjgcmjF9uubnRNYMpPtGfqCvvv9Fv+/YpfY3P627rk5Xkfd+z76d/6qUc09V7qKVyrjjBdWuGacn7/RcE2JjYjTk5p66efjbchdb9e54rk4+ITLu/d7Puov1zdOjlfbqUzIOh36eMlvb16xTyyt6SJJWf1TBvc9etRrWU/uRwyRJJjZG62bOV95n3wQj7Gq1YP5Cpaa2V878Wdq7d68eevCRktfefOs1DXx4sAoKNunZZ17QS6Oe13333a3lK37QhPGeRW1Hv/yqnn3uSWXN/FhGRs8+M1K//74tRNkcvoW5n6t9+ws1a/aH2rt3rx4ZdOAJSq/9+zkNfvRpbdq0Rddee4VuvOkaNWrUQB9P+Y8WLvxcQwY/o06dUnV138tVVOTWH3/8oX/8o+KV/MPVggWfKCW1nbJzpmvPnr16+KEhJa+9/sZoPTLoMRUUbNL111+jW24doEaNGmra9AnKzf1Ujwx67KDHR4IFCxYqNfUS5eTM1N69e0rNpnjzzX9p4MChnvH/7It66aXndN99d2n58h80YYJn3YeWLU/U888/KbfbrdWrf9bDD0dO/rm5/1P7lIs0Z+5E7d2zV4MGjSh57d9jXtTgR59QQcFmXXfdVbrp5uvUqFEDTZ06Trm5n2nwo5HzpLGKcO3n2j9//gKlpaVoQW629uzZowcfOPAEobfefl0PP/SI53Pv08/p5Zdf1D/+ca9WLF+h8eM/kiR169pF/a69Rm53kfbu/UN/v+ueEGUCVJ3x595PY8ydkoZJype0/+Y6a609+1DH9j7tnMi5ubSafbvH/98MHJ0i9iE31SJGEXifbTVakzUy1CGE1Hv9Xgt1CCEzuPC3Qzc6itWs2eDQjY5i+/btCHUIIVVsI2RNiQCIiz021CGE1JDakXVbYnWL9mt/cfG+UIcQUr+sXRVxS4sdjttaXXRU/kz72vLPIq7f/F3E8x5Jp1pro/0ncgAAAAAAEAL+/op8vTy3kgAAAAAAAASdvzMwfpa0wBgzQ9If+3daa6N7jjgAAAAAAAgKfwsYv3q/ani/AAAAAAA46rl1VC6BEZH8KmBYax8LdCAAAAAAAACV8auAYYxpLOlBSa0k1dq/31rbIUBxAQAAAAAAlPB3Ec9xkn6UlCzpMUlrJX0doJgAAAAAAABK8XcNjIbW2jeNMXdba3Ml5RpjcgMZGAAAAAAAoVZsWQMjXPhbwNjn/TPPGNNd0kZJTQMTEgAAAAAAQGn+FjAeN8bUlfQPSS9Lipd0b8CiAgAAAAAA8OHvU0ime/+6XVJa4MIBAAAAAAAo73CeQnKLpBa+x1hrbwxMWAAAAAAAhJ5brIERLvy9hWSKpE8kzZPkDlw4AAAAAAAA5flbwDjGWvtQQCMBAAAAAACohMPPdtONMd0CGgkAAAAAAEAlDjoDwxizQ5KVZCQNMsb8Ic8jVY0ka62ND3yIAAAAAAAg2h20gGGtrROsQAAAAAAACDfRvIinMaaLpJckxUh6w1r7dJnX+0nav9zETkm3W2uXel9bK2mHPOtoFllrz6tqPH7dQmKMudwYU9dnu54x5rKq/ucAAAAAACD8GGNiJL0iqaukMyT1NcacUabZL5JSrLVnSxohaUyZ19OstW2qo3gh+b8GxlBr7fb9G9babZKGVkcAAAAAAAAg7PxF0mpr7c/W2j8lfSDpUt8G1trPrLW/eze/kNQ0kAH5W8CoqJ2/TzABAAAAAABhxBhzqzHmG5+vW8s0OV7Sep/tDd59lblJ0kyfbStpjjHm2wr+7SPibxHiG2PMSHmmj1hJd0n6tjoCAAAAAAAgXBXbo3MNDGvtGJW/5cOXqeiwChsakyZPAaOdz+6LrbUbjTEJkuYaY3601i484oDl/wyMuyT9KelDSeMl7ZH0f1X5jwEAAAAAQNjaIKmZz3ZTSRvLNjLGnC3pDUmXWmu37N9vrd3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FRxMXE8PAgQN5uUC/duaMGfS9//6yDrtUNbu1ITWq2+h2x9OMHvUhAwY+VGy5739YxZ3d+9GzR3/Kly9H164tAfhl3Rbu6fU8vXu/wMgR7/HiEO/88FYEnExgGIZRJM1X3L6ydF3DBhw6eJAjhw6RnZXFgrnziG3bulCZEykpbNu8hezsrAuu6+natmnDrJkzAdiwYQMBgYGEhYcXKdesWTPmz58PwMyZM2nbtu0F1fdUbdu0ZdbMWcCf8QcQFh5WpFxJ7U9JSWHz5s1kZ2WXXdClpH7Dhhw8cJBDhw6RlZXFd3Pn0rpN20JlWrVpy+zc87PpvPMTYbMR27IlM776qsxjLy2tW7dk9mzHG9ONGzcTGBhAWFhokXJNm97C9987PnGZNfMb2rRpBTg+pa9UqRIAFStWJC01jexsz78XLBG1yUlNwExPghw72btW43NF48KFTBPD18/xfTk/zMxTkJMDgP3oDse2F2tcL5qggIolHl+ybjtdYxthGAYN69Qg/XQmScfT2bznMDUjQ6huq0I5Xx86Nq/PknU7yjDyixdyXR1OHTrK6SMJ5GRnc3DBcqJimxUpd3Wv2zm05Ecyj6eWfZAudDnf/5dz2wGqXFeH04ePcuZIPGZ2NocXLCcy9tYi5a7s2ZUjS1ZxtoR7P/zmRpw+fJSM+CQXR1z6WrZszpxvFwCwefN2AgL8CQ0NKVLu9x27OXo0ocj+jh1bs3jRSuJz237ci34/NGjYkIMHDuT1e+bOnUubNm0KlWlToF+7ccMGAgv0a9etW0dqampZh12qYmIa8938lQBs3bqbgIBKhIRULlJu9U8b877ftm0P4RFVAMjIOJu3v0KF8pha0EG8mLMjMGYWs+/r0gzkQoVHRJBwND+7nBifQHhEhMvreooIm42jR4/mbSckJGA7rw3BwcGkp6djt9sBiI+PJ8Jmc7q+J4uwRRQTv61QmeLb7z1tLEmELYKE+AJtL6ZdEbYIEgqcn8SEBCJyz8/gYUMZN3oMOTne+9crwhbO0fj8DlpCQiI22/n3f2VOpp/Mu/4JCYl59/hnU6ZS+8orWLN2BfO//5YRI0djesFfc0ulKuScSsnbzjmVguFfpVCZc5t/wFKlGpUefJ9KvV4nc9VkLqelpxKPp2MLzR82bQsJJPF4OokpadhC8vdHhASReDzdHSH+YxXCQzmdkJy3fSbxGBXDQ88rE0JUXHP2zJhX9D8wTeLeHUv7L97hyu4dXB1uqbuc7//Lue0AfmGhZCTkJx0ykpLxCw85r0wIVeNuZf/Xxdz7uaLaxXF4wTKXxelK4eGhJBQ4B4mJyUREFE3cl6RWreoEBgYw+ZPxTJ/xIV26tHNFmC5hs9mIj8/vtyfEx2OzFe7zRdhsxBfo98R7Wb/274SFBZOYkP87ICkxhfDwKiWWt1qtdOjQgjWrN+Xti41tzIyv3+DNtwYwcsS7Lo33UpSDeUl+eaO/fAqJYRjXAPWAIMMwCk4YDAT8/qLeI8AjAFFVQgkJCCyFUIv8jCL7nH3/cTF1PUXxbTCdLuNMfU92se33Zgb/vO2xLVuSkpLCtq1bublJE5fF6Gr/+Prn/qK+rUVztu/4nd69H6BmzRp8OuUjOv1yB6dOnXZNwKWlmDad/8vLp0YDcpIPkjF7BEZQBBVvH8LpI89BVkYZBelexb3EDcMo9k90MWfTszlx39/43GNsHP8RZu4n7wUt6tuPjOQUygdXpuV7Y0nff4jk9VtcFm6pu5zv/8u57VBC+wtv1u//GFvf/ihv1EmR/8LHB1uLpmyb8JELAnS9i+3TWK1W6ta7moce7Ef58uX54st32bRpGwcPHi7NMF2iuN/Vl0uf708X2r4BAx5iw/odbNz4e96+5ct/YfnyX2jU6FoefbQHjz/uXdPHRf70d49RrQN0AioDnQvsPwmUuPKhaZofAB8ANKx1pUt+eyQmJGCrGpm3HRFpIznJufnMF1PXnfrcdx+9ejoWrtq0eTNVq1bNO2az2UhMKjwk8vjx4wQGBmK1WrHb7URGRpKU6GhnQnz839b3NH3u60Ovnr0A2LR5UzHxF76Gxbffs9vojISEBGyRBdpeTLsS4hOwFTg/ETYbSUmJtO/QgVatWxMTG0f58uXxD/Dn1bfe5Ln/9iuz+P+pe/v0okePuwDYsnkLVSNt/DnD32aLIDHx/Pv/BAGBAXnXv2CZO++8g/fec3RiDx78g8OHDnPFFVewebNnv5nLOZWCr3/+p44W/xDM0ycKlfGtG8e5374BwExLJCc9CUuVquQk7i3LUN3GFhJIwrG0vO2ElHTCgwPIyraTkJK/PzEljfAqpZ9cd6WMxGQq2fKnylWMCCUjOaVQmSp1r+LWVwYBUL5yEFWbN8a02zm8bHVe2bMnUjm87CdCrqvjVQmMy/n+v5zbDpCZlEwFW/401wrhYWSed+9Xrns1jccMBhz3vq35zZh2O/HLVwNgu/VmUn/fXeL0Ek/Uq9cd3HlXJwC2bvkdW4FzEBERRlJSSklVi0hMTOZEahoZGZlkZGTy66+bqHNNba9IYMQnJBAZmd9vt0VGkphYuM+XEB9PZIF+T6QX9Gv/zl13taVrV8fU1+3b9xJhC4HcARXhESEkJ58ott7D/76TysGBjB79erHHN2zYQbWoCIKCAkhLO+mS2EVc6S+nkJim+a1pmg8AnUzTfKDA11Omaa4uoxiLtW3TZmrUqkXVqCh8fH1p17kTKxYtcXldd/psyhQ6dOhAhw4dWLhwId26dwegUaNGnDx5kuRiflGvWbOGDh0cQ4W7d+/OwkWLAFi0eLFT9T3JZ1M+O6/9jkFB+fEnF6lTtP3evQI1wJZNm6gVXYuo6lH4+vrSsXNnluRe1z8tXbyIO3LPT4NGjTiVe35eHzeOFk2a0rJ5c/o9+SRrV6/2iuQFwOeffUnnTt3o3KkbCxct4Y47HKvwN2xY33H9k48VqbN27Tr+9S/H+iDdundl8eKlABw9Gk+zZo4RKCGhIURfEc2hQ4fKqCX/XE7iXiyVIzECw8BixefqZmTv/7VwmZPHsEZdD4BRIQhLcFXMNM9+bZemlo2v5ZvlGzBNk407/yCgoh/hVQK5vnY1DsQf41Dicc5lZfPdj5tp2bj4p9d4qpRtOwmoUY1KVW1YfHyo2S6WIyvWFCozp+N9zOnQhzkd+nBo8Sp+GT2Bw8tWY/Xzw6diBQCsfn7Ymt5I2p4DbmjFP3c53/+Xc9sBTmzbiX/1alSsasPw8SGqXSzxKwp3Qxd27sPCTveysNO9HFm8ko1j3s5LXgBEtfe+6SNffjmb7t0eonu3h1iyZBVdbndM+6hfvy6nTp7m2DHnExhLl/7IjTfWx2q14udXnvr1r2Xf3oOuCr1Ubd60iVrR0URVr46vry+dO3dm8Xn9nsUF+rUNvaRf+3dmzFhI794v0Lv3Cyxf/gsdO7QA4LrrruLUqTOkpKQWqXP77S1p2qQ+Lw4eX2iERlRU/nSaOnWi8fX1UfJCvNbfjcD40x7DMAYBtQrWMU3zQVcE5Qy73c7YoS/x7pRPsFgtfDv9a/bu3s2dvR2f0H899UtCwkL5Ys43VPL3xzRNej/Yl25t2nP61Kli63qTZUuXEhcXx4qVK8nIyOC5/v3zjk3+5BNeeP55kpKSGDtmDBMmTuTZ/v3Ztm0b06dN+9v63mDZ0mW58a/Ijf+5vGOTP5nMC8+/kNv+sUyYOIFn+z+b2/7pAISFhTFn7hz8/f0xc0wefPBB2rRuw6lTnr/Imd1uZ8TQoUyaMgWr1crX06ezZ/duevbuDcBXU6eyfOkyYuLiWJx7fgYWOD+XguXLVhIb24Kly34gMzOTF54fnHds0sfvMXDAEJKSkhn3yuuMf/s1nnnmabZt38GM6Y7lfCZOeJdxr45m/vffYGAw7pU3OHEi1U2tuQBmDpkrPqZil8FgsZC1fRk5xw/je51jMbOsrYs498tM/Fo/RsVer4EBZ1dPxcx0dFL82j2NtVpdDL8AKj3wLud+nk7Wdu/q0D/zxles27qfEydP0+LhsTzZszXZueuc9Gp3CzE31mHF+p20eex1KpT3ZfQTjg6tj9XK0Ie78PCIydhzTLq3upGranjX/GjTnsOvYycS9+4YDIuFfd8uIG3vQWrf6fiEds9fzP33C6lMizeGA2D4WDn4/TLiV/9aYnmPdDnf/5dz23Hc+5temcCt74wFi4WDc37g5L6D1OruuPcPzCz53gew+pUn/JYb2TDqrTKI1jVWrlxLixZN+f6HL8nMPMuLg8fkHXv3vXEMHfIKyckp9L63Ow8+2IvQ0CrM/mYyK1euZdjQcezbd5Aff/yZ2d9MJicnh5lff8eePfvd2CLn2e12hg0dypQpU7BYrcyYPp3du3dzT26/54upU/P6tctz+7XPF+jXjn/7bZo0bUpwcDCr167lrTffzOsPe4ufftrArbc2YvY348nMPMeIl/LXsHhr/ABeHvk+x46dYMDAh0lISObjjx3TQ5YtW8dHH82kZatb6NihBdnZdjLPnmPQwLfc1BLvdelMSPJ+hjPzwwzDWA2sAn4D7H/uN02zuMU9C3HVFBJvkGp6/lMNXMvrZpiXqnLuDsDN7NaSnxRxOdjY77q/L3SJCmjZw90huNUXvd9zdwhu1fmhYHeHIG6yePJxd4fgVi9mnnN3CG515rR3jOhwldAw711brDT88uu0S7rjX6dmrUvyPe3Ogwe87ro5OwKjommaL7g0EhERERERERGREjj7GNV5hmF43zPXREREREREROSS4OwIjKeBQYZhnAWycMwNME3T9K4l3EVEREREREQuwCU5f8RLOZXAME0zwNWBiIiIiIiIiIiUxKkEhmEYLYrbb5rmytINR0RERERERESkKGenkBR8BqMfcDOOJ5K0LPWIRERERERERETO4+wUks4Ftw3DqA6Mc0lEIiIiIiIiIh4iR6tgeAxnn0JyvsPAdaUZiIiIiIiIiIhISZxdA2MC+YuvWoCGwCYXxSQiIiIiIiIiUoiza2D8WuD7bOBL0zR/ckE8IiIiIiIiIiJFOLsGxqeGYZQDrs7dtdN1IYmIiIiIiIiIFObsFJJY4FPgAGAA1Q3DuF+PURUREREREZFLmZbw9BzOTiF5HWhrmuZOAMMwrga+BG50VWAiIiIiIiIiIn9y9ikkvn8mLwBM09wF+LomJBERERERERGRwpxexNMwjEnAZ7nbvYHfXBOSiIiIiIiIiEhhziYw/gM8DjyFYw2MlcD/XBWUiIiIiIiIiCfQGhiew9mnkJwF3sj9EhEREREREREpU06tgWEYRifDMDYYhnHcMIx0wzBOGoaR7urgRERERERERETA+SkkbwHdgC2maWoEjYiIiIiIiIiUKWcTGIeArUpeiIiIiIiIyOVEb4I9h7MJjOeB+YZhrADO/rnTNE2tiSEiIiIiIiIiLudsAmMUcArwA8q5LhwRERERERERkaKcTWBUMU2zrUsjEREREREREREpgVNPIQEWG4ahBIaIiIiIiIhcVsxL9MsbOZvAeBz4wTCMDD1GVUREREREROTSZxhGe8MwdhqGsccwjAHFHDcMw3g79/hmwzBucLbuP+HUFBLTNAMMw6gCXIVjHQwRERERERERuUQZhmEF3gHaAIeBXwzDmGOa5vYCxf6FI09wFXAL8C5wi5N1L5hTCQzDMB4GngaigI1AE2A10OpifriIiIiIiIiIeKSbgT2mae4DMAzjK+B2oGAS4nZgimmaJrDWMIzKhmFEArWcqHvBnF3E82mgMbDWNM04wzCuAV5ypuI5M+efxub1rO4OwM3sGO4Owa38jcv7DsgsX8XdIbiVT3iUu0Nwmy96v+fuENzqnqmPujsEt1rx7/HuDsGtzmQ527W69FxlO+3uENyqYlItd4fgVl9EnXN3CG41MOged4cgcsEMw3gEeKTArg9M0/ygwHY14FCB7cM4RlnwN2WqOVn3gjn7VzbTNM1MwzAwDKO8aZq/G4ZR52J/uIiIiIiIiIiUvdxkxQd/UaS4T6TPX/+zpDLO1L1gziYwDhuGURn4BlhkGMYJ4OjF/nARERERERER8UiHgeoFtqMomgcoqUw5J+peMGcX8bwj99vhhmEsA4KAHy72h4uIiIiIiIiIR/oFuMowjGjgCNATOH++1Bzgidw1Lm4B0kzTjDcMI9mJuhfsgidqmqa54mJ/qIiIiIiIiIh4LtM0sw3DeAJYgGOJx49N09xmGMajucffA+YDHYA9wBnggb+qe7ExXb4rTYmIiIiIiIj8rcv34QSmac7HkaQouO+9At+bwOPO1r1YltL8z0REREREREREXEEJDBERERERERHxeEpgiIiIiIiIiIjH0xoYIiIiIiIiIiW6fNfA8DQagSEiIiIiIiIiHk8JDBERERERERHxeEpgiIiIiIiIiIjH0xoYIiIiIiIiIiXSGhieQiMwRERERERERMTjKYEhIiIiIiIiIh5PCQwRERERERER8XhKYIiIiIiIiIiIx9MiniIiIiIiIiIl0RqeHkMjMERERERERETE4ymBISIiIiIiIiIeTwkMEREREREREfF4WgNDREREREREpET63N9T6EqIiIiIiIiIiMdTAkNEREREREREPJ4SGCIiIiIiIiLi8bQGhoiIiIiIiEgJDAx3hyC5NAJDRERERERERDyeV4/AaB7TgoHDhmG1Wvj6q2l89O57RcoMGj6MFnGxZGRkMqh/f3Zs3UatK67gjYkT8spE1ajOhDfe5LOPJ5dh9BenRUwMQ4YNw2q1Mu2rr3j/3XeLlBk6fDixcXFkZGTwfP/+bNu6lXLly/PV9OmUK1cOq48PP8yfz/g333RDCy7esOHDiItzXNv+/fuzbeu2ImWiqkcxccIEgioHsW3rNvr1e4asrCxu73o7jz76KABnzpzmxcFD2LFjR9k24CI0i2lB/6EvYrVamT1tOp+8+36h47WuvILhr77CNfXq8c5rr/PZh5Pyjg0bN4bbWrbkeEoKd7frUNahl5pBg56mRYumZGRmMmjQaHZs31WkzD33dOO+++6mRs0omjXtSGpqGgCNGzdi4jtjOHI4HoBFi1fw7v8+Kcvw/7Gfdicxbv52ckyTO26ozoMtahc6fjIzi8FfbyQhLYPsHJP7br2CrjdU58CxUzw/fUNeuSMnzvCfuKu5t1l0WTfhokQ2u4kbn38Mw2Jh7+zv2T55WrHlqtS7mrZT3uanF0ZxaPEqALrM/4zs0xmYOTnkZNtZ0Pvxsgz9og2cOJPlv/5OSFAl5o3/b5HjpmkyatI8VqzfiV/5cox9ojv1rqwGwMr1uxj18TxycnK4q3VjHukWU8bRl47gW26m9n+fwrBaiJ/7HYc+m1roeFCjhlz3ymgyjzpe28dWrOTg5E8xypWj4f8mYPH1xbBaSV62nIOTvOdvPkBo08Zc++wTGBYLh7+dz75Pvyx0vMoNDbjh9ZFkHE0AIHHZKvZ89JlTdb2B/41NiPy/Z8Bi4cSCORybMaVImUrX34DtkX4YPj7Y01PZ/8J/nK7rDZ7t35dbb21EZuZZXhr+Ljt37i9SZuTIJ7m27hVkZ9vZtm0Po0d9iN1up0XMTTz66N2YOSbZdjtvvP4pmzbtdEMr/pmAm5pQ9T/9MCwWjv8wh6RpnxU6Xqn+DUS/NI5zCUcBSPtxOYlTPwYgtFtPQtp3wcQkc/9eDr32MmbWuTJvw8X6vweup/EN4Zw9a+eNdzawd39aiWUfffB62sTVoHuf7wBocpONPj2vIceEHLvJ+59sYfvvx8sqdJFS5bUJDIvFwosjR/Bw7z4kJiQwbc63LFu8mL279+SVaREXS83oWrSPiaN+o4YMe/llena9gwP79tGtQ8e8/2f5z2tZsmChm1py4SwWC8NHjuT+3r1JSEhg9pw5LFm8mD27d+eViY2Lo1Z0NC1jYmjYqBEjXn6Z7l27cu7sWe7t1YszZ87g4+PDtK+/ZsXy5WzcsOEvfqLniY2LJTq6FrExcTRq1JBRL79M1653FCk3YMAAJk2axNy58xg16mV69Libzz+fyqFDh+hxdw/S09OJjY1hzJjRxdb3RBaLhRdGDOexe+8nMSGBz+fMYsWiJezfk3/vp6WmMm74COLatilSf+7Xs5j26eeMeOPVMoy6dLVo0YSaNavTvn1P6jeox7Ch/enZ85Ei5TZs2MLy5av5dMqEIsd++20Tj/3nhbIIt9TYc0zGzNvGe/ffQkSgH73f/5GYayK4Mjwgr8y0nw9yRbg/b9/bmOOnz9L17RV0rF+NWqH+TH/strz/p+1rS2hZN8JdTflHDIuFmwY+ydJHXyAj8Rjtpk7k8Io1pO/7o0i5hk8/TMKa34r8H0v+3Z+zqellFXKp6hZ3A/f+qwkvvD2j2OMr1+/iQHwKC995lk27DjH8g2+Z8cpj2O05jPhwDpOHPUhESCB3Pv8/Wja+htrVvev6Y7FwVf9+bH76Gc4mJXPDpA9IWfUjZw4cLFQsbdNmtj43oNA+89w5Nj35X3IyMjCsVhq+9w7H1/7MyW3by7IF/5zFQr3nn2bdE8+RmZhMs0/fJWnlak7tL9z2Exu28Nszg/9RXY9msVD1sefYP/hJso8lccVbn3By7SrOHsp/A2+p5E/k489zcMjTZCUnYg0KdrquN2h2a0NqVLfR7Y6nue66qxgw8CEe6PtikXLf/7CKIUMcf/NeHvUUXbu2ZObMRfyybgsrV/wKQO3aNRgz9r/cdeczZdqGf8xiodoT/dk34CmyjiVx1YTJpK1Zxdk/DhQqdnrLRvYP7V9on09IGKFd72bnw70wz52l5uCXqRzbhhOLvivDBly8mxqFUy2yEg8/uYQ6VwXzxL8b0G/QymLLXnVFZfwr+Rbat3FrMmv7O5KbtWoEMvCZm/i//y51edwiruC1U0iub9iAPw4c5PChQ2RlZfH93Lm0bFP4zVrLNm34duYsADZv2EhAYCCh4WGFyjS59Vb++OMgR48cKbPYL1aDhg05eOAAh3LbPm/uXFqf1/bWbdowe+ZMADZu2EBgYCBh4eEAnDlzBgAfHx98fH0xTbNsG1AK2rZpw6zca7sh99qGnXdtAZo1a8r8+d8DMHPmTNq2bQvA+t/Wk57ueBOzfv0GbJG2Mor84l3XsAGHDx7kyKFDZGdlsWDud8S2bV2ozImU42zfvIXs7Owi9dev+4W0tNQyitY1Wra8jW+//QGAzZu2ERDoT2hYSJFyO3bs5mjup5GXgq2HU6lepSJRVSri62Oh3fVVWf57YqEyhgGnz2ZjmiYZ5+wEVfDFaik8b/PnfceICq5I1coVyzL8ixZyXR1OHTrK6SMJ5GRnc3DBcqJimxUpd3Wv2zm05Ecyj6eWfZAu1LheNEEBJV+zJeu20zW2EYZh0LBODdJPZ5J0PJ3New5TMzKE6rYqlPP1oWPz+ixZ5z0jzv4UWPdaMg4fIfNoPGZ2NkmLlxByW3On6+dkZABg+Phg+PiAF/3tq1zvGk4fOkLGEUfb4xctJTym6L1f2nU9RYWr63L26GGyEo5iZmeTtnIRAU1bFCpTObYd6auXkZXs+J1oTzvhdF1vEBPTmO/mO96wbt26m4CASoSEVC5SbvVPG/O+37ZtD+ERVQDIyDibt79ChfLedPtTsU5dzh09zLnca5i6YhFBzZy/hobViqV8ebBYsZT3I+t4sgujdY0mjSNZsuIQADt3n6BSJV+CK5cvUs5igQf71GXSZ4VHJWdm2vO+9/OzetX19xiGcWl+eaESExiGYcw1DGNOSV9lGWRxImw2EuLj87YT4hMItxV+ExpuiyDhaH6ZxIR4IiIKl+nQpRPz58x1bbClLMJmI75Q2+OJOK/tETYbR48ezS+TkIAtwvFpm8ViYe78+axbv56fVq1i08aNZRJ3aYqwRXC0wLVNSIjHdt61DQ4OJj09Hbvd8Us7Pj6BCFvRTxx79OzB8uUrXBtwKQqLKHxfJ8UnEB7hZZ+kXqTwiFASEpLythMTkogID72g/6Nhw+uYNfsT3n//NWrX9o5pFEknM7EFVcjbjgj0Iyk9s1CZnrfUYn/yKdq8uoQ731nJc/+qi+W8BMaCLUf5V/2qZRJzaaoQHsrphPyO55nEY1Q877pXCA8hKq45e2bMK/ofmCZx746l/RfvcGV3750+VZLE4+nYQoPytm0hgSQeTycxJQ1bSP7+iJAgEo973yiUcmGhnE3Mf92fTU6mfFjRxHXgdfW48dOPuf71cVSMrpV/wGLhxk8m0ey7bznxy6+c3O49SRy/sFAyC7Q9M/EYfsW0vfL1dbl16ofcNH4M/lfUuqC6nsw3JJysY/nJ2uxjSfiGFG5DuWo1sPoHEj32f1w5/lMqt/yX03W9QVhYMIkJKXnbSYkphIdXKbG81WqlQ4cWrFm9KW9fbGxjZnz9Bm++NYCRI4pOPfZUvqFhnEvOv4ezkou/hhXrXs/V735G9Kg3KV/T8Xc9OyWZ5BlTufbzb6j31TzsZ05z6rd1ZRZ7aQmt4kdySkbe9rGUDEKrVChSrnP7K/j51wROpJ4tcqzpzZG8/1ZLXhrYhLfe9a6R1yIF/dUUktdy/+0G2IDPc7d7AQf+6j81DOMR4BEAW5UQgv0D/qr4P1LsSrDnpRONYrJKBUcb+Pr6Ete6NW++4l1D6YvNlV1A23NycujcoQMBgYG898EHXH311ezaVXT9AE/2d9fW2TJNmzahR4+7ubP7XaUboAs5065LXfHnwPn627fvpHWrOzlzJoMWLZowYeJo/tW+VylG6BrFtfH8U7F6TzJ1IoP48IEmHDp+hkc//ZkbalbB388xnDQrO4cVOxN5qs01ZRBxKXPi3r/xucfYOP4jzJycImUX9e1HRnIK5YMr0/K9saTvP0Ty+i0uC7esFX9/GBT30vDOz1z+/u/+qZ27WNvtbnIyMqjStAn1xo7mlx73OA7m5PBb34ew+vtz3ZiXqXhFNGf2eck0Aifu/fSdu1nepRf2jEzCmt3CDa+OYGX3+5yq6/GKu2HP/5tvtVKh9jXsH/g4lvLlueL1SZzZudWput7gQv/2DxjwEBvW72Djxt/z9i1f/gvLl/9Co0bX8uijPXj88ZddEmvpK+61X3gzY8/v7Li3KzmZGQQ0bkr08HH8/sBdWP0DCGzWgh33dcN+6iS1hoymcqv2pC75oWxCLy3FnoLCJ6FKsB/Nm1blhWE/FftfrFkXz5p18Vx3bQh9elzL4JGrXRGpiMuVmMAwTXMFgGEYI03TLDhOa65hGMVPusqv+wHwAUDdmtEu+SuRkBCPLTIyb9sWaSMpsfBQ6sT4BGxV88tE2CJJSsovc1tsLNu3biPl2DFXhOgyCQkJRBZqeySJ57U9IT6eqlWr8ucMcJvNRmJSUqEyJ9PTWbtmDS1iY70igdHnvj706tkTgE2bN1O1wLW12SJJTCp8Do4fP05gYCBWqxW73U5kpI2kAp9CXXPNNYx9ZSx973+A1NTUMmlDaUhKKHxfh0faSD7v2l6Ket3Tjbvu7AzAlq07sNnC845F2MJJSnb+dXz69Jm871euXMuQoc9SuXJQ3iKfnioi0I+EtPxPYBLTMwkL8CtU5tv1h3jwttoYhkGNkEpUC67I/mOnuT6qMgA/7k7imsggQvyLDj31dBmJyVSy5X/qVjEilIzklEJlqtS9iltfGQRA+cpBVG3eGNNu5/Cy1Xllz55I5fCynwi5rs4llcCwhQSScCz/Hk5ISSc8OICsbDsJKfn7E1PSCK8S6I4QL8q55GTKR+S/7suHhXH2vL/f9jP5r+3ja9ZyVf9++AQFkZ2W3377qVOkbthIlVtu8ZoERmZSMn4F2u4XEVqk7dkFfq8lr/6Zui88jW9QoFN1PV3WsSR8Q/NHGvqEhpN1/FiRMvb0VMyzmdjPZnJm6wb8oq9yqq6nuuuutnTt2gqA7dv3EmELgdwBFeERISQnnyi23sP/vpPKwYGMHv16scc3bNhBtagIgoICSEs76ZLYS1PWsSTKheXfw75h4UWmgeQUeO2f/GUNhtUHa2AQ/g1u5FzCUey5U2fTflxOpbrXe0UCo1O7aNq1rgnA7j0nCAvJH3ERGlKBlOOFR2BeGR1EpK0SkyY4phWXL2flowmtePjJJYXKbd2RQqStIoEB5Ug/6X2LmYo4swZGmGEYV/y5YRhGNOD2sXdbN22mZnQtqlWPwtfXl3917syyRYsLlVm6eDG3d+8GQP1GDTl58iTHkvJ/4XXo0pn5c9w+G+aCbd60iVrR0URVr46vry+dOndmyaJFhcosXryYO7p3B6Bho0acPHmS5KQkqlSpQkCgo+Navnx5bm3enL0FFn/0ZJ9N+YwOHTrSoUNHFi5cSLfca9so99omJxWd07hmzVo6dHAMI+3evTsLc89T1apVee/9d+nX7xn27/eODuyftm3aTPVaNakaFYWPry/tOndkxaIlf1/Ry335xSy6dXuAbt0eYMmSVdx+e3sA6jeox8mTpzh23hvZvxIamj/s9vrrr8ViWDw+eQFQr1oQfxw/zZETZ8jKzmHBlqPEXFN4+lBk5Qr8vM/ROU85dZYDx04RFZy/bsIPW47S/nrvmz4CkLJtJwE1qlGpqg2Ljw8128VyZMWaQmXmdLyPOR36MKdDHw4tXsUvoydweNlqrH5++FR0dP6sfn7Ymt5I2p4DbmiF67RsfC3fLN+AaZps3PkHARX9CK8SyPW1q3Eg/hiHEo9zLiub737cTMvG17o73AuWvuN3KkRF4RcZieHjQ3jrVqT8WPiTRt8q+a/tgGuvBcNCdloavpWDsPr7A2ApV47gm27kzEHvWcQybfvvVKpRjQpVbRg+PkS2aUnSysL3frmQ4Lzvg+peg2ExyEpLd6qup8vYtYPyVavjG+G49kEt2nBybeHP0k6uXUnFeg3BYsUoX54Kdepx9tABp+p6qhkzFtK79wv07v0Cy5f/QscOjs8Tr7vuKk6dOkNKSmqROrff3pKmTerz4uDxhUZoREXl/62oUycaX18fr0heAJzZuYNy1apTzua4hpVj2pC2ZlWhMj7B+a/9CnXqgsXAnp5GVnIila65DqO8I2nv3+imIot/eqp5C/bz5HPLefK55az5JYFWMdUBqHNVMKfPZBWZJvLL+kTu/fcCHnh8EQ88voiz5+x5yYtIW6W8cldGB+HjY1HyQryWM08h6QcsNwxjX+52LeD/XBaRk+x2O6OGDuPDKVOwWC3Mnj6DPbt306O3Y6jotKlfsHLpMlrExfHDyuVkZmQwuP/zefX9/Pxodltzhg8aXNKP8Fh2u52Xhg7lkylTsFitfD19Ort376ZX794AfDl1KsuXLiU2Lo6lK1eSmZHBC/0dqzKHhYfz6htvYLVYsFgsfDdvHsuWet8qxMuWLiMuLo4VK5eTkZHBcwWu7eRPPuaF5weQlJTE2DFjmTBxAs/2f5Zt27Yzfdp0AJ56+imCg4N5eeRIALLt2XTpfLtb2nKh7HY7rwx9iXemTMZitTJn+gz27d5N996OKRAzp35JSFgon8/5hkr+/phmDvc8+AB3tmnP6VOnGP32m9zY5BYqBwfz/Zofee/N8Xw7vfinGniqlSvW0KJFU35YMI3MzEwGDxqdd+y9919lyItjSU5O4d577+TBh+4hNLQK33z7KStXrmHokFdo2zaWnr3uIDvbztmzZ3n22WFubI3zfKwWBnS8jv9MWUdOjsntN0RROzyAGb843ojd1bgm/465iqGzN3HnxJWYmPy37TUEVyoHQMY5O2v3HuPFLte7sxn/mGnP4dexE4l7dwyGxcK+bxeQtvcgte/sBMCer4tZ9yKXX0hlWrwxHADDx8rB75cRv/rXsgi71Dzzxles27qfEydP0+LhsTzZszXZuWv89Gp3CzE31mHF+p20eex1KpT3ZfQTjiS2j9XK0Ie78PCIydhzTLq3upGranjhujl2O3veeIvr33wNw2ohYd58zuw/QGTXLgDEfzOHsLhYqt5xO6bdTs7Zs+wY+hIA5UJCqDNkEIbFimExSF6yjOOrvedNvGnPYfu4CTR++xUMq5XDc77n1L4DVO/mGJV2aNZcbC1jqHFnF8xsR9s3Dn75L+t6lRw7R999jVovv41hsXBi4VzO/rGf4A6Op4edmD+bs4cOcOq3tdT+31TIyeHEgjmcPejouhZX19v89NMGbr21EbO/GU9m5jlGvJS/hsVb4wfw8sj3OXbsBAMGPkxCQjIff+y4/suWreOjj2bSstUtdOzQguxsO5lnzzFo4Ftuask/kGPnyMTXuGL0eLBYOL5gHmcP7ieko+P6p3w3m6DbWhLaqZvjtX/uLAdHDwHgzO/bSF21lKv/9ymm3U7Gnl2kzP/GjY35Z35Zn0jjRhFMmtCas+fsvPlO/hoWLw1swvj3NnL8RGaJ9W+9JZJWMdXJtpucO2dn7Jve9ffPExS7fIG4heHMPEjDMMoDf06Y/t00zaIrw5TAVVNIvMFZis7BvpzYvfchN6WiimF1dwhulVnBe57s4gq/Db/Z3SG4zewxl860jH/inqmPujsEt1rx7/HuDsGtzmR57RPqL1r1sNPuDsGtHkiq5e4Q3OqjKt4zqskVBgYNdHcIbjV/xu2X9Dv8K6LrXJLvafft3+l11+1v/8oahnHfebsaGIaBaZpTXBSTiIiIiIiIiEghznxM0LjA935AK2A9oASGiIiIiIiIiJSJv01gmKb5ZMFtwzCCgM9cFpGIiIiIiIiIx7i8p8Z7kn9yJc4AV5V2ICIiIiIiIiIiJXFmDYy5wJ+LlliAusB0VwYlIiIiIiIiIlKQM2tgvFbg+2zgoGmah10Uj4iIiIiIiIhIEc6sgbGiLAIRERERERER8TSG4XVPG71k/e0aGIZhNDEM4xfDME4ZhnHOMAy7YRjpZRGciIiIiIiIiAg4t4jnRKAXsBuoADwMTHBlUCIiIiIiIiIiBTmzBgamae4xDMNqmqYdmGwYxmoXxyUiIiIiIiIikseZBMYZwzDKARsNwxgHxAOVXBuWiIiIiIiIiAcwnJm4IGXBmSvRJ7fcE8BpoDrQ3ZVBiYiIiIiIiIgU9JcjMAzDsAKjTNO8F8gEXiqTqERERERERERECvjLERi5a16E5U4hERERERERERFxC2fWwDgA/GQYxhwcU0gAME3zDVcFJSIiIiIiIiJSUIkJDMMwPjNNsw/QA3gTx2iNgLIKTERERERERMTdDKeWjpSy8FcjMG40DKMm8AcwoYziEREREREREREp4q8SGO8BPwDRwK8F9huACVzhwrhERERERERERPKUOBbGNM23TdO8FphsmuYVBb6iTdNU8kJEREREREREyszfLuJpmuZ/yiIQEREREREREU9jGIa7Q5BcWo1ERERERERERDyeEhgiIiIiIiIi4vGUwBARERERERERj/e3a2CIiIiIiIiIXLYMfe7vKXQlRERERERERMTjKYEhIiIiIiIiIh7P5VNI/Ayrq3+Ex/LDynEzy91huJHp7gDc6rSZ7e4Q3Con66S7Q3CrCtfd6u4Q3KbzQ4fdHYJbrfj3eHeH4FYxHz7t7hDEjWb3edfdIbhNtv2Uu0Nwq647490dgltVr77E3SG42e3uDkAuE1oDw4Uu7+SFiIiIXE4u5+SFiFzaDK2B4TF0JURERERERETE4ymBISIiIiIiIiIeTwkMEREREREREfF4SmCIiIiIiIiIiMfTIp4iIiIiIiIiJTD0ub/H0JUQEREREREREY+nBIaIiIiIiIiIeDwlMERERERERETE42kNDBEREREREZESGIY+9/cUuhIiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PK2BISIiIiIiIlICw7C6OwTJpREYIiIiIiIiIuLxlMAQEREREREREY+nBIaIiIiIiIiIeDytgSEiIiIiIiJSAsPQ5/6eQldCRERERERERDyeEhgiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PC3iKSIiIiIiIlICLeLpOXQlRERERERERMTjKYEhIiIiIiIiIh5PCQwRERERERER8XhaA0NERERERESkBIZhdXcIksurExjNYlrQf+iLWK1WZk+bzifvvl/oeK0rr2D4q69wTb16vPPa63z24aS8Y8PGjeG2li05npLC3e06lHXoFy0mJoahw4ZhtVqZ9tVXvPvuu0XKDBs+nLi4ODIyMujfvz/btm51uq43GDZ82Hnt21akTFT1KCZOmEhQ5SC2bd1Gv379yMrK4sorr+TV116lXr16vPbaa3z4wYduaME/d1tMDIOHDcVitTLjq2l8WMw1HDx8GDFxcWRmZDCgf3+2556fJT/+yOnTp8ix52C3Z9O9c5eyDr9UDBnyAjGxzcnIyOSFF4awfdvvRcrc26cnffv2pmbNGtzcOIYTJ1IvqL4nWrl+F6M+nkdOTg53tW7MI91iCh1PO5XBoIkz+SPxOOV9fRj9eDeurmkD4NN5PzFj0S+YwF2tG9O3861uaMHFsdZogF+LB8CwkLV9Ced++7ZwgXIVqND2KYyAEDCsnNswl+wdywHwa/UfrLVuwMxI48wX/cs++FIQfMvN1P7vUxhWC/Fzv+PQZ1MLHQ9q1JDrXhlN5tF4AI6tWMnByZ9ilCtHw/9NwOLri2G1krxsOQcnTXZHE/6xgRNnsvzX3wkJqsS88f8tctw0TUZNmseK9TvxK1+OsU90p96V1YC/f914g8v9tR/erDH1+z+GYbVwcPb37Prkq2LLVa5bh9hP32bdgJc5umQV/jWjaDz2xbzjlapFsuO9T9n7xayyCr3UPP/C/3Fr85vIzDzLsCFv8vvve4uUGTW6P3XrXUV2djZbt+5i1MiJZGfbna7vqVrExDBs2DAsuX3X90ro98bm9nsK9ntfefVVWrZsSUpKCu3bti3r0EvNU093p0nTupzNPMeY0VPZtetwkTJDht5HnWuqk51tZ8eOP3ht3FfY7TlUquTHi0PvIyIiGKvVwldfLuX7+T+7oRUiF89rp5BYLBZeGDGcJ/s+RPc27WnfpRPRtWsXKpOWmsq44SP47MOPitSf+/Usnrj/wTKKtnRZLBZGjBxJ3/vvp03r1nTp0oXaV11VqExsXBzR0dHExsQwaOBARr38stN1vUFsXGxu+2IZNHAQo14eVWy5AQMGMGnSJOJi40hLS6NHjx4ApKamMnzYcD780LsSF+C4hkNHjuDh+/vSsXUbOnXpwpVXFb73W8TFUis6mrYxsQwZOIjh552f+3v2omuHDl6bvIiJaU7NWjVo3aozQ14cwYiXXiy23PrfNnL/ff/H4cNH/lF9T2O35zDiwzl89GJfvhv/X+at2sSeQ4mFyrw3cznXRkcy982neOWpOxn18TwAdh1MYMaiX5gx7jG+feNJlv/2OweOHnNHM/45w8Av9iHOzBnN6an98Ln6VizB1QoVKVe/Pfbjhznz5fNkzBqOX/P7wOL41CRrx3Iy5ox2R+Slw2Lhqv792PLsc/xyz32Et25FxVo1ixRL27SZ3/o+xG99H+Lg5E8BMM+dY9OT/+W3+x/kt/sfpEqTWwioV7esW3BRusXdwEdD+pZ4fOX6XRyIT2HhO88y8tGuDP/Akdxy5nXj6S77177FQoMXnmT1k4NY3P0hotrHERBdo9hy1z39MIlrfs3bdergYZb1etTx1fsx7JlnObrsxzIMvnQ0b34TNWpU5fbO/+blERMY9OLjxZb7fv5y7rj9/7ir++P4lS/PHXe0u6D6nqhg37XtX/R7a0VHExcTw8CBA3k5t98LMHPGDPref39Zh12qmjSpS1T1MO7pOZJXX53GM/3vLrbcooW/cu89o+h731jKl/elU+dmANzR7TYOHkjgwb6v8NSTE3j8ia74+GhEgXgnr01gXNewAYcPHuTIoUNkZ2WxYO53xLZtXajMiZTjbN+8hezs7CL116/7hbS01DKKtnQ1bNiQgwcOcOjQIbKyspg7dy5t27QpVKZtmzbMmjkTgA0bNhAQGEhYeLhTdb1B2zZtmTXT8emJo30BhIWHFSnXrFkz5s+fD8DMmTNpm5t5T0lJYfPmzWRnFb03PF39hg05eOAgh3Ov4Xdz59KqTeFPFFq1acs3uedn04YNBJZwfrxV69ZxfDN7LgAbN25xXP+w0CLltm//nSNHjv7j+p5m857D1IwMobqtCuV8fejYvD5L1u0oVGbvoSSa1L8SgCujwjmSlMqx1JPsPZJMg6trUKF8OXysVhrXjWbRz9vd0Yx/zBJRm5zUBMz0JMixk71rNT5XNC5cyDQxfP0c35fzw8w8BTk5ANiP7nBse6nAuteScfgImUfjMbOzSVq8hJDbmjtdPycjAwDDxwfDxwdM01WhukTjetEEBVQs8fiSddvpGtsIwzBoWKcG6aczSTqe7tTrxtNd7q/9KtfV4fTho5w54rj3Dy9YTmRs0VEkV/bsypElqzh7PLXY/yf85kacPnyUjPgkF0dc+mLimjBv7lIAtmzZSUBAJUJDg4uU+/HH/OTN1q27CI8IvaD6nqhBMX3XNuf1XdsU6Pdu3LCBwNx+L8C6detITU0t67BLVfPbrmfBD+sA2L7tAP7+FQgJCSxSbu3a/Nf2ju0HCQsPAhy/7itULA9AxQrlSE8/g92eUwaRi5Q+pxIYhmEU+StR3L6yFBYRQULuEFmApPgEwiMi3BhR2Ymw2Tgan9/2+Ph4Imy2omWO5r9xS0hIwBYR4VRdbxBhiyimfYXbERwcTHp6Ona7Y+iko63ef49E2CJIiM9ve2Ix7YqwRZBw3vmJyDs/JpM+/4yZ8+Zyd69eZRFyqYuICCc+Pv/Tx4SERCIiwsusvrskpqRhCwnK244ICSLxeHqhMtfUsrForWO60ObdhzianEpCSjpX14jg1+37OXHyDBlnz7Fy/U4SjqWWZfgXzVKpCjmnUvK2c06lYPhXKVTm3OYfsFSpRqUH36dSr9fJXDUZ8K436iUpFxbK2cT8N15nk5MpH1Y0MRl4XT1u/PRjrn99HBWja+UfsFi48ZNJNPvuW0788isnt3vXm/i/k3g8HVto/uvDFhJI4vF0p143nu5yf+37hYWSkZB/72ckJeMXHnJemRCqxt3K/q/nlfj/RLWL4/CCZS6L05XCw0NISEzO205MPEb4eeegIB8fKx07xbH6p9/+UX1PYrPZiC/Qd02Ij8dWTL83vkC/Jz6333upCA0NIikpNW87OSmV0AK/785ntVpo164x69Y6fs/PmrmSmjVtzP5mJJM/Hcjb42dielkS290Mw3JJfnkjZ9fAmADc4MS+MmMYRpF9l8sLsWjLi7a9pPPjTF1v4Mz1v1TvEaOYq3ghbe/VrTtJSUlUCQlh8uefs2/vXn5dt841wbpIMc27oGt7sfXdpbgIz2/KI91iGDVpHrc/M4Gra0ZwbXQkPhYLV0aF8/AdMTw4/GMqVihHnVqRWK1eNny0+AtXaNOnRgNykg+SMXsERlAEFW8fwukjz0FWRhkF6Up/3/5TO3exttvd5GRkUKVpE+qNHc0vPe5xHMzJ4be+D2H19+e6MS9T8YpozuzbXwZxl43iXsKGYTj1uvF0eu0Xd+8X3qzf/zG2vv1R3oirIv+Fjw+2Fk3ZNqHotGJvUPzf/pLLDxz0GOt/28qGDdv+UX1PcjH93ktFse37i/LPPHs3mzbtZfPmfQDcfMu17Nl9mP8+NYFq1UJ5483HeWDTK5w5k+miiEVc5y8TGIZhNAWaAWGGYTxT4FAgUOJfP8MwHgEeAaheJYzQgKJDnC5WUkICtqqRedvhkTaSk7xvSOA/kZCQQNXI/LZHRkaSlFh4LmxCfDxVq1bN27bZbCQmJVGuXLm/reup+tzXh149HSMGNm3eVEz7Crfj+PHjBAYGYrVasdvtuW31/nskISEBW2R+2yOKaVdCfAK2885PUu75Scp9nRxPSWHRggXUb9jAKxIYve/tQY+7uwGwecs2IiPzP1mx2SJISkouqWoRCQlJF1XfXWwhQSSkpOVtJ6akEV6l8O9X/4p+jHnyTsDReWv16KtERTiGCd/V+ibuan0TAG98voCIkJI/vfFEOadS8PXP/8TQ4h+CefpEoTK+deM499s3AJhpieSkJ2GpUpWcRO9ZrK4k55KTKV9gpFD5sDDOHiu8loH9zJm874+vWctV/fvhExREdlr+fWM/dYrUDRupcsstl1QCwxYSSMKx/HYmpKQTHhxAVrb9b183nu5yf+1nJiVTwZZ/71cIDyMzOaVQmcp1r6bxmMEAlK8chK35zZh2O/HLVwNgu/VmUn/fXeL0Ek90d4+OdOvWHoBt23Zhi8gfcRUREUryeefgT4/8Xy+Cg4N4eeTEvH2JScecru9p4hMSiCzQd7VFRpJYTL83skC/JzK33+vN7uh2G506NwXg9x1/EB5eOe9YWHhlUgr8viuo7wPtqVzZnxcH5z+8oEOHW5j6+SIAjhw5Rnx8CjVrhrNjxx+ua4CIi/zduJFygD+OREdAga904M6SKpmm+YFpmjeZpnmTK5IXANs2baZ6rZpUjYrCx9eXdp07smLREpf8LE+zadMmakVHE1W9Or6+vnTu3JlFixYVKrNo8WK6de8OQKNGjTh58iTJSUlO1fVUn035jA4dOtChQwcWLlxIt+6ON7P57Sv6BnTNmjV06OB4ykz37t1ZuGhhmcbsCls2baJWdC2iqkfh6+tLx86dWXreNVy6eBFdc89PgwLnp0KFClSqVAmAChUqcGuL29i9c1eZt+GfmPr5NLp06UGXLj1YvGgZXe/oDEDDhtdz8uQpkpOdX5RuyZLlF1XfXa6vXY0D8cc4lHicc1nZfPfjZlo2vrZQmfTTGZzLXdtlxuJfualuNP4VHWtCpKQ61n84mpzKwp+30em2BmXbgIuUk7gXS+VIjMAwsFjxuboZ2ft/LVzm5DGsUdcDYFQIwhJcFTPNuzuxf0rf8TsVoqLwi4zE8PEhvHUrUn78qVAZ3yr5U2oCrr0WDAvZaWn4Vg7C6u8PgKVcOYJvupEzBw+Wafyu1rLxtXyzfAOmabJx5x8EVPQjvEqgU68bT3e5v/ZPbNuJf/VqVKxqw/DxIapdLPErVhcqs7BzHxZ2upeFne7lyOKVbBzzdl7yAiCqvfdNH5k+7Tt69niSnj2eZNmytXTq3BKA66+vw6lTpzl27ESROnfc0ZZmzW5k4IBxhUYgrFj+s1P1PdHmYvqui8/r9ywu0O9tWKDf681mz1rFQw+M46EHxrFq1Wbatb8ZgLr1anH6VCYpKUWnwnXs1JSbb76Wl4Z/Wuj6Jyae4Mab6gAQHBxA9RrhHD3qHQkskfP95QgM0zRXACsMw/jENE2P6unY7XZeGfoS70yZjMVqZc70GezbvZvuvR2f0M+c+iUhYaF8PucbKvn7Y5o53PPgA9zZpj2nT51i9NtvcmOTW6gcHMz3a37kvTfH8+30GW5ulXPsdjtDhw5lypQpWK1Wpk+fzu7du+nduzcAU6dOZdnSpcTFxbFi5UoyMjJ4rn//v6zrbZYtXZbbvhW57Xsu79jkTybzwvMvkJSUxNgxY5kwcQLP9n+Wbdu2MX3adADCwsKYM3cO/v7+mDkmDz74IG1at+HUKc9f4M9utzNi6FA+yr2GM6dPZ8/u3fTMvf5fTZ3KiqXLiImLY1Hu+RmUe35CQkN554MPALD6WJn37besWrHCbW35p5YvX0VMbHOWLJ1HRkYmA14Ymnfsw48mMnjQSyQlJXPffffw70f6Ehoawtx5M1ix4kcGD3rpL+t7Mh+rlaEPd+HhEZOx55h0b3UjV9WI4MsFjkeh9Wp3C3sPJ/PC2zOwWAxqR4Uz6vHuefWffHUqqSfP4GO1MuzfXQjyr+CupvwzZg6ZKz6mYpfBYLGQtX0ZOccP43udYzG3rK2LOPfLTPxaP0bFXq+BAWdXT8XMPAmAX7unsVari+EXQKUH3uXcz9PJ2u5Fb2jsdva88RbXv/kahtVCwrz5nNl/gMiujqcJxX8zh7C4WKrecTum3U7O2bPsGPoSAOVCQqgzZBCGxYphMUhesozjq9e4sTEX7pk3vmLd1v2cOHmaFg+P5cmercnOXeOoV7tbiLmxDivW76TNY69Tobwvo59w3PslvW68yeX+2jftOWx6ZQK3vjMWLBYOzvmBk/sOUqt7JwAOzCx53QsAq195wm+5kQ2j3iqDaF3jx1W/0Lz5TcyZ9xGZmWcZPvTNvGMTJg5nxEtvk5x8nEEvPkF8fBKfTnkdgKVLV/PB+1/+ZX1PZ7fbGZbbd7VYrczI7bvek9vv+aJAv3d5br/3+f75j8oe//bbNGnalODgYFavXctbb77J9GnT3NWcf2Ttmu00bVqPL6cNzXuM6p/Gvfp/vDL2S1JS0nm2/90kJp7g3ff7AbByxWY+/eQHPv3kBwYNvpdPPh0ABrz37hzS0k67qzleyTC8bOrdJcxwZn6YYRg3AYOBmhRIepimWf/v6t5Qq/alMwHtAh03s9wdgpt52yzj0lXe3QG4WY6vdw1RLm27v/WOpIgrnFzqXR3D0rb+ywR3h+BWMR8+7e4QxE1m93nX3SG41Qj75f2XPzV1q7tDcKvq1W93dwhutfLHty/pjn/969teku9pN29Z6HXXzdlFPKcCzwFbAD1zR0RERERERETKlLMJjGTTNOe4NBIRERERERERkRI4m8AYZhjGR8AS4OyfO03TnOWSqERERERERERECnA2gfEAcA3gS/4UEhNQAkNEREREREQuWVrE03M4m8BoYJrm9S6NRERERERERESkBBYny601DKOuSyMRERERERERESmBsyMwmgP3G4axH8caGAZgOvMYVRERERERERGRi+VsAqO9S6MQERERERER8UAWw9mJC+JqTiUwTNM8CGAYRjjg59KIRERERERERETO41QqyTCMLoZh7Ab2AyuAA8D3LoxLRERERERERCSPs2NhRgJNgF2maUYDrYCfXBaViIiIiIiIiEgBzq6BkWWaZophGBbDMCymaS4zDOMVl0YmIiIiIiIi4maGYXV3CJLL2QRGqmEY/sBKYKphGElAtuvCEhERERERERHJ5+wUktuBM0A/4AdgL9DZVUGJiIiIiIiIiBT0tyMwDMd4mW9N02wN5ACfujwqEREREREREZEC/jaBYZqm3TCMM4ZhBJmmmVYWQYmIiIiIiIh4Aq2B4TmcXQMjE9hiGMYi4PSfO03TfMolUYmIiIiIiIiIFOBsAuO73C8RERERERERkTLnVALDNM1PDcOoANQwTXOni2MSERERERERESnEqaeQGIbRGdiI4wkkGIbR0DCMOS6MS0REREREREQkj7NTSIYDNwPLAUzT3GgYRrSLYhIRERERERHxCFrE03M4NQIDyC7mCSRmaQcjIiIiIiIiIlIcZ0dgbDUM4x7AahjGVcBTwGrXhSUiIiIiIiIiks/ZERhPAvWAs8AXQBrwtKuCEhEREREREREpyNkRGHVzv3xyv24HugD1XRSXiIiIiIiIiNsZFq2B4SmcTWBMBfoDW4Ec14UjIiIiIiIiIlKUswmMZNM057o0EhERERERERGREjibwBhmGMZHwBIc62AAYJrmLJdEJSJeL8e0uzsEEbc4k+Xsn1aRS8s503B3CCIicolztpf1AHAN4Ev+FBITUAJDRERERERELlkWQ2tgeApnExgNTNO83qWRiIiIiIiIiIiUwNnHqK41DKOuSyMRERERERERESmBsyMwmgP3G4axH8caGAZgmqapx6iKiIiIiIiIiMs5m8Bo79IoRERERERERDyQoTUwPIZTU0hM0zxY3JergxMRERERERERz2IYRhXDMBYZhrE799/gYspUNwxjmWEYOwzD2GYYxtMFjg03DOOIYRgbc786OPNznV0DQ0REREREREQEYACwxDTNq4AludvnywaeNU3zWqAJ8Ph5a2u+aZpmw9yv+c78UCUwRERERERERORC3A58mvv9p0DX8wuYphlvmub63O9PAjuAahfzQ5XAEBEREREREbnMGIbxiGEYvxb4euQCqkeYphkPjkQFEP43P6sW0Aj4ucDuJwzD2GwYxsfFTUEpjrOLeIqIiIiIiIhcdi7VRTxN0/wA+KCk44ZhLAZsxRwafCE/xzAMf2Am8F/TNNNzd78LjATM3H9fBx78u/9LCQwRERERERERKcQ0zdYlHTMMI9EwjEjTNOMNw4gEkkoo54sjeTHVNM1ZBf7vxAJlPgTmOROTppCIiIiIiIiIyIWYA9yf+/39wLfnFzAMwwAmATtM03zjvGORBTbvALY680OVwBARERERERGRCzEWaGMYxm6gTe42hmFUNQzjzyeK3Ar0AVoW87jUcYZhbDEMYzMQB/Rz5odqComIiIiIiIhICQxDb5vPZ5pmCtCqmP1HgQ653/8IGCXU7/NPfq5GYIiIiIiIiIiIx1MCQ0REREREREQ8nhIYIiIiIiIiIuLxNJlHREREREREpAQWw+ruECSXRmCIiIiIiIiIiMdTAkNEREREREREPJ4SGCIiIiIiIiLi8bQGhoiIiIiIiEgJDIvWwPAUGoEhIiIiIiIiIh5PCQwRERERERER8XhKYIiIiIiIiIiIx1MCQ0REREREREQ8nhbxFBERERERESmBYehts6fw6ivRLKYF/Ye+iNVqZfa06Xzy7vuFjte68gqGv/oK19Srxzuvvc5nH07KOzZs3Bhua9mS4ykp3N2uQ1mHftFiYmIYOmwYVquVaV99xbvvvlukzLDhw4mLiyMjI4P+/fuzbetWp+t6g2HDh53Xvm1FykRVj2LihIkEVQ5i29Zt9OvXj6ysLK688kpefe1V6tWrx2uvvcaHH3zohhb8c7fFxDB42FAsViszvprGh8Vcw8HDhxETF0dmRgYD+vdne+75WfLjj5w+fYocew52ezbdO3cp6/BLxdChA4mNvY2MjEyef34w27btKFImKqoa48e/SuXKQWzbtoNnnx1AVlY2gYGBvPLKSGrUqM7Zs2cZMGAIu3btcUMrLtzAiTNZ/uvvhARVYt74/xY5bpomoybNY8X6nfiVL8fYJ7pT78pqAKxcv4tRH88jJyeHu1o35pFuMWUc/cWz1miAX4sHwLCQtX0J5377tnCBchWo0PYpjIAQMKyc2zCX7B3LAfBr9R+stW7AzEjjzBf9yz74UhDatDHXPvsEhsXC4W/ns+/TLwsdr3JDA254fSQZRxMASFy2ij0ffeZUXW/wd/dw2qkMBk2cyR+Jxynv68Pox7txdU0bAJ/O+4kZi37BBO5q3Zi+nW91Qwv+ucv9tW9rdhONnnsMw2Jh3zff8/vkacWWq1L3alpNeZs1A0ZxePEqADp99xlZpzMwc3Iw7XYW9X68LEMvNc+/8H/c2vwmMjPPMmzIm/z++94iZUaN7k/deleRnZ3N1q27GDVyItnZdqfre6oWMTEMGzYMS27f9b0S+r2xuf2egv3eV159lZYtW5KSkkL7tm3LOvRS89TT3WnStC5nM88xZvRUdu06XKTMkKH3Ueea6mRn29mx4w9eG/cVdnsO/gEVGDDwHqpVDeXcuWzGjvmC/fvj3dAKkYvntVNILBYLL4wYzpN9H6J7m/a079KJ6Nq1C5VJS01l3PARfPbhR0Xqz/16Fk/c/2AZRVu6LBYLI0aOpO/999OmdWu6dOlC7auuKlQmNi6O6OhoYmNiGDRwIKNeftnput4gNi42t32xDBo4iFEvjyq23IABA5g0aRJxsXGkpaXRo0cPAFJTUxk+bDgffuhdiQtwXMOhI0fw8P196di6DZ26dOHKqwrf+y3iYqkVHU3bmFiGDBzE8PPOz/09e9G1QwevTV7Ext5GrVo1aNmyA4MHD2fEiCHFlnv++X5MnvwZrVp1JC0tnbvu6g7AY4/9m+3bf6djx2707z+IIUMGlGX4F6Vb3A18NKRvicdXrt/FgfgUFr7zLCMf7crwDxxv8O32HEZ8OIePXuzLd+P/y7xVm9hzKLGMoi4lhoFf7EOcmTOa01P74XP1rViCqxUqUq5+e+zHD3Pmy+fJmDUcv+b3Qe6jz7J2LCdjzmh3RF46LBbqPf80vz49gFV3P0Bk25b4R9csUuzEhi381PsRfur9SF7ywtm6nsyZe/i9mcu5NjqSuW8+xStP3cmoj+cBsOtgAjMW/cKMcY/x7RtPsvy33zlw9Jg7mvGPXc6vfcNi4cYBT7LyiUH80P1haraPI/CKGsWWq//0wySs+a3IsWWP9Gdhz0e9NnnRvPlN1KhRlds7/5uXR0xg0IvFt+P7+cu54/b/467uj+NXvjx33NHugup7ooJ917Z/0e+tFR1NXEwMAwcO5OXcfi/AzBkz6Hv//WUddqlq0qQuUdXDuKfnSF59dRrP9L+72HKLFv7KvfeMou99Yylf3pdOnZsB0KdPW/bsPsIDfV9h1Muf8dTT3coyfJFS5bUJjOsaNuDwwYMcOXSI7KwsFsz9jti2rQuVOZFynO2bt5CdnV2k/vp1v5CWllpG0Zauhg0bcvDAAQ4dOkRWVhZz586lbZs2hcq0bdOGWTNnArBhwwYCAgMJCw93qq43aNumLbNmzgL+bF8AYeFhRco1a9aM+fPnAzBz5kza5mbeU1JS2Lx5M9lZRe8NT1e/YUMOHjjI4dxr+N3cubRqU/gThVZt2vJN7vnZtGEDgSWcH2/VunUcs2fPAWDjxs2O9oWFFinXtOktfP/9QgBmzfqWNm1aAlC79pWsXr0WgH379lOtWjVCQkLKKPqL07heNEEBFUs8vmTddrrGNsIwDBrWqUH66UySjqezec9hakaGUN1WhXK+PnRsXp8l64qOWvFkloja5KQmYKYnQY6d7F2r8bmiceFCponh6+f4vpwfZuYpyMkBwH50h2PbS1Wudw2nDx0h40g8ZnY28YuWEh7TzOV1PYUz9/DeQ0k0qX8lAFdGhXMkKZVjqSfZeySZBlfXoEL5cvhYrTSuG82in7e7oxn/2OX82q9yXR1OHjrK6SMJ5GRn88eC5VSLLXr/XtXzdg4v+ZGzx1PLPkgXi4lrwry5SwHYsmUnAQGVCA0NLlLuxx9/zft+69ZdhEeEXlB9T9SgmL5rm/P6rm0K9Hs3bthAYG6/F2DdunWkpqaWddilqvlt17Pgh3UAbN92AH//CoSEBBYpt3Zt/u+1HdsPEhYeBECtWjZ++20XAH/8kYQtMoTg4IAyiFyk9DmVwDAMY4kz+8pSWEQECUfzhz4lxScQHhHhxojKToTNxtH4/LbHx8cTYbMVLXP0aN52QkICtogIp+p6gwhbRDHtK9yO4OBg0tPTsdsdQycdbfX+eyTCFkFCfH7bE4tpV4QtgoTzzk9E3vkxmfT5Z8ycN5e7e/Uqi5BLXUREBEdzh8gDJCQkYjvvHAQHV+bkyZN5199RxtGZ2bFjJ+3aORKe9etfR7VqkURGev+9AZB4PB1baFDeti0kkMTj6SSmpGELyd8fERJE4vF0d4T4j1kqVSHnVEreds6pFAz/KoXKnNv8A5Yq1aj04PtU6vU6masmA2YZR+oafmGhZCYm5W1nJh7DL6xoYrLy9XW5deqH3DR+DP5X1Lqgup7MmXv4mlo2Fq11TJfbvPsQR5NTSUhJ5+oaEfy6fT8nTp4h4+w5Vq7fScKx1LIM3+Uu5dd+hfBQMhKT87bPJB6jwnlJ6wphIVRr2Zy9X88rUt80TWL/N5Y2U9/him7eN20YIDw8hIQC5yAx8Rjh4SUn3n18rHTsFMfqn377R/U9ic1mI75A3zUhPh5bMf3e+AL9nvjcfu+lIjQ0iKSk1Lzt5KRUQgu83s9ntVpo164x69Y6kpV79hyhRYsGAFx7bQ0iIoIJC6/sypAvOYZhvSS/vNFfroFhGIYfUBEINQwjGDByDwUCVV0c218yDKPIPtO8NDqpf6doy4u2vaTz40xdb+DM9b9U7xGjmKt4IW3v1a07SUlJVAkJYfLnn7Nv715+XbfONcG6yMVe//ff/4ghQwYwd+7X7Ny5m+3bf8+bI+ztirvFDcMo9i18cb8PPFox1/T8BvvUaEBO8kEyZo/ACIqg4u1DOH3kOcjKKKMgXciJ+z59526Wd+mFPSOTsGa3cMOrI1jZ/T6n6no6Z+7hR7rFMGrSPG5/ZgJX14zg2uhIfCwWrowK5+E7Ynhw+MdUrFCOOrUisVq9s+NWkkv6tV9876XQVqPnHmPz+I8wc0dcFbTkgX5kJqdQPrgyse+N5eSBQySv3+KiWF2j+L/9JZcfOOgx1v+2lQ0btv2j+p7kYvq9l4pi2/cX5Z959m42bdrL5s37AJj6+WKeerobkyY/z7698ezefTjvAx4Rb/N3i3j+H/BfHMmK38j/HZIOvFNSJcMwHgEeAaheJYzQgKJDnC5WUkICtqqRedvhkTaSk5L+osalIyEhgaqR+W2PjIwkKbHwfNaE+HiqVs3PMdlsNhKTkihXrtzf1vVUfe7rQ6+ejhEDmzZvKqZ9hdtx/PhxAgMDsVqt2O323LZ6/z2SkJCALTK/7RHFtCshPgHbeecnKff8JOW+To6npLBowQLqN2zgFQmMe+/tSY8edwKwZctWqla18VvuNGebLYLE887B8eMnCAgIyLv+jjKOT59OnTrNCy/kr5uxYsUCDh8uuhiWN7KFBJJwLC1vOyElnfDgALKy7SSk5O9PTEkjvErp/252pZxTKfj6539iaPEPwTx9olAZ37pxnPvtGwDMtERy0pOwVKlKTqL3LFZXksykZPwiwvO2/SJCOXus8DoO2afP5H2fvPpn6r7wNL5BgU7V9XS2kKC/vYf9K/ox5knH7wnTNGn16KtERTiGyd/V+ibuan0TAG98voCIkJI/vfRGl/JrPyMpmQoR+SOGKkaEkpGcUqhMcN2raDp2EADlKgcR2bwxZradI8tXk5lb9uyJVA4v/Ykq9ep4RQLj7h4d6datPQDbtu3CVuAcRESEknzeOfjTI//Xi+DgIF4eOTFvX2LSMafre5r4hAQiC/RdbZGRJBbT740s0O+JzO33erM7ut1Gp85NAfh9xx+EFxgxERZemZQCr/eC+j7QnsqV/XlxcP7DC86cyWTsmC/ytqfNGEb80eOuCVzExf5yColpmuNN04wG+pumeYVpmtG5Xw1M05z4F/U+ME3zJtM0b3JF8gJg26bNVK9Vk6pRUfj4+tKuc0dWLHLrrJYys2nTJmpFRxNVvTq+vr507tyZRYsWFSqzaPFiunV3LFjYqFEjTp48SXJSklN1PdVnUz6jQ4cOdOjQgYULF9Ktu2MBovz2JReps2bNGjp0cAwX7d69OwsXLSzTmF1hy6ZN1IquRVT1KHx9fenYuTNLz7uGSxcvomvu+WlQ4PxUqFCBSpUqAVChQgVubXEbu3fuKvM2/BOff/4VnTvfSefOd7Jw4VLuuMOxAGnDhvU5efIUyclF34ytXbuOf/3LsT5It263s3ixY/5vQEAAvr6O/G2PHt355ZffOHXqdBm1xLVaNr6Wb5ZvwDRNNu78g4CKfoRXCeT62tU4EH+MQ4nHOZeVzXc/bqZl42vdHe4FyUnci6VyJEZgGFis+FzdjOz9vxYuc/IY1qjrATAqBGEJroqZ5t2d2D+lbf+dSjWqUaGqDcPHh8g2LUlauaZQmXIh+XPag+peg2ExyEpLd6qup3PmHk4/ncG53LWNZiz+lZvqRuNf0bEmSkqqY/2To8mpLPx5G51ua1C2DXCxS/m1f3zbTgJqVKNSVRsWHx9qtIvlyPLC9+93ne5jXsc+zOvYh8OLV/HbmAkcWb4aq58fPhUrAGD188PW9EbS9h5wQysu3PRp39Gzx5P07PEky5atpVNnxzpO119fh1OnTnPs2Ikide64oy3Nmt3IwAHjCo1AWLH8Z6fqe6LNxfRdF5/X71lcoN/bsEC/15vNnrWKhx4Yx0MPjGPVqs20a38zAHXr1eL0qUxSUopOBevYqSk333wtLw3/tND19/evgI+PY9RZp85N2bRpL2fOZJZNQ0RKmbOPUf2fYRhdgFoF65im+YYrgnKG3W7nlaEv8c6UyVisVuZMn8G+3bvp3tvxCf3MqV8SEhbK53O+oZK/P6aZwz0PPsCdbdpz+tQpRr/9Jjc2uYXKwcF8v+ZH3ntzPN9On+Gu5lwQu93O0KFDmTJlClarlenTp7N792569+4NwNSpU1m2dClxcXGsWLmSjIwMnuvf/y/reptlS5fltm9Fbvueyzs2+ZPJvPD8CyQlJTF2zFgmTJzAs/2fZdu2bUyfNh2AsLAw5sydg7+/P2aOyYMPPkib1m04dcrzF/iz2+2MGDqUj3Kv4czp09mzezc9c6//V1OnsmLpMmLi4liUe34G5Z6fkNBQ3vngAwCsPlbmffstq1ascFtb/qnly1cSG3sbS5d+T2ZmRqHRFJMm/Y+BA4eRlJTMuHFvMn78qzzzzJNs27aDGTMcC5vWrn0Fr702Grvdzp49+xgwYKi7mnLBnnnjK9Zt3c+Jk6dp8fBYnuzZmuzcYaC92t1CzI11WLF+J20ee50K5X0Z/YSjQ+djtTL04S48PGIy9hyT7q1u5KoaXjY/2Mwhc8XHVOwyGCwWsrYvI+f4YXyvcyzmlrV1Eed+mYlf68eo2Os1MODs6qmYmScB8Gv3NNZqdTH8Aqj0wLuc+3k6WduXubNFF8S057B93AQav/0KhtXK4Tnfc2rfAap36wzAoVlzsbWMocadXTCz7eScPcvGwS//ZV1vUtI9/OWCnwHH/b/3cDIvvD0Di8WgdlQ4ox7vnlf/yVenknryDD5WK8P+3YUg/wruaso/cjm/9k17DutfmUjM/8Y4HqP67QLS9x3kyjs7ARS77sWf/EIq0/yN4QAYVisHv19GwupfSyzvqX5c9QvNm9/EnHkfkZl5luFD38w7NmHicEa89DbJyccZ9OITxMcn8emU1wFYunQ1H7z/5V/W93R2u51huX1Xi9XKjNy+6z25/Z4vCvR7l+f2e5/vn/+o7PFvv02Tpk0JDg5m9dq1vPXmm0yfVvxjeD3V2jXbadq0Hl9OG5r3GNU/jXv1/3hl7JekpKTzbP+7SUw8wbvv9wNg5YrNfPrJD9SsGcHgF+/FnmNy8EACY8d+UdKPkhIYhrNvm8XVDGfmhxmGMR/IBLYAeZMLTdN86e/q3lCr9qUzAe0CHTez3B2Cm3nfLNvSVN7dAbhZto+/u0Nwq71z/vbX4yXr5FLv6hiWth+neNfUjNL2r0+85/GMUrqm3fueu0Nwq7E55dwdglulpm51dwhuVb367e4Owa1W/vj2Jd3xj23x3CX5nnb5yle97ro5m0qKMk2zvksjEREREREREREpgVOPUQW+NwyjrUsjEREREREREREpgbMjMNYCsw3DsABZOOYGmKZpetcy1iIiIiIiIiIXwGJcWo/e9mbOJjBeB5oCW8xL6aHKIiIiIiIiIuIVnJ1CshvYquSFiIiIiIiIiLiDsyMw4oHlhmF8D5z9c6c7H6MqIiIiIiIiIpcPZxMY+3O/yuV+iYiIiIiIiIiUGacSGKZpvuTqQEREREREREQ8jWFx9nN/cTWnroRhGGHA80A9wO/P/aZptnRRXCIiIiIiIiIieZxdxHMq8DsQDbwEHAB+cVFMIiIiIiIiIiKFOJvACDFNcxKQZZrmCtM0HwSauDAuEREREREREZE8zk7mycr9N94wjI7AUSDKNSGJiIiIiIiIeAbD0BoYnsLZK/GyYRhBwLPABCAQ+K+rghIRERERERERKcjZBMYJ0zTTgDQgDsAwjFtdFpWIiIiIiIiISAHOroExwcl9IiIiIiIiIiKl7i9HYBiG0RRoBoQZhvFMgUOBgNWVgYmIiIiIiIi4m2Hora+n+LspJOUA/9xyAQX2pwN3uiooEREREREREZGC/jKBYZrmCmCFYRifmKZ5sIxiEhEREREREREpxNlFPM8YhvEqUA/w+3OnaZotXRKViIiIiIiIiEgBziYwpgLTgE7Ao8D9QLKrghIRERERERHxBIbh7NtmcTVnn0ISYprmJCDLNM0Vpmk+CDRxYVwiIiIiIiIiInmcTSVl5f4bbxhGR+AoEOWakERERERERERECnM2gfGyYRhBwLPABByPUf2vq4ISERERERERESnI2SkkdwGGaZpbTdOMA9oAd7guLBERERERERGRfM6OwKhvmmbqnxumaR43DKORa0ISERERERER8QyGRYt4egpnR2BYDMMI/nPDMIwqOJ/8EBERERERERG5KM4mIV4HVhuG8TVgAncDo1wWlYiIiIiIiIhIAU4lMEzTnGIYxq9AS8AAupmmud2ZumdN+0WEJ97N2QE+l6byhrsjcC/Dp5K7Q3CrTf1edXcIbrPvmL+7Q3Crq2yn3R2CW83u8667Q3Crc+bl+8u/x+ePujsEtxpx13h3h+BWHQIu7wcUbnF3ACKXCaengeQmLJxKWoiIiIiIiIhcCgxDqyd4isv7I3IRERERERER8QpKYIiIiIiIiIiIx1MCQ0REREREREQ8nibziIiIiIiIiJREa2B4DI3AEBERERERERGPpwSGiIiIiIiIiHg8JTBERERERERExONpMo+IiIiIiIhICQyL3jZ7Co3AEBERERERERGPpwSGiIiIiIiIiHg8JTBERERERERExOMpgSEiIiIiIiIiHk+rkYiIiIiIiIiUwDD0ttlTaASGiIiIiIiIiHg8JTBERERERERExOMpgSEiIiIiIiIiHk+TeURERERERERKYtHbZk+hERgiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PE3mERERERERESmJYXV3BJJLIzBERERERERExOMpgSEiIiIiIiIiHk8JDBERERERERHxeFoDQ0RERERERKQEhkVvmz2FRmCIiIiIiIiIiMfz6lRS85gWDBg2DKvVwsyvpvHRu+8VKTNw+DBaxMWSkZHJ4P792bF1G7WuuILXJ07IKxNVozoT33iTzz6eXIbRX7xhw4cTFxdHRkYG/fv3Z9vWrUXKRFWvzsQJEwiqXJltW7fSr18/srKynK7vyYYNH0pcnOPa9u//HNu2bitSJqp6FBMnvF2g/c+SlZXF7V1v59FH/w+AM2dO8+LgIezY8XvZNuAi3BrTgheGDsVitTBr2nQ+Lubef2HYUG6LiyUzI5Mh/Z9jxzbH+en9QF+69+wBhsGsr6bxuZfd938aPPgZWsQ0IzMzk4EDRrJ9+84iZXr3vpP77u9JzZrVadKkLakn0godv+76a5k2bRLP9HuRBQuWllXoFyXgpiZU/U8/DIuF4z/MIWnaZ4WOV6p/A9EvjeNcwlEA0n5cTuLUjwEI7daTkPZdMDHJ3L+XQ6+9jJl1rszbcDHCmzWmfv/HMKwWDs7+nl2ffFVsucp16xD76dusG/AyR5eswr9mFI3Hvph3vFK1SHa89yl7v5hVVqGXCv8bmxD5f8+AxcKJBXM4NmNKkTKVrr8B2yP9MHx8sKensv+F/zhd19Ndztff1uwmGj33GIbFwr5vvuf3ydOKLVel7tW0mvI2awaM4vDiVQB0+u4zsk5nYObkYNrtLOr9eFmGXioGTpzJ8l9/JySoEvPG/7fIcdM0GTVpHivW78SvfDnGPtGdeldWA2Dl+l2M+ngeOTk53NW6MY90iynj6EvHwEFP0aJFEzIyzjJ40Bh27NhVpMw993Sjz313UqNGFLc260xqav7fvcaNGzJg4JP4+Phw4kQafe9/qizDvyh1b72FOwf8F4vVwk8z57Jo0ueFjjfu2JY2D/UG4OyZDL4a+RpHdu4BIPbeu7i1excMw+Cnr+ew7PPpZR5/aXjq6e40aVqXs5nnGDN6Krt2HS5SZsjQ+6hzTXWys+3s2PEHr437Crs9B/+ACgwYeA/VqoZy7lw2Y8d8wf798W5ohcjF89oRGBaLhcEjR/Do/X3p0rotHbp04cqrahcqc1tcLDWja/GvmDiGDxzI0JdfBuDAvn1079CR7h06clenzmRmZLJ4wUI3tOKfi42LIzo6mtiYGAYNHMio3Ladb8CAAUyaNIm42FjS0tLo0aPHBdX3VLFxsURH1yI2piWDBg5i1Msjiy03YMALTJr0MXGxLUlLS6dHj7sBOHToED3u7sm/2ndgwtsTGTNmdBlGf3EsFguDRrzEf/o+QNc27fhXl85cUbvwvd881nHvd4ptyYhBg3hxlOP81L76arr37ME9t9/BXf/qSIuWLalRq5YbWnFxWrRoRs1a1WnX9k6GDhnLsOHPF1tu/frNPPjAkxw5fLTIMYvFQv/+T/Djjz+7OtzSY7FQ7Yn+7B/cj53/7kXl2LaUr1GrSLHTWzay6z/3ses/9+UlL3xCwgjteje7nniAXY/0xrBYqBzbpowbcJEsFhq88CSrnxzE4u4PEdU+joDoGsWWu+7ph0lc82verlMHD7Os16OOr96PYc88y9FlP5Zh8KXAYqHqY89xYOh/2fNoT4Ji2lK+enThIpX8iXz8ef4Y0Z89/+nFH6MHOV3X413G19+wWLhxwJOsfGIQP3R/mJrt4wi8omjbDYuF+k8/TMKa34ocW/ZIfxb2fNQrkxcA3eJu4KMhfUs8vnL9Lg7Ep7DwnWcZ+WhXhn/wLQB2ew4jPpzDRy/25bvx/2Xeqk3sOZRYRlGXnttaNKFmzSj+1f4ehg97laHDnim23PoNW3jowWc4cqTwm9OAAH+GDH2GJx4fyO1d7ueZfkPLIuxSYVgs3P3is7zzn2cZ2aU3N3Voje2KWoXKHDtylDf7PsHobvfz/XufcM8wR78gsnY0t3bvwrheDzO6+/1cF9OMsBpRbmjFxWnSpC5R1cO4p+dIXn11Gs/0v7vYcosW/sq994yi731jKV/el06dmwHQp09b9uw+wgN9X2HUy5/x1NPdyjJ8kVLltQmM6xs24NCBgxw+dIisrCzmz51LXJvCnfGWbdowZ6bj05XNGzYSEBhIaHhYoTJNbr2VQ38cJP7IkTKLvTS0bdOGWTNnArBhwwYCAgMJCw8vUq5Zs2bMnz8fgJkzZ9K2bdsLqu+p2rZpzayZswHYkHttw867tgDNmjVl/vzvgT/b77hH1v+2nvT0dMf36zdgi7SVUeQX77qGDfjj4EGOHDpEdlYWP8ydR1zbwvd+XNvWzJ3lOD+bN2wkICCQ0LAwomtfyeYNG8nMzMRut/Przz/Tql1bdzTjorRq1YJvv3Fc102bthIYGEBYWEiRcjt27CrSifvTvX3uZuGCZRxPOe7SWEtTxTp1OXf0MOcSjmJmZ5O6YhFBzVo4Xd+wWrGULw8WK5byfmQdT3ZhtKWvynV1OH34KGeOxGNmZ3N4wXIiY28tUu7Knl05smQVZ4+nFvv/hN/ciNOHj5IRn+TiiEtXhavrcvboYbJyr3/aykUENC18/SvHtiN99TKykh1v0OxpJ5yu6+ku5+tf5bo6nDx0lNNHEsjJzuaPBcupFtusSLmret7O4SU/lth2b9a4XjRBARVLPL5k3Xa6xjbCMAwa1qlB+ulMko6ns3nPYWpGhlDdVoVyvj50bF6fJet2lGHkpaNly+bM+XYBAJs3bycgwJ/Q0KJ/937fsZujRxOK7O/YsTWLF60kPve+P+5F90it668l+Y/DpBw+ij07m9++X0L9lrcVKrN/41Yy0k86vt+8jcoRjj6t7Ypa7N+8jazMs+TY7ez+dSMNWnnX7z6A5rddz4If1gGwfdsB/P0rEBISWKTc2rXb877fsf0gYeFBANSqZeO33xwjdv74IwlbZAjBwQFlELlI6XMqgWEYxl3O7CtLETYb8fH5b0wS4xOIsBV+ExpuiyDhaIEyCfFERBQu868unZg/Z65rg3WBCJuNo0fzP1VOSEjAFhFRqExwcDDp6enY7XYA4uPj886RM/U9mSP+/GvriL/wtS3a/gQibEXb2KPn3SxfvsK1AZeiiAgbiQXv6/h4ws+7duERtvPu/QTCbTb27NzFDTffTFDlyvj5+XFbXCwRkZFlFXqpiYgIIz4h/xO0hIQkIiKKJrBKEh4eRpvWMXz1lfcMHwfwDQ3jXHL+m66s5CR8Q4q2u2Ld67n63c+IHvUm5Ws6PmXPTkkmecZUrv38G+p9NQ/7mdOc+m1dmcVeGvzCQslIyG9/RlIyfuEh55UJoWrcrez/el6J/09UuzgOL1jmsjhdxTcknKxj+fd99rGi179ctRpY/QOJHvs/rhz/KZVb/svpup7ucr7+FcJDyUjMTzieSTxGhbDQwmXCQqjWsjl7i2m7aZrE/m8sbaa+wxXdOrg8XndIPJ6OLTQob9sWEkji8XQSU9KwheTvjwgJIvF4ujtCvCjh4aEkFLj/ExOTiYgI/YsahdWqVZ3AwAAmfzKe6TM+pEuXdq4I0yUqh4dxokDbUxOTqFzMh1Z/atatE9t+XAvA0T37qH1jAyoFBeLrV556tzUluJi+oKcLDQ0iKSk1bzs5KZXQAvf7+axWC+3aNWbdWkeybs+eI7Ro0QCAa6+tQUREMGHhlV0Z8qXH8Lk0v7yQs1EPBGY4sQ8AwzAeAR4BiKwSQrC/KzJ8RpE9pmmeH8dflvH19SWudWveeuXV0g/Pxf6ubX9Xxpn6nuyft7/wdtOmTejR427u7F78UDyPVLRZTl/7/Xv3Mvm99/ng8ymcOX2GnTt+z0vweBUnru1fGTS4H6+99g45OTmlGFRZKO7iF97M2PM7O+7tSk5mBgGNmxI9fBy/P3AXVv8AApu1YMd93bCfOkmtIaOp3Ko9qUt+KJvQS0Mx1/389tfv/xhb3/4ISri2ho8PthZN2TbhIxcE6GLFNP/8G9+wWqlQ+xr2D3wcS/nyXPH6JM7s3OpUXY93WV//Yi9goa1Gzz3G5vEfYRbT9iUP9CMzOYXywZWJfW8sJw8cInn9FhfF6h7F3c6GYZx/izj2uzya0nex/Tar1Urdelfz0IP9KF++PF98+S6bNm3j4MGi6yh4nAto+1WNb6BZt0680cex9k/ivoMs+ngqT3z4FufOZHBk1x5yvLDfU+z1/4vyzzx7N5s27WXz5n0ATP18MU893Y1Jk59n3954du8+7J39PxH+JoFhGMa/gA5ANcMw3i5wKBDILqmeaZofAB8A1KsZ7ZIeUmJCPJEFPjmOiLSRlFh4TmNifAK2qgXK2CJJSsov0zw2lu1bt5Fy7JgrQix1fe67j149ewKwafNmqlatmnfMZrORmFR4OOzx48cJDAzEarVit9uJjIzMO0cJ8fF/W9/T9LmvD716OtbwcLQ//9o64i98/Yu2v/A9cs011zD2lTH0vf9BUlNTy6QNpSExIYGIgvd1ZCTJ5127xIT48+59G8m5bZ89fTqzpzsWsHrquf4kxhcdauqJ7rnnTu66+3YAtmzZTmSBT1BstnCSkpyfDnHdddfyxhuOdUEqB1emRUwzsrOzWbJkZekGXcqyjiVRLix/qpdvWHiRaSA5Z87kfX/ylzUYVh+sgUH4N7iRcwlHsaelAo7FPSvVvd6rEhiZSclUsOW3v0J4GJnJKYXKVK57NY3HDAagfOUgbM1vxrTbiV++GgDbrTeT+vturxxin3UsCd/Q/PveJzScrOPHipSxp6dins3EfjaTM1s34Bd9lVN1Pd3lfP0zkpKpUGCUWcWIUDLOa3tw3atoOtax5km5ykFENm+MmW3nyPLVeefp7IlUDi/9iSr16lxyCQxbSCAJx/IXrExISSc8OICsbDsJKfn7E1PSCK9SdOi9J+rV6w7uvKsTAFu3/I6twP0fERFGUlJKSVWLSExM5kRqGhkZmWRkZPLrr5uoc01tr0hgpCYmEVyg7ZUjwklLLvr7q+rVV9J7xAD+9+iznE7LH2WzZtY81sxyjEzq8vT/FRrN4cnu6HYbnTo3BeD3HX8QXmDERFh4ZVIK3O8F9X2gPZUr+/Pi4El5+86cyWTsmC/ytqfNGEb8Ue+ZQitS0N9NITkK/ApkAr8V+JoDuHXs2dZNm6kRXYtq1aPw9fWlQ+fOLFu0uFCZZYsX06W7Y5Ga+o0acurkSY4VeJPToUtn5s+ZU6ZxX4zPpkyhQ4cOdOjQgYULF9Kte3cAGjVqxMmTJ4u8iQVYs2YNHTo4hot2796dhYsWAbBo8WKn6nuSz6Z8RocOnejQoRMLFy6iW/c7AGjUqGFu/EXfwK5Zs5YOHRxDqB3td9wjVatW5b33/0e/fs+yf//+smtEKdi2aTM1a9WiWlQUPr6+tO/cieXn3fvLFy2hczfH+amfe36OJTvOT5UQx5BrW9WqtGrfzmteA1988TV3dO3DHV37sGTxSm7v6riuDRpcx8mTp0hOdr4j17rVHbTK/Vq4YCkjXnrV45MXAGd27qBcteqUs0Vi+PhQOaYNaWtWFSrjE1wl7/sKdeqCxcCenkZWciKVrrkOo3x5APwb3cTZPw6UZfgX7cS2nfhXr0bFqjYMHx+i2sUSv2J1oTILO/dhYad7WdjpXo4sXsnGMW/nvXkFiGrvfdMH/pSxawflq1bHN8Jx/YNatOHk2sL37cm1K6lYryFYrBjly1OhTj3OHjrgVF1Pdzlf/+PbdhJQoxqVqtqw+PhQo10sR5avKVTmu073Ma9jH+Z17MPhxav4bcwEjixfjdXPD5+KFQCw+vlha3ojaXsPuKEVrtWy8bV8s3wDpmmycecfBFT0I7xKINfXrsaB+GMcSjzOuaxsvvtxMy0bX+vucJ3y5Zez6d7tIbp3e4glS1bR5XZH17t+/bqcOnmaY8ec/7u3dOmP3HhjfaxWK35+5alf/1r27T3oqtBL1cGtvxNeI4qQapFYfXy48V+t2HLeIrzBtggeeWs0nw4cQdLBQ4WO+VepnFemQasYfv2+cJ/JU82etYqHHhjHQw+MY9WqzbRrfzMAdevV4vSpTFJSik6F6tipKTfffC0vDf+00CgVf/8K+PhYAejUuSmbNu3lzJnMsmmISCn7yxEYpmluAjYZhvGFaZpZZRSTU+x2O6OGDuODKVOwWC3Mnj6Dvbt3c3fvewCYPvULVi5dRou4OL5fuZzMjAxe7J//pAI/Pz+a3daclwYNdlcTLsqypUuJi4tjxcqVZGRk8Fz//nnHJn/yCS88/zxJSUmMHTOGCRMn8mz//mzbto3p06b9bX1vsGzpMuLiYlmxchkZGZk8V+DaTv7kY154fkBu+19hwsS3ebb/M2zbtp3p03JHHjz9JMHBwbw8cgQA2XY7XTrf7oaWXDi73c7oocN5d8qnWK0Wvsm99+/KvfdnTP2CVcuWcVtcLN+tWOZ4jOpz+efnjXf/R1BwZbKzsxk9ZBgn071vLvCKFT/RIqYZCxfNJDMjk0GD8p9C8/4HbzLkxVEkJR2jT5+7eejhPoSGVmHOnKmsWLGaIS96zxNnisixc2Tia1wxejxYLBxfMI+zB/cT0tGRrEr5bjZBt7UktFM3TLudnHNnOTh6CABnft9G6qqlXP2/TzHtdjL27CJl/jdubMyFM+05bHplAre+MxYsFg7O+YGT+w5Sq7vjE8oDM0te9wDA6lee8FtuZMOot8ogWhfIsXP03deo9fLbGBYLJxbO5ewf+wnu4Lj+J+bP5uyhA5z6bS21/zcVcnI4sWAOZw86hhAXV9ebXM7X37TnsP6VicT8b4zjMarfLiB930GuvNPR9uLWvfiTX0hlmr8xHHBMMTr4/TISVv9aYnlP9cwbX7Fu635OnDxNi4fH8mTP1mTnDoHv1e4WYm6sw4r1O2nz2OtUKO/L6CccH9L4WK0MfbgLD4+YjD3HpHurG7mqhvetgbBy5VpatGjK9z98SWbmWV4cPCbv2LvvjWPokFdITk6h973defDBXoSGVmH2N5NZuXItw4aOY9++g/z448/M/mYyOTk5zPz6O/bs8Y7fATl2O9NHv8nj77+BxWplzex5xO/dT/O7uwLw4/Rv+Nd/HqBSUCA9X3T0Z+12O+N6PATAv98cTaXKgdizs5k+6vW8xT69ydo122natB5fThua9xjVP4179f94ZeyXpKSk82z/u0lMPMG77/cDYOWKzXz6yQ/UrBnB4BfvxZ5jcvBAAmPHflHSj5ISmBbvXC/iUmQ4M3/OMIxOwEigJo6khwGYpmn+7Rg8V00h8Qan8bb59aXN6u4A3CrQGyfZlqJz5b1rgcDSNq3m5XsD7Dvm7+4Q3Ooqm/d1jkvT7oTLe2X7c+bl+9rv8fmj7g7BrerdNd7dIbhVrOXyXlNhS+Ub3R2CW6388e1L+pdfh+6zLsn3tPNndvO66+ZsKuktoBuwxfSmlR5FRERERERE5JLg1GNUgUPAViUvRERERERERMQdnB2B8Tww3zCMFcDZP3eapvmGS6ISERERERER8QSWy3tqvCdxNoExCjgF+AHlXBeOiIiIiIiIiEhRziYwqpim2dalkYiIiIiIiIiIlMDZNTAWG4ahBIaIiIiIiIiIuIWzIzAeB543DOMskMUFPEZVRERERERExGtpDQyP4VQCwzTNy/uh7iIiIiIiIiLiVs6OwMAwjGDgKhwLeQJgmuZKVwQlIiIiIiIiIlKQUwkMwzAeBp4GooCNQBNgDdDSZZGJiIiIiIiIiORydhHPp4HGwEHTNOOARkCyy6ISERERERERESnA2SkkmaZpZhqGgWEY5U3T/N0wjDoujUxERERERETEzUwt4ukxnE1gHDYMozLwDbDIMIwTwFFXBSUiIiIiIiIiUpCzTyG5I/fb4YZhLAOCgO9dFpWIiIiIiIiISAFOrYFhGMZnf35vmuYK0zTnAB+7LCoRERERERERkQKcnUJSr+CGYRhW4MbSD0dERERERETEc2gNDM/xlyMwDMMYaBjGSaC+YRjpuV8ngSTg2zKJUEREREREREQue3+ZwDBNc4xpmgHAq6ZpBuZ+BZimGWKa5sAyilFERERERERELnNOrYEBzDMMoxKAYRj3GobxhmEYNV0Yl4iIiIiIiIhIHmfXwHgXaGAYRgPgeWASMAWIcVVgIiIiIiIiIm6nNTA8hrMjMLJN0zSB24HxpmmOBwJcF5aIiIiIiIiISD5nR2CcNAxjIHAv0CL3KSS+rgtLRERERERERCSfsyMwegBngYdM00wAqgGvuiwqEREREREREZECnBqBkZu0eKPA9h841sAQERERERERuWSZFmc/9xdXcyqBYRjGScDM3SyHY/rIKdM0g1wVmIiIiIiIiIjIn5wdgVFowU7DMLoCN7siIBERERERERGR8/2jsTCmaX4DtCzdUEREREREREREiufsFJJuBTYtwE3kTyn5S+WNy/eZuafNHHeH8P/t3Xd8FNX6x/HPk4AgEFoISZRubwhXUUEkCU1EQASVpoLY27WhgtIE9SoqFvCiIHYsKEWaSAe94g+VEgiKoIIIaQQIvYXz+2M3jSSwSDa7Id/365VXdmfO7D5nZ+bM7DNnzgZYRqADCKjdPu0hJ6+hp1YMdAgBdfGr9wQ6hIDpfuPrgQ4hoMql1Al0CAF1KGNXoEOQABlSwvf9hC8eCnQIAVW/69uBDiGg9iZ/G+gQREoEX39GtX2Ox4eA9UCHQo9GREREREREJIi4kJJ7UT7Y+JrACAEecs5tBzCzKsArQG8/xSUiIiIiIiIiksXXMTDqZyYvAJxz24CGfolIREREREREROQIviYwQry9LgAws6r43ntDREREREREROSE+JqEeAX43sy+xDN4503Ac36LSkRERERERCQIHA79Rz/eKX7gUwLDOfehmf2E56dTDejknFvt18hERERERERERLx8vg3Em7BQ0kJEREREREREipz6woiIiIiIiIhI0NNAnCIiIiIiIiIFcCG67h8stCZEREREREREJOgpgSEiIiIiIiIiQU8JDBEREREREREJehoDQ0RERERERKQAGgMjeGhNiIiIiIiIiIjPzKyqmc02s7Xe/1UKKLfezFaa2XIz++l4lz+SEhgiIiIiIiIicjz6AnOdc2cBc73PCxLnnGvgnLv0Hy6fRQkMERERERERETke1wEfeB9/AHQsiuU1BoaIiIiIiIhIAQ6fpGNgmNldwF05Jo12zo32cfFI51wigHMu0cyqF1DOAbPMzAFv53h9X5fPRQkMERERERERkRLGm0woMGFhZnOAqHxmPX0cb3Olc26zN0Ex28x+dc4tOs5QsyiBISIiIiIiIiK5OOdaFjTPzJLNLNrbeyIaSCngNTZ7/6eY2STgMmAR4NPyRzo5+8KIiIiIiIiIiL9MAXp6H/cEvjqygJmVN7OwzMdAa2CVr8vnRwkMERERERERETkeLwCtzGwt0Mr7HDM7zcxmeMtEAt+Z2QpgCTDdOTfzaMsfi24hERERERERESmAC9V1/yM559KAFvlM3wy09T7+A7j4eJY/Fq0JEREREREREQl6SmCIiIiIiIiISNBTAkNEREREREREgp7GwBAREREREREpgAuxQIcgXuqBISIiIiIiIiJBr1gnMJrENGPi3Fl8tWAuve69O8/8OmfU4/2JX/DDmtXccuftueYNGvYf5vz0f4z/Zkae5YqLQYMHs2DhQr6eOZMLLrww3zI1atZk8uTJzF+wgJEjR1K6dGkAzjjjDCZOmsSa337jzrvuKsqwC82J1N/X5YNVs5gYZs+bx7yFC7n73nvz1KsZewAAV21JREFULTNw8GDmLVzI9Bz1O6VMGSZ+9RXTvv6ar2fP5qFHHinKsAtNdJNLaTf5XdpPeZ/zb+tSYLmqF5xN159nUrPlVVnTOsz4iLZfjOaaz9/i6nFvFkW4harfyAk07vUc7R56Ld/5zjmefWcqre57mfaPvEHC75uy5i1a+htXPzCcVve9zOiJC4so4sLX76l/8/XMT5g46T3OO+/sfMt0796Jr2d+QsLqRVSuXCnXvEaNGjBh4li+mvIB73/wRlGEXKge69OLiZNe55NPh3HOOXXzLTN06IN8OeFVPvv8ZQYMvIfQ0FAAmsVcyiefDmPcuBf54MPnufjic4oy9ELxxJN389XUMXz+xUjOPfeMfMs893wfJn31Nl9MeJNBzzxEqVKhx7V8MCvJ9S/J+77afniy731Mm/4eX054i/POOzPfMl27dWDa9PeIXzmLypUrZk2vUKEcI0YM4YsvRzFx0miu69i6qMIuNAMGPMGcOV8xdernnH/+ufmWufnmLsyZ8xVr1y6jSpXKWdPr1avD+PEfkJDwf9x++y1FFLGIfxTbBEZISAhPDhnMg71up3OrNrTp0I66Z+ZuzNK3b2fY4CF8NOadPMtP/XIiD/TsXUTRFr7YuDjq1q1LbEwMT/Xrx3PPPptvub59+zJ27FjiYmNJT0+nSxfPl73t27czeNAgxowZU5RhF5oTrb+vywejkJAQBg8dSu+ePbm6ZUvad+jAmWedlatMbFwcderWpXlMDE/368cQb/0O7N/Pzd260e6aa2h/zTU0i4mhQcOGgajGP2YhIVza70Hm3/8U0zvdQe02cVSsVyvfcg0euoOkxT/nmTf3zj583eUevulxf1GEXKg6xf2Ldwb0KnD+oqW/sT4xjVlvPsbQezoyePRXAGRkHGbImCm8078X019/mGnfrmDdxuQiirrwXNXsCmrXrsE1bbozeNBLDBz0aL7lli5bye29H2XTpsRc08PCKjBg4KM8cH8/ruvQk0cfGVgUYReaJlc2oFbNKDpd/xDPPzeGvv1uz7fc1zO/5YbOj9C1Sx/KlDmFjh2bA/DjkpV07/YEPXo8ydAhb9F/QN7kfzBr2vRSatU6jeva38mzQ0bwVP/89+GvZyzg+uvu5sbO91O2TBmuv/7q41o+WJXk+pf0fb+kt/1Nr2pE7dqn0+7a2xjyzGv07//vfMstX5bAXXf2ZdOmpFzTu3btwO9/bODGG+7l9t6P06fPXZQqVXzupI+JaUrt2rVo2fI6Bgx4liFDnsq33NKly+nZ8x7+/ntzrunbt6czdOiLvPPOh0URrohfFdsExoUNLubvDRvYtHEjhw4e5Jup04lt3TJXmW1pW1kdv5JDhw7lWX7pkh9JT99eRNEWvtatWjFxwgQAli1bRljFikRUr56nXJMmTZgxw9PLZMKECbRu7ck4p6WlER8fz6GDB4su6EJ0ovX3dflgdHGDBmxYv56NGzdy8OBBpk2dSstWrXKVadmqFZO89Vu+bBkVc9Rvz549AJQqVYpSpUvjnCvaCpyg8AvPYdfGzezelMThQ4fY8M0CasQ2yVPu7G7XsXHud+zbur3og/SjRhfUpVJYuQLnz12ymo6xDTEzGpxTix2795GydQfx6/6mdnQ4NaOqckrpUlzbtD5zl/xShJEXjubNmzLlq28AiI9fTVhYBapVC89T7tdf1rJ5c1Ke6dde25I5sxeRmJgCwNZitn3ExDRi+oxFAKxatZawsPKEh1fOU+77/y3PepyQsI7qkVUB2Lt3f9b0U08tQzHb/YmJu4JpU+cBsHLlGsLCylOtWpU85b777qesx6tW/Ub1yGrHtXywKsn1L+n7fklv++PimjB1ymwA4uN/9W67VfOU+/XX39m8OW+CxjkoX87z+ZUrdyrp6TvJyMjwb9CFqGXLGCZPngbA8uUrCQsLIyKiWp5yq1evyZO8A9i6dRsrV67O9zuR+OZwqJ2Uf8WRTwkMM5vry7SiFBEZSdLm7B00JTGJ6pGRAYyoaEVGRbF5c3Z2NSkpiagj6l+lShV27NiR1UAnJiYSGRVVpHH6y4nW35flg1VkVBSJidnbflI+6/Vo9QsJCWHqjBksWbqU/337LSuWLy+SuAvLqdWrsTspNev5nuQtlKte7Ygy4dSIa8q6L6blfQHniBv1Am0+eZMzOrf1d7hFLnnrDqKqZXebjgqvSPLWHSSnpRMVnj09MrwSyVt3BCLEE1K9ejWSklKynicnpxIZmfckriB16tSkYsUw3nv/dcZ/MYYOHa72R5h+ExFRheSktKznKclpVK+e9yQ+U2hoKG3bNmPx9yuypsXGNuKLL4fz6mt9GTpklF/jLWzVq4eTlJy9/ycnb6F69bxfYjOVKhXKte3i+P5/P/+j5YNNSa5/Sd/3j+Xkb/vDSUr659vup59+Rd16NZk771MmTHybF18YVawu4ERGVicxMTsxl5SUTGRk8bjwJlLYjtp3yszKAuWAamZWBchM01QETjvKcncBdwHUrBpBtbCKBRX9x8zyZoyKU0N0onyp/8n8GZ1o/YvzZ5NvrvQ46n748GHat21LWMWKvDV6NGeffTa//fabHyL1Ex/W3SWP38fy19/BHT6cp+zsXo+wNzWNMlUq0/ytF9jx50ZSl670W7hFLb/N2MzIb+sujnn3E913Q0NDOf+Cs7m99yOUKVOGTz4dxYoVCWzY8Hdhhuk3x1v/vn1vZ9nSX1i+/NesaQsW/MiCBT/SsOF53HNPF+6/v/jcQmf5bLVHW/39nrqPpT+vYtmyhH+0fLApyfUv6fv+sZTItv84lr/yyktZs+YP7rj9CWrWPI3Ro1/ghhvuYffuPYUXpB8V5/NWkcJ2rJu/7gYexpOs+JnsNm8HUODod8650cBogH/VOdMve1dKUhJRp0VnPa8eHUVqSspRlij+brn1Vrp17QrAivh4TjstO4cUFRVF8hH137p1KxUrViQ0NJSMjAyio6NJSS5+9z1mKsz6JyUmHnP5YJWUlER0dPa2HxUdTfIR6zWzfpmjP+RXv507dvDD4sU0i40tVgmMvcmplI+KyHpeLrIae1PTcpWpev5ZXPmi5/7QMpUrcVrTRriMDP6e/31W2f3btvP3/P8RfuE5J1UCIyq8Iklb0rOeJ6XtoHqVMA4eyiApLXt6clo61asWfnLZH7p1u54bbmwHwKqVvxIVlX3VKTIygpSUtIIWzSM5OZVt29PZu3cfe/fu46efVnDOuWcG9ZeYG29sTceOLQBYvfp3IqPCwduhonpkOKmp2/Jd7o47b6BylYo8//wr+c5ftuwXTq8RSaVKYaSn7/RL7IXhpi7X0qlTGwASEn4jKjJ7/4+MrEZqav7r/667u1GlSiWeHToya1pyyhaflw8WJbn+JX3fPx4nY9vfpWt7Ont7SiasWkNU1BHb7nGs/+s6tubdsZ8DsHHjZjZtSqJu3ZqsWrWmcIMuRD163ESXLp0AiI9PIDo6u7dtVFQkKSmpBS0qclI76i0kzrnXnXN1gT7OuXrOubrev4udcyOPtqy/JayIp2ad2pxWowalSpfm6vbXsnB2QO9q8buPPvyQtm3b0rZtW2bNmkWnzp0BaNiwITt37sw3gbN48WLatvU0/p07d2bW7NlFGnNhKsz6z54zx6flg1H8ihXUqVuXGjVrUrp0adq1b8/cI9brnDlzuN5bvwY56le1alXCKnpOXMqUKcOVTZvy+7p1RV6HE5GWsIawWqdT/rQoQkqVovbVsWxauDhXmSnX3sqUtrcwpe0tbJzzLT8+P4K/539PaNmylCp3KgChZcsS1fgS0tetD0At/Kd5o/OYvGAZzjmWr/mLsHJlqV61IhedeTrrE7ewMXkrBw4eYvp38TRvdF6gw/XJp59OonOn2+nc6Xbmzv2WDtd5un7Xr38+u3buZssW309i5837jksuqU9oaChly5ahfv3z+OP3Df4KvVB88cUsevR4kh49nmTBgh+5tm0zAC688Cx27dpDWtr2PMtcd11zGl9Rn/5Pv57rKl2NGtm3yp1zTl1Kly4V1MkLgPGfT6drlwfp2uVB5s//gXbtPQOSXnTROezatZstW/ImcK6/vjVNmlxCv77DctV/4YL/82n5YFKS61/S9/3jcTK2/Z9/NpWbbryXm268l3nzvqd9B894X/Xrn8vOXbvZsmWrz6+VlJjC5Zd7Bi2vGl6Z2nVq8PffeceKCCbjxo2nQ4eudOjQlTlz5tOxoyeZ16DBRezcuYvU1C0BjrBkcSF2Uv4VR+Zr9yMzuxA4HyibOc05d8yhbP3VAwPgytgY+gzsT0hoKFPGf8HYN0fRuUc3ACaM+5TwiGp8PGUy5StUwLnD7Nm9hxtatWH3rl08/8arXHLF5VSuUoWtW9J469XX+Wr8F4Ua31bn3wEyhwwdSkxMDHv37uXxPn1YudJzFfm999/nySeeICUlhZo1azJi5EgqV65MQkICjzz8MAcOHCAiIoIpU6dSoUIF3OHD7N6zh1YtW7Jr1y6/xlyYTqT+R1u+sIQeu8g/FhsXR/+BAwkJDeXL8eP578iRdOvRA4BPx40DYPDQoTSLiWHf3r086a3fOeeey0vDhxMaEkJISAjTp01j5Bv++Sm5oVXy/4m7wnBa08v41+P3YiEh/PHVNyS88wln3uA5sK/7Mve4F1cMeZxNi35g45xvKX96FM2GDwbASoWy4ev5JLzziV9i7D7uHr+87qPDP2PJqj/ZtnM34ZUq8GDXlhzyjvPS7erLcc4xZMwUvl22llPLlOb5Bzpz0Zk1AFj48xqef3caGYcdnVtcwr03xPklxgtufN0vr5upf/9HuLLpZezbt5/+T/+HhATPFbRRbw1j4IAXSU1No8fNnenduxvVqlVl69btLFr0A4MGDgPgtt5duf76thw+fJgJX07no48Kt+0vVy762IVOwBNP9KZxk4vZt+8AQ54ZxS+//AHAa6/35dmhb7NlyzYW//AJSUmp7Nm9D4D585fwzjsTuLVnB65t24xDhzLYt/8Ab7z+MStWFO4VyEMH/Xsc6dvvXppceQn79u1n8MBXWb3ak4QdMXIwQ555g9TUrfz48xQSE1PYs3svAPPmfc/otz896vLFRTDX/8BB/ybDgn3fT/jioUJ9vZyKQ9tfv+vbfnndTE89/QBXXnkp+/btZ0D/l1m9ei0Ab/73WQYPGk5q6la6d+/Ibb1vJDzcs/6/+3YJgwe/SkREVYY++zgREVUxjLHvfs70aYV74XPvPv/2iBg0qC/NmjVh79599O07mFWrVgMwZswInn56CCkpqdx6azfuvLMn1aqFk5a2jYULv+Ppp4dQrVo4kyaNo0KF8hw+7NizZw/XXNOZXbt2F1p8a9cuK57fhn10ZZ9lJ+U9O/97uWGxW28+JTDMbBAQiyeBMQO4BvjOOXfDsZb1ZwIj2Pk7gSHBzZ8JjOLAnwmM4sBfCYziwN8JjGDn7wRGsPN3AkOCl78TGMHOnwmM4sDfCYxg5+8ERrBTAqN4Ko4JDF9/RvUGoAWQ5Jy7DbgYKOO3qEREREREREREcvA1gbHXOXcYOGRmFYEUoJ7/whIRERERERERyXasXyHJ9JOZVQbG4Pk1kl3AEn8FJSIiIiIiIhIMiuuAlycjnxIYzrn7vA/fMrOZQEXnXLz/whIRERERERERyebTLSRmdr2ZVQJwzq0H/jKzjn6MS0REREREREQki69jYAxyzqVnPnHObQcG+SUiEREREREREZEj+DoGRn6JDl+XFRERERERESmWXGigI5BMvvbA+MnMhpvZGWZWz8xexTOYp4iIiIiIiIiI3/mawHgQOAB8DowH9gL3+ysoEREREREREZGcjnkbiJmFAl8551oWQTwiIiIiIiIiInkcM4HhnMswsz1mVinnQJ4iIiIiIiIiJzsXYoEOQbx8HYhzH7DSzGYDuzMnOuf+7ZeoRERERERERERy8DWBMd37JyIiIiIiIiJS5HxKYDjnPjCzU4Fazrk1fo5JRERERERERCQXn36FxMzaA8uBmd7nDcxsih/jEhEREREREQm8kJP0rxjyNezBwGXAdgDn3HKgrl8iEhERERERERE5gq8JjEP5/AKJK+xgRERERERERETy4+sgnqvMrDsQamZnAf8GvvdfWCIiIiIiIiIi2XztgfEgcAGwH/gESAce8ldQIiIiIiIiIiI5+doD43zvXynv33VAB6C+n+ISERERERERCbzQQAcgmXxNYIwD+gCrgMP+C0dEREREREREJC9fExipzrmpfo1ERERERERERKQAviYwBpnZO8BcPONgAOCcm+iXqEREREREREREcvA1gXEbcC5QmuxbSBygBIaIiIiIiIicvHz96QvxO18TGBc75y7yayQiIiIiIiIiIgXwNZf0g5md79dIREREREREREQK4GsPjKZATzP7E88YGAY455x+RlVERERERERE/M7XBEabf/oGh3H/dNFiz9cP92R1CAt0CAFVOtABBNiAHZsCHUJAdQ90AAG0Z/eGQIcQUJ/UOBDoEAKq45rEQIcgAdI2rEagQwio+l3fDnQIARX/2d2BDiGg2jz6V6BDEH/SGBhBw6fv2M65kn02KiIiIiIiIiIBpVySiIiIiIiIiAQ9JTBEREREREREJOiV9GEaRERERERERApkuuwfNLQqRERERERERCToKYEhIiIiIiIiIkFPCQwRERERERERCXpKYIiIiIiIiIhI0NMgniIiIiIiIiIFsBAX6BDESz0wRERERERERCToKYEhIiIiIiIiIkFPCQwRERERERERCXoaA0NERERERESkAKbL/kFDq0JEREREREREgp4SGCIiIiIiIiIS9JTAEBEREREREZGgpzEwRERERERERAoQEhroCCSTemCIiIiIiIiISNBTAkNEREREREREgp4SGCIiIiIiIiIS9DQGhoiIiIiIiEgBQnTZP2hoVYiIiIiIiIhI0FMCQ0RERERERESCnhIYIiIiIiIiIhL0lMAQERERERERkaCnQTxFRERERERECmAhLtAhiJd6YIiIiIiIiIhI0CvWCYwmMc2YPHc2UxbM47Z7784zv84Z9fhg4hcsWbOaW++847iWDXbNYmKYNW8ecxcu5O577823zIDBg5m7cCHTZs7kggsvzDUvJCSEKTNmMPrdd4siXL8YNHgQCxYu4OuZX3PBhRfkW6ZGzRpMnjyZ+QvmM3LkSEqXLg3AGWecwcRJE1nz2xruvOvOogy7UDSNieHreXP5ZuEC7ixg/T89eBDfLFzAVzO/5vwcn09YxYq8Puq/zJg7l+lz59DgX/8qqrAL1cCBTzFv3kymz5jEBRecl2+ZGjVOZ8LEz5g772veeOOVrPVfIawCo8e8ybTpE/l65hQ633B9UYZ+QvqNnEDjXs/R7qHX8p3vnOPZd6bS6r6Xaf/IGyT8vilr3qKlv3H1A8Npdd/LjJ64sIgiLlzNYmKYO28e8xcu5J4Ctv1Bgwczf+FCvj6i7XvxpZf48eefmTlrVlGFW+jCLr2Cc8Z+zrnvfUH1LrfkmV++/r+4cNIczh71IWeP+pDIHr2z5lXr1JVzRn/C2aPHUavfEKz0KUUZeqEoyeu/JNcd4PwrL2fg1E8ZPONzWt1+c575ja5tzVMTP+CpiR/w2Mdvcfo5Z2bNi735Rp6e9BH9J39M3M03FWXYherJvvcxbfp7fDnhLc4778x8y3Tt1oFp098jfuUsKleumDW9QoVyjBgxhC++HMXESaO5rmProgr7hJX0416me++N5d33bmPUqJs588zq+ZZ55JFW/HfUzYwadTNP929H2bKls+bVr1+DN//bg7dH38qwl24sqrBFCl2xTWCEhITQb8hg7u/Vm06trqZNh/bUOzN3Y56+PZ1hg4fw4Zixx71sMAsJCWHw0KHc3rMnbVq2pF2HDpx51lm5ysTExVGnbl1axMTQv18/nnn22Vzze/Xuzbp164oy7EIVGxdL3bp1iY2J5al+T/Hcs8/lW65v376MHTuWuNg40tPT6dKlCwDbt29n8KDBjBkzpgijLhwhISEMHDqEO3v2ol3LVlzboQNnnJV7+20WF0vtunW5OiaWgf2eYlCOz+fpQYP4duFC2rZoQcc21/B7MdwOYmObUadObZo3b8PTTw1iyNBB+ZZ74snHeO/dD2jR/BrSd+zgxps6AXDLLd1Zt+532l3biR7de/LUU09kJTeCXae4f/HOgF4Fzl+09DfWJ6Yx683HGHpPRwaP/gqAjIzDDBkzhXf692L66w8z7dsVrNuYXERRF46QkBCGDB1Kr549ad2yJR3yaftivW1fXEwM/fr149kcbd+EL76gV8+eRR124QkJ4fQH+vDn04+w5s5uVI5tTZladfIU271yOb/deyu/3XsryeM8SepS4RFU63gTvz1wG7/d1QMLCaFybKsirsCJKcnrvyTXHcBCQrip/2O8ee9jDO3Qg0vbtiSqXp1cZbZs2syrvR7g+U49+fqt9+k+6AkAos+sy5WdOzCs2x0837knF8Y0IaJWjQDU4sQ0vaoRtWufTrtrb2PIM6/Rv/+/8y23fFkCd93Zl02bknJN79q1A7//sYEbb7iX23s/Tp8+d1GqVPG4k7wkH/cyNWpUh9NOr0zv297j9dfn8MCDzfMt9/bbC7nv3o+5996PSU3ZQYcODQAoX74M9z/QnMGDpnD3XR/y3LPTijB6kcLlUwLDzK70ZVpRurDBxWzcsIFNGzdy6OBBvpk6jdjWLXOV2ZaWRkL8Sg4dOnjcywazixs0YMP69WzcuJGDBw8yfepUWrbKfSLaslUrJk2YAMDyZcuoWLEiEdU92dqoqChimzdn/GefFXnshaV1q9ZMnDARgGXLlhFWMYyI6hF5yjVp0oQZM2YAMGHCBFq39lxxSEtLIz4+nkMHDxVd0IWkfoMG/LV+A3971/+MqVNp0Sr3lZQWrVrzlffzWbFsGRW9n0/5ChW49PLL+PKzzwE4ePAgO3fsKPI6nKiWLZszaZLnBGX58nhP/SKq5SnXuPHlfP2154rjxAmTadWqBeC5WlO+fHkAypUrR/r2dA4dKh7bQqML6lIprFyB8+cuWU3H2IaYGQ3OqcWO3ftI2bqD+HV/Uzs6nJpRVTmldCmubVqfuUt+KcLIT9yRbd/UqVNpdUTb16pVKyYW0PYtWbKE7du3F3XYhabcOedzYPPfHEjajDt0iO0LZ1OpSTOfl7fQUELKlIGQUELKlOXg1lQ/Rlv4SvL6L8l1B6hz0Xmk/vU3aX9vJuPQIX7+ei71m1+Vq8yfy1exd8dOz+P4BCpHes956tXhz/gEDu7bz+GMDNb+tJyLW/i+3wSLuLgmTJ0yG4D4+F8JCytPtWpV85T79dff2bw575d056B8Oc+xo1y5U0lP30lGRoZ/gy4kJfm4l6lx4zOYO8cT+6+/JlGhfBmqVi2fp9yePQeyHp9SphQOz7gNcXHn8P3/1pGa6tlH0tP3FkHUJ5eQkJPzrzjyNewRPk4rMtUjI0nanJj1PDkxieqRkX5fNhhERkWRmJgdf1JiIpFRUXnLbN6cXSYpiUhvHfsPGsSLzz+PO3y4aAL2g8ioSDYfUb+oyNyfQZUqVdixY0fWAToxMZHIqOKzngsSGRVJYmKOuudTr8ioyHzWfxQ1a9Via1oa/3n5ZSbOmM7QF1/g1FNPLbLYC0tkVHU2J2ZfXUpKSibqiM+gSpXK7NyRfYKWlJRMlHcf+OjDcZx5Rj0W/7CQGV9/xZChz+PcyTE4U/LWHURVq5T1PCq8Islbd5Cclk5UePb0yPBKJG8tXsmrqHzavqhjtH2JSUlZ6724K10tggOpKVnPD6amUDo8b+K23PkXcfaoj6j73KuUqV0XgENpqaR+MY7zPp7MBZ9NI2PPbnb9vKTIYi8MJXn9l+S6A1SuHsG2pOxtf3tyCpXzuWiRqUmndiR89wMAm9f9wZmXXEz5ShUpXbYMF1zVmCrF8FygevVwkpKyk47JyVuoXj3c5+U//fQr6tarydx5nzJh4tu8+MIoHfeKkfBqFbKSDwCpW3YRHl4h37KPPtaaTz+7i5o1qzLlq+UAnF6jChUqlGHYsBsYMbI7LVrmf+utSHFw1ASGmTU2s8eACDN7NMffYCD0KMvdZWY/mdlPaTv901CYWZ5pvrbDJ7JsMMgbPXkOQvnX0RHXvDlpaWkkrFrlp+iKRkH1O94yxZMP9Sqg7qVCQzn/wgv59OOP6dT2Wvbu2cud9+V/L3Uw+8fr33sl4qpmTVn9y680viKG9u06MXhwfypUyHslozjKbxM3M/Lb8vNrS4LZibR9J4d8PoEjqrZ33a/8cnNHfrv3FrZMHk/dwcMACK0QRsUmzfjl1k4kdGtHSNmyVG7RpghiLjwlef2X5LoDBR7T8nNWo3/RpFM7vhr+XwCS/9jA7HfH8cCY13jgreFs+m0dh4tJz4Oc8j+m+e7KKy9lzZo/aNG8GzfecC9PPfUA5csX3KuhODmZj3uZfGkDMg1/ZRY9uo/hr7+20izmbABCQ0M486xIBgyYzNNPTaR798s5/fTK/gtYxI+OdfPbKUAFb7mwHNN3ADcUtJBzbjQwGqBBnTP8cvRMTkoi6rTorOeR0VGkpvh2X9uJLBsMkpKSiI7Ojj8qOpqU5NzxJyUmEn3aadlloqJISUnhmrZtadGyJTGxsZQpU4YKYWG88tprPPbww0UV/j92y6230K1rNwBWxK/gtCPql3zEOty6dSsVK1YkNDSUjIwMoqOjSUlOobhLTkoiOjpH3fOpV3JiUj7rPxnnPPPily8H4JsZM4pNAuPmW7rRpYtn0KmV8Ss5LTqKn73zoqIiST7iM9i6dRthFcOy1n/OMjfccD1vvfUOABs2/MXfG/+mXr16xMevLLL6+EtUeEWStqRnPU9K20H1KmEcPJRBUlr29OS0dKpXrZjfSwStxHzavuRjtH3RUVEkpxT//R7g4JYUTonIHritdET1PLeBHN6zJ+vxzh8XY6GlCK1YiQoXX8KBpM1kpG8HIP27BZQ//yK2z51ZJLEXhpK8/kty3cHT46JKVPa2XzmyOumpW/KUO+3sM+gxpC//vecxdqdnX0BbPHEaiyd67vnv8NDduXpzBLMuXdvTuXNbABJWrSEqKrvXSWRkNVJT0nx+res6tubdsZ7bRzdu3MymTUnUrVuTVavWFG7QAXCyHvfat7+YNtd4BuP97bdkIiKyv4pFVKvA1q27C1z28GHHooVruOHGS5k9azVbUnexI30v+/cfYv/+Q6xauYl69SLYtGm7v6shUuiO2gPDObfQOfcMcIVz7pkcf8Odc2uLKMZ8JayIp1adOpxWowalSpfm6vbtWDh7rt+XDQbxK1ZQu25datSsSenSpbm2fXvmzp6dq8zcOXO4vnNnABo0bMjOnTtJTUnh5WHDaHrFFcQ2bcrDDz7I4u+/LxbJC4CPPvyItm3b0rZtW2bNmkWnzp4BGRtm1S/v/dyLFy+mbVvPwb9z587Mml18R2DPtHLFCmrXrcPpNWtQunRp2rZvz7wj1v+8ObO5zvv5XJzj89mSmkpi4mbq1qsHQOMrr+T3tQHdlX328Uef0r5dJ9q368Ss2XO5/vrrAGjQoL6nfvmczP7wwxKuucYzPkinzh2ZM2ceAJs3J9KkyRUAhFcLp269umzcuLGIauJfzRudx+QFy3DOsXzNX4SVK0v1qhW56MzTWZ+4hY3JWzlw8BDTv4uneaPi1YU0fsUK6uRo+9q3b8+cI7b9OXPm0Cmftu9ksGfNL5xyek1OiYrGSpWickwr0hd/m6tMqSrZ98Sfes75EGJk7EjnYGoy5c+9ECtTBoAKDS9l/1/rizL8E1aS139JrjvAhlW/Ur1WDcJPjya0VCkuuaYFK+d/l6tMlahI7nrteT7oN4SUDbnb8wpVK2eVubhFDD99PaeoQj8hn382lZtuvJebbryXefO+p30Hz7gn9eufy85du9myZavPr5WUmMLllzcEoGp4ZWrXqcHffyceY6ni4WQ97k2duoL77xvH/feNY/H3v2fd9nHuuVHs3nMg3wRG9GnZt8xcfkU9Nm70bCOLF//OBReeTkiIUaZMKc45N4q//vJ9+5HAj1WhMTCy+Tr88B4zewm4ACibOdE5l/8QuEUgIyODFwY+w6gP3yckNISvxn/J72vXckMPzxX6L8d9SnhENT6ZMpnyFSrgnKNH7150atWG3bt25btscZGRkcEzAwfy3ocfEhoayhfjx7N27Vq69egBwKfjxrFg3jxi4+KYt2gRe/fu5ck+fQIcdeGaP28+cXFxLFy0kL179/J4n8ez5r33/ns8+cSTpKSk8MJ/XmDEyBE81ucxEhISGP/5eAAiIiKYMnUKFSpUwB129O7dm1YtW7Fr165AVclnGRkZDB04kLEffkhIaCgTxo9n3dq1dPGu/8/HjWPhvPk0i4tj1qKF7Nu7l6dyfD7PDhrMS6+/RunSpdn410aeKobbxoL5i4iNbca8+TPZt28fTz7xdNa8se++Rb++A0hJSWXYi6/w+hsv8+ijD5Gw+he+GO8Z4G7kiFEMe+l5Znw9GcMY9uJwtm3bHqDaHJ9Hh3/GklV/sm3nbprd8QIPdm3JIW936G5XX07MJeewcOkaWt33CqeWKc3zD3i+0JQKDWXgHR24Y8h7ZBx2dG5xCWfVKl73gWdkZDBo4EA+9G77mW1fd++2/8m4ccyfN4+4uDgWeNu+J3Js36+/8QZXNG5MlSpV+P6HH3jt1VcZ//nngarO8TucwaaRL1Pv+dchJISt30xj/4Y/Cb/W8zPAadMnUemq5lRr1wmXkcHhA/vZ8PwAAPb8msD2b+dx9n8/wGVksHfdb6TNmBzAyhy/krz+S3LdAQ5nZDD++Ve5/+3hhISGsnjSNBJ//5OmN3UE4Lvxk7nm3tsoX6kiXft76p2RkcGwLrcDcOerz1O+ckUyDh1i/HOvZA32WZx8++0Srmp2GdNnvM++ffsZ0P/lrHlv/vdZBg8aTmrqVrp378htvW8kPLwqX054m+++XcLgwa/y9tvjGPrs40yY+DaG8dprY9m+vXiMB1GSj3uZliz5k0aN6vDue7exf/8hhr+SfUFuyNCOvPbqbLZt202fPm0oV+4UzOCPP1IZOcJz4Wbjxq38/NN6Rr11C845Zs5cxYYNvvfgEQkm5sv9kWY2C/gc6APcA/QEUp1zTx5rWX/dQlIc7HLF41cN/OVQsb3TsHCUPXaRk9rB0JPj3tp/6vepQwMdQsDUbftooEMIqMnnRB+70Ems45qT46quHL+2YcXv50kL07d2coyl9E/Ff3Z3oEMIqDaP/hXoEAJq5jePnNQn/i3fXHZSfqedc3/DYrfefO04Eu6cGwsc9N5W0hu4wo9xiYiIiIiIiIhk8fUWkoPe/4lmdi2wGSjZaXYRERERERE56RXX8SJORr4mMJ41s0rAY8AIoCLwiN+iEhERERERERHJwacEhnNumvdhOhDnv3BERERERERERPLyqTOMmX1gZpVzPK9iZu/6LSoRERERERERkRx8vZunvnNue+YT59w2oKFfIhIREREREREROYKvY2CEmFkVb+ICM6t6HMuKiIiIiIiIFEsaxDN4+JqEeAX43sy+BBxwE/C836ISEREREREREcnB10E8PzSzn4DmgAGdnHOr/RqZiIiIiIiIiIiXTwkMM/vIOXcLsDqfaSIiIiIiIiIifuXrLSQX5HxiZqHAJYUfjoiIiIiIiEjw0BgYweOoq8LM+pnZTqC+me3w/u0EUoCviiRCERERERERESnxjprAcM79xzkXBrzknKvo/QtzzoU75/oVUYwiIiIiIiIiUsL52hlmmpmVBzCzm81suJnV9mNcIiIiIiIiIiJZfB0DYxRwsZldDDwBjAU+BGL8FZiIiIiIiIhIoIWGuECHIF6+9sA45JxzwHXA686514Ew/4UlIiIiIiIiIpLN1x4YO82sH3Az0Mz7KySl/ReWiIiIiIiIiEg2X3tgdAH2A7c755KA04GX/BaViIiIiIiIiEgOPvXA8CYthud4/heeMTBERERERERETlohvl72F7/zKYFhZjuBzJFLTsFz+8gu51wlfwUmIiIiIiIiIpLJ1x4YuQbsNLOOwGX+CEhERERERERE5Ej/qDOMc24y0LxwQxERERERERERyZ+vt5B0yvE0BLiU7FtKRERERERERET8ytefUW2f4/EhYD3QodCjEREREREREQkiGsQzePiawAgBHnLObQcwsyrAK0BvP8UlIiIiIiIiIpLF11xS/czkBYBzbhvQ0C8RiYiIiIiIiIgcweceGGZWxZu4wMyqHseyJdYhLNAhBFSpEj5MyuESvv4PHz4Y6BAkQKpFXBHoEAKqX6XugQ4hoGrWnBvoECRAVgY6gADbm/xtoEMIqDaP/hXoEAJq5vBagQ5BpETwNQnxCvC9mX2JZ/DOm4Dn/BaViIiIiIiISBAI1RgYQcOnBIZz7kMz+wnPT6ca0Mk5t9qvkYmIiIiIiIiIePl8G4g3YaGkhYiIiIiIiIgUOXWGEREREREREZGgp4E4RURERERERAoQUrLH5g8q6oEhIiIiIiIiIkFPCQwRERERERERCXpKYIiIiIiIiIhI0NMYGCIiIiIiIiIFCNVl/6ChVSEiIiIiIiIiQU8JDBEREREREREJekpgiIiIiIiIiEjQUwJDRERERERERIKeBvEUERERERERKUCILvsHDa0KEREREREREQl6SmCIiIiIiIiISNBTAkNEREREREREgp7GwBAREREREREpQKgu+wcNrQoRERERERERCXpKYIiIiIiIiIhI0FMCQ0RERERERESCnsbAEBERERERESmAxsDIy8yqAp8DdYD1wE3OuW1HlDnHWyZTPWCgc+41MxsM3Amkeuc95Zybcaz31aoQERERERERkePRF5jrnDsLmOt9notzbo1zroFzrgFwCbAHmJSjyKuZ831JXoASGCIiIiIiIiJyfK4DPvA+/gDoeIzyLYDfnXMbTuRNlcAQERERERERkeMR6ZxLBPD+r36M8l2BT4+Y9oCZxZvZu2ZWxZc31RgYIiIiIiIiIgU4WcfAMLO7gLtyTBrtnBudY/4cICqfRZ8+zvc5BegA9MsxeRQwFHDe/68AvY/1WkpgiIiIiIiIiJQw3mTF6KPMb1nQPDNLNrNo51yimUUDKUd5q2uApc655ByvnfXYzMYA03yJuVgnMJrENOOJgQMICQ1l0uef896ot3PNr3NGPZ556UXOu+ACRr48nA/HvOPzssXBoMGDiIuLY+/evfTp04eEVQl5ytSoWYORI0ZSqXIlElYl8Mgjj3Dw4EHOOOMMXnr5JS644AJefvllxoweE4Aa/HPNYmLoP2gQoaGhjP/sM94eNSpPmQGDBxPr/Xye7NOHhFWrOKVMGT4dP55TTjmFUqVKMXPGDF5/9dUA1ODEXBUTw9ODBhIaGsoXn33O6Hzq33/wIGK89e/bpw+rc2wfISEhTJw2leSkJO7ufXtRhl5oBg0aQGxcDPv27qVPnydJSFidp0yNGjUYMfI1KlWqREJCAo8+8jgHDx7k8isuY/Tot/j7778BmDlzFiPeGFnUVfhH+o2cwIKffiW8Unmmvf5wnvnOOZ4bO42FS9dQtswpvPBAZy4443QAFi39jefencbhw4e5sWUj7uoUU8TRF47H+vTiyisbsm/ffp4ZPIo1a/7MU2bo0Ac57/x6HDqUQULCOp5/bgwZGRk0i7mUe+65CXfYcSgjg+GvfMCKFWsCUIt/7u7bLqLRv6qzf38Gw99cxu9/phdY9p7eF9Eqrhadb5kOwBWXRnFL13M57OBwhuPt91ey+tetRRV6ofj3Q525ovH57N93gP88P47ffvs7T5kBA2/lnHNrcuhQBr/88hcvD/uMjIzDlC9flv4DbyUysgqhoSF89uk8vp7xfwGoxT93IvWvEHYqfft15/TTqnHgwCFe+M8n/PlnYgBq8c+U5LoDDBjwBDExV7J37z6efHIQq1f/mqfMzTd3oVev7tSuXYvLLotj27btANSrV4cXXniGCy44l+HDRzJ27EdFHP2Ju/feWBpdVpf9+w7yyiuzWLcu73elRx5pxVlnR2LA35u288rL37Bv30EA6tevwd33xFCqVCjp6Xt54vEvirgG/4yO+xLEpgA9gRe8/786StluHHH7SGbyw/v0emCVL29abDvDhISE0G/IYO7v1ZtOra6mTYf21DvzzFxl0renM2zwED4cM/a4lw12sXGx1K1bl9iYWJ7q9xTPPftcvuX69u3L2LFjiYuNIz09nS5dugCwfft2Bg8azJgxxStxAZ71N3joUG7v2ZM2LVvSrkMHzjzrrFxlYuLiqFO3Li1iYujfrx/PPPssAAf27+eWbt1of801tL/mGq6KiaFBw4aBqMY/FhISwqChQ7izZy/atmxFuw4dOOOs3NtvTFwsderWpVVMLAP6PcUzR2wfPXvfxu/r1hVh1IUrNjaGOnVrExfbkn5PDeDZ54bkW65v38cZO/Y9mse1Ij19Bzd1uTFr3o8//sS1bTtwbdsOxSZ5AdAp7l+8M6BXgfMXLf2N9YlpzHrzMYbe05HBoz3HkoyMwwwZM4V3+vdi+usPM+3bFazbmFzg6wSrJlc2oFbNKDpd/xDPPzeGvv3yT8B9PfNbbuj8CF279KFMmVPo2LE5AD8uWUn3bk/Qo8eTDB3yFv0H3F2U4Z+wSxtW5/To8tzx4FzeeHsFD9x5cYFlz6pXmQrlS+eatnxVKvf3WcCDjy/g1f8u46F7Gvg54sJ1xRXnU6NmBN27DuWllz7n0T435Vtu9qyfuLn7c/S69QXKlClNu/ZNALi+01VsWJ9E714v8u8HR3D/Ax0pVSq0KKtwQk60/rfc0pp1azdxW68Xee7Zj/j3Q52KMvwTUpLrDhAT05TatWvRsuV1DBjwLEOGPJVvuaVLl9Oz5z38/ffmXNO3b09n6NAXeeedD4si3ELXqFEdTju9Mr1ve4/XX5/DAw82z7fc228v5L57P+beez8mNWUHHTo0AKB8+TLc/0BzBg+awt13fchzz/p0oTcolPTjvgS1F4BWZrYWaOV9jpmdZmZZvyhiZuW88ycesfwwM1tpZvFAHPCIL29abBMYFza4mI0bNrBp40YOHTzIN1OnEds6dw+XbWlpJMSv5NChg8e9bLBr3ao1Eyd4toFly5YRVjGMiOoReco1adKEGTM828+ECRNo3bo1AGlpacTHx3Po4KGiC7qQXNygARvWr2fjxo0cPHiQ6VOn0rJVq1xlWrZqxaQJEwBYvmwZFStWJKK6Z1yZPXv2AFCqVClKly6Nc65oK3CC6jdowIb1G46of+tcZVq0as0k7/ax4ojtIzIqitjmzfnis8+KPPbC0qp1SyZOnAzA8mXLqRgWRkRE3u2/cZMr+HrGTAAmTJhI62K2n+en0QV1qRRWrsD5c5espmNsQ8yMBufUYsfufaRs3UH8ur+pHR1OzaiqnFK6FNc2rc/cJb8UYeSFIyamEdNnLAJg1aq1hIWVJzy8cp5y3/9vedbjhIR1VI+sCsDevfuzpp96ahmK2e7PFY2imbtwIwBr1m6jfPnSVKlcJk+5kBDofcv5jP0od8+8ffsysh6XLRta7Orf9KqL+GbmEgBWJ6ynQoVTCQ+vmKfcDz9k98j6ZfUGIqpXAsA5OLWc5/Mqd+op7Nixh4yMw0UQeeE40frXqRPFzz//BsBff6UQFR1OlSphRRD5iSvJdQdo2TKGyZM9X7qXL19JWFgYERHV8pRbvXoNmzbl7Vmydes2Vq5czaFDxe+8D6Bx4zOYO8dzzPr11yQqlC9D1arl85Tbs+dA1uNTypTC4Wnk4uLO4fv/rSM1dScA6el7iyDqwlHSj/sSvJxzac65Fs65s7z/t3qnb3bOtc1Rbo9zLtw5l37E8rc45y5yztV3znXI0RvjqHxKYJjHzWY20Pu8lpld5nv1Cl/1yEiSNmfXMTkxieqRkX5fNlhERkWyeXN2dj0pKYmoyNzjq1SpUoUdO3aQkeE5YU1MTCQyqnjVMz+RUVEkJmavv6TERCKjovKWOeLzifSu45CQEKbMmMH/LV3Kd99+y4rly4sk7sISGRVJUmKOuuWzXiOjIknKUf/kpCQivdvH04MGMuz5/3D4cDH75pJDZGQkiTn24cSkJKKO+Aw82//OrO0/KTF7GwD4178aMOPrKbz3/jucdVbx6oF1NMlbdxBVrVLW86jwiiRv3UFyWjpR4dnTI8Mrkbx1RyBCPCEREVVITkrLep6SnEb16lULLB8aGkrbts1Y/P2KrGmxsY344svhvPpaX4YOyXv7VTCrVrUsqWnZJ95b0vZSreqpecq1b1OP//spiW3b9+eZ1/iyaN5+rTnP9LuC10Yt82u8ha1atUqkpGzPep6asp1qObb3I4WGhnD11Y1Y8oPnpH3ihEXUrh3FpMlDee+Dfrzx+oRilcQ+0fqvW7eJZs08vXbOO68WkZFViKhe2Z8hF5qSXHeAyMjqJCYmZT1PSkomMvJYA/6fPMKrVchKPgCkbtlFeHiFfMs++lhrPv3sLmrWrMqUr5YDcHqNKlSoUIZhw25gxMjutGh5XlGEXSRO9uN+sAgJOTn/iiNfw/4v0BjPvSsAO4E3/RKRj8wszzRfz0FOZNlgkX8d3HGXKY7y1ur46n748GE6tG1L0yuu4OIGDTjr7LP9EabfWD6fgK/1j23enLS0NBJW+XSLWdA60e0/YdVqml4ZS9trOvDB+x/x9uji9SX2aPLbxc2M/Pb8/PalYHe87VrfvrezbOkvLF+efa/4ggU/cuMNj/J4n5e5554ufonTb/JZae6ItVu1SlmaNj6NKV/nHRsEYPGSRO5+eB5Dhy3hli7F6yQ+3/V/lPKPPnYTK1b8Tnz8HwBcdvl5rFv7N9d3HMDtt73II4/cSLlyZf0UbeE70fqP+3gOYWGnMva9J+jUOYa1a//OSvIGu5Jcdzh5z+l85cu5X6bhr8yiR/cx/PXXVprFeM7xQkNDOPOsSAYMmMzTT02ke/fLOf30yv4LuAid7Md9kSP5Oojn5c65f5nZMgDn3DbvT6HkK+fPsdSoWo3wsLxd/E5UclISUadFZz2PjI4iNcW3+7pOZNlAuuXWW+jW1ZNDWhG/gtNOOy1rXlRUFMlH1GHr1q1UrFiR0NBQMjIyiI6OJiX5aIPDFg9JSUlER2evv6joaFKSc9c9KTGR6CM+n5SU3HXfuWMH/7d4Mc1iY1n722/+DboQJSUlERWdo275rNekxCSictQ/MiqKlJRk2rRtS4uWLYmJjaNMmTJUCKvAS6+9yuMP+3TLWUDdcksPunbzfNmMXxFPdI59ODoqiuQjPgPP9h+Wtf1HRWdvA7t27coqt2DBQoY+O5gqVaqwbdu2IqiJf0WFVyRpS3YPvaS0HVSvEsbBQxkkpWVPT05Lp3rVwm+b/eHGG1vTsWMLAFav/p3IqHDwdqioHhlOamr+6+2OO2+gcpWKPP/8K/nOX7bsF06vEUmlSmGkp+/Mt0wwaHd1Xa5uWRuAteu2ERGe3eOiWvippG3dl6v8GXUrER1VnrEjPLdMlTkllHdGtOCOB+fmKrfqlzSio8pRMewUduw8QLC6vtNVtGvfGIBff/mL6jmumkdUr0zalvR8l+t1WxsqV65A/6ezx8Fq2/Zyxn08G4BNm7aQmJhG7drV+eWXv/xXgRNUmPXfs2cfL/znk6znn38xiMTNwTuIa0muO0CPHjfRpYtnrI74+ASio7N7m0ZFRZKSkhqo0IpE+/YX0+aaCwH47bdkIiKyb/mJqFaBrVt3F7js4cOORQvXcMONlzJ71mq2pO5iR/pe9u8/xP79h1i1chP16kWwadN2f1fD707G477I0fjaA+OgmYXiTXabWQRQ4E2jzrnRzrlLnXOX+iN5AZCwIp5adepwWo0alCpdmqvbt2Ph7LnHXvAElw2kjz78iLZt29K2bVtmzZpFp86eg1rDhg3ZuXMnqfkcyBYvXkzbtp5bkDp37sys2bOKNGZ/iF+xgtp161KjZk1Kly7Nte3bM3f27Fxl5s6Zw/WdOwPQIOvzSaFq1aqEVfRsk2XKlKFJ06b8UcwGs1y5YgV16tahRs0aBdZ/3pzZXO/dPi5u2JBd3u3jlWHDaHZFY5o3bcojDz7ID99/XyySFwAffTQua9DNWbPm0KlTRwAaNGzgWb+pebf/Hxb/H9e0bQNA586dmD1rDgDVctw3fPHF9TELOSmSFwDNG53H5AXLcM6xfM1fhJUrS/WqFbnozNNZn7iFjclbOXDwENO/i6d5o+Jx9f2LL2bRo8eT9OjxJAsW/Mi1bZsBcOGFZ7Fr1x7S0rbnWea665rT+Ir69H/69VxX6WrUyL6N6Jxz6lK6dKmgTl4ATPvmTx583DPw5uIfk2gRUxOAc86qwu49B/PcJvLj0mRuvvMbbrt/NrfdP5v9BzKykhfRUdn3jJ9RtxKlSoUEdfICYNLEb7n9tmHcftswvv02nqvbeO5gPf+COuzetY+0tLxdoq9t15jLLjuPZwZ/kGv9Jydv45JLzwGgSpUwataqzubNaXmWDyaFWf8KFU7NGrS0XfvGrFjxO3v27MuzfLAoyXUHGDduPB06dKVDh67MmTOfjh3bAdCgwUXs3LmL1NQtAY7Qv6ZOXcH9943j/vvGsfj737Nu+zj33Ch27zmQbwIj+rTsWyYuv6IeGzd6klSLF//OBReeTkiIUaZMKc45N4q//gruBJavTsbjvsjR+NoD4w1gElDdzJ4DbgD6+y0qH2RkZPDCwGcY9eH7hISG8NX4L/l97Vpu6OHpofDluE8Jj6jGJ1MmU75CBZxz9Ojdi06t2rB71658ly1O5s+bT1xcHAsXLWTv3r083ufxrHnvvf8eTz7xJCkpKbzwnxcYMXIEj/V5jISEBMZ/Ph6AiIgIpkydQoUKFXCHHb1796ZVy1a5rkwHq4yMDJ4ZOJD3PvzQ8zOi48ezdu1auvXoAcCn48axYN48YuPimLdoUdbPqAJEVK/OS8OHExISQkhICDOmTWP+vHmBrM5xy8jIYMjAgYz11v/L8eNZt3YtXb31/2zcOBbMm09MXBxzvNtHvxzbx8lg/vwFxMXFsGDhXPbu3csTj/fNmvfue2Po++TTnu3/hZcYMeJVHnvsEVYnrGb8+C8BaHtNG3rc3J2MjEPs27effz/4cIBqcvweHf4ZS1b9ybadu2l2xws82LUlh7zdoLtdfTkxl5zDwqVraHXfK5xapjTPP+BJ5JUKDWXgHR24Y8h7ZBx2dG5xCWfVKn5j4vzvf8u48sqGTJr8Ovv2HWDIM9m3/7z2el+eHfo2W7Zso2+/O0hKSuXddz2/QDR//hLeeWcCzVtczrVtm3HoUAb79h/gqX6vBagm/8yPS5Np1DCSsSNasv9ABq++mT2GxTP9ruD1t5azdVvBX8quvDyaFjE1OZThOHAggxde/akowi40PyxeTePGF/Dp5wOzfkoz07CX7ubFFz4lLW0Hj/W5ieTkbYx625OgXbQwng/en8kH78/kqadv5v0P+oLBW6OmkJ5e8FXcYHOi9a9dO5Kn+99MxmHHhvVJvPDCJwW9VdApyXUHWLDgO2JimjJ37hT27t1H376Ds+aNGTOCp58eQkpKKrfe2o077+xJtWrhTJ06noULv+Ppp4dQrVo4kyaNo0KF8hw+7OjVqwfXXNOZXbuKx/a/ZMmfNGpUh3ffu439+w8x/JXsC3JDhnbktVdns23bbvr0aUO5cqdgBn/8kcrIEZ5zvI0bt/LzT+sZ9dYtOOeYOXMVGzYEd/IyU0k/7geLUN1/EzTM1/vnzOxcoAWe26fmOud8Gsa2QZ0zSs4NekfY7orPvZX+UOqod6ee/EJK+J2GB630sQudxP6c/kKgQwiYRj3HBzqEgIqo2z3QIQTUrsTg79Eo4g+Jyd8GOoSAOqPerYEOIaBmDq8V6BAC64LOJ/WJ771fLT0pv9iMuu5fxW69+dQDw8yqAinApzmmlXbOHSx4KRERERERERGRwuHrGBhLgVTgN2Ct9/GfZrbUzC7xV3AiIiIiIiIiIuD7GBgzgUnOuW8AzKw10AYYj+cnVi/3T3giIiIiIiIigRPq62V/8TtfV8WlmckLAOfcLKCZc+4HoIxfIhMRERERERER8fK1B8ZWM3sS+Mz7vAuwzfvTqgX+nKqIiIiIiIiISGHwtQdGd6AGMBn4CqjlnRYK3OSXyEREREREREREvHzqgeGc2wI8WMDsdYUXjoiIiIiIiEjw0BgYwcPXn1GNAJ4ALgDKZk53zjX3U1wiIiIiIiIiIll8zSWNA34F6gLPAOuBH/0Uk4iIiIiIiIhILr4mMMKdc2OBg865hc653sAVfoxLRERERERERCSLr79CctD7P9HMrgU24xnUU0RERERERETE73xNYDxrZpWAx4ARQEXgYX8FJSIiIiIiIhIMSoVYoEMQL18TGNucc+lAOhAHYGZX+i0qEREREREREZEcfB0DY4SP00RERERERERECt1Re2CYWWOgCRBhZo/mmFURCPVnYCIiIiIiIiIimY51C8kpQAVvubAc03cAN/grKBEREREREZFgEOrrfQvid0dNYDjnFgILzex959yGIopJRERERERERCQXXwfx3GNmLwEXAGUzJzrnmvslKhERERERERGRHHztDDMO+BWoCzwDrAd+9FNMIiIiIiIiIiK5+NoDI9w5N9bMHspxW8lCfwYmIiIiIiIiEmihFugIJJOvCYyD3v+JZnYtsBmo4Z+QRERERERERERy8zWB8ayZVQIeA0bg+RnVh/0VlIiIiIiIiIhITr6OgXEjYM65Vc65OKAVcL3/whIRERERERERyeZrD4z6zrntmU+cc1vNrKF/QhIREREREREJDqG+XvYXv/N1VYSYWZXMJ2ZWFd+THyIiIiIiIiIiJ8TXJMQrwPdm9iXggJuA5/wWlYiIiIiIiIhIDj4lMJxzH5rZT0BzwIBOzrnVfo1MRERERERERMTL59tAvAkLJS1EREREREREpMj5fRyL5et/N3+/x9GY2V3OudGBjCGQVP+SW/+SXHdQ/QNZ/x9/6hyIt82lJK//wNf9usC9NcFQ/8BS/VX/klr/klx3UP39TYN4Bo+SsCruCnQAAab6l1wlue6g+qv+JVdJrjuo/qp/yVaS61+S6w6qv5QQJSGBISIiIiIiIiLFnBIYIiIiIiIiIhL0/D4GRhAo6feCqf4lV0muO6j+qn/JVZLrDqq/6l+yleT6l+S6g+rvV6EhAR3WUXIw51ygYxAREREREREJSkMWLD8pvzQPjG1Q7DIzuoVERERERERERILeSZXAMLOHzaxcoOMIBDN7KtAxSPAzs/fN7IZAx1GUzGxXIb1OZTO7rzBe6wRiiDWzJoGMoSQws45mdn6g48hkZv82s1/MbFwhv26smU0rzNc8GRSX/ayw4yzO51CFeQ5kZg3MrG1hvV5xUZzXf6YT2Q6Ky36fqbjFK1KYTqoEBvAwUKwb3xNQpAkMMysJ46eUeMVlPRdRnJWBgCYwgFjArycs5nGyHRuOV0cgaBIYeLa7ts65HpkTisu+WdQK6XOJxc/7WSGJpXDjfJjiew5VmOdADYBincD4h/vBwxTf9Z/pRLaDWIrHfp8pluIVb7EXGnJy/hVHxTRsMLPyZjbdzFaY2SozGwScBsw3s/neMq3NbLGZLTWzL8ysgnf6ejN70cyWeP/ODGRdvDHdambx3vp8dOSV8syryGYWbWaLzGy5t95XmdkLwKneaeO85R71zl9lZg97p9Uxs1/N7B3v9HFm1tLM/mdma83sMm+58mb2rpn9aGbLzOw67/Re3s9xKjCriD+ifJnZZDP72cwSzOwu77Tbzew3M1tgZmPMbKR3eoSZTfDW60czuzKw0R+dmQ3wrq/ZZvapmfUxszPMbKa3zt+a2bnesu+b2Rtm9r2Z/ZG57Xi/jI40s9VmNh2onuP1LzGzhd7X+sbMor3TF5jZ82a2EHjIz3U85jbp6/ZoZhXM7D0zW+ndlzrneJ/nvPvWD2YW6Z3W3sz+z/uac3JMH+x9vwXez/Lf3pd5ATjDu5+9VMifw5H7f57YzKwOcA/wiDeGqwrapr3TZ5un7XvbzDaYWTXvvILahl/M7L/AUmCAmb2aI747zWx4Ydb5KJ9Ffvv0LvO02T97P4/LcqyfDt4yZXOs/2VmFued3su8bYD3+TQzi83xurm2DfNc0eoAvOT9nM8oinoXxMzeAuoBU8ws3cxGm9ks4EPvevvWu56XemPP07PCPG1AL+/jNt597jugUwCqlC8/tAVzvZ/JyhzlfHmPOhyxnwXgs/in7cHR2rQPzGyWec5/OpnZMO9nM9PMSpunnct1DhXgOp/oOVCediTzdewobYmZnQIMAbp4X69LEX8Ofj8mmtkoM/vJ+9k8450W0PWfo/6FvR3kej3vNJ/2p6KvfVYdC3v/P9r5wM3m+R603DsvNFD1FjkexXYQT29D3MY5d6f3eSVgBXCpc26Ld+ecCFzjnNttZk8CZZxzQ8xsPTDGOfecmd0K3OScaxegqmBmF3hjvdIbe1VgODDNOfelt8wu51wFM3sMKOuNPRQo55zbmTnfW/YS4H3gCsCA/wNuBrYB64CGQALwI57P7HY8J+y3Oec6mtnzwGrn3MdmVhlY4l3mRuBZoL5zbqv/P5ljM7OqzrmtZnYqnvpcDfwP+BewE5gHrHDOPWBmnwD/dc59Z2a1gG+cc+cFLPijMLNLgXeAxnh+LWgp8DZwDXCPc26tmV0O/Mc519zM3gfKA12Ac4EpzrkzzawTcC/QBogEVgN3AF8BC4HrnHOp3pO0q51zvc1sAZ717/feBt6D8FG3SW/Mx9wezexFPPv4w97XruKc22ZmDujgnJtqZsOAHc65Z82sCrDdOefM7A7gPOfcY2Y2GGgNxAFhwBogCjgdzz55YSF/Bvnt/+4ose1yzr3sXTbfbdo8X9g3Oef+Y2ZtgK+BCKA2BbcNfwBNnHM/mFl5IB441zl30My+B+52zq0szLoX8HkcuU/HAFvw9ED42swm4dnWr8XTS+ID51wDb9t4oXPuNvMk9mYBZwNd8RwXHvC+/jTgZefcgqNsG++To/0NNO8x61LgAaA90NQ5t9c83b0PO+f2mdlZwKfOuUvNk6Dpk3lc824PPwGfAWuB5nj2u8/xHEMCdvzLVMhtQSk89drhPRf4ATgLz/bvyzFwMDn2s6J0gu3B0dq0lnjatPOBxUDnHPvTB865yZnbmXNuSxDU+R+fA3nL52lHnHNp3n3+WG1JL3K0GUWpiI6JmZ9NKDAX+LdzLj5Q6z+TH86F87yet95H208Cst9n8tP+X9D5QAQwDOjkPc7/F/jBOfdhUde7uHhu0ck5iOfTzYrfIJ7FuQvqSuBlbwM9zTn3rVmuz/8KPAek/3mnn4LnoJ3p0xz/XyWwmgNfZh40vA1sQWV/BN41s9LAZOfc8nzKNAUmOed2A5jZROAqYArwZ+aXEDNLAOZ6G7uVQB3v8q2BDmbWx/u8LFDL+3h2sCQvvP5tZtd7H9cEbgEWZsZoZl/g+RIDnhO483N8thXNLMw5t7MoA/ZRU+Ar59xeAPNcUSmLp7vgFznqUCbHMpOdc4eB1ebNvAPN8HypyQA2m9k87/RzgAuB2d7XCgUSc7zW54VfpQIda5usgW/bY0s8X1YBcM5t8z48AGRejf4ZaOV9XAP43Dw9T04B/swR03Tn3H5gv5ml4En++Et++/9FR4ktp3y3aTzbz/Xe15tpZpmfxdHahg3OuR+8y+z2bivtzOwXoHRRJC+8jtynz8KzDmd6p60E9ntPuHK2W02BEd74fzWzDWTv+wUpaNsIZlMy2wWgNDDSzBoAGRy7vufi2d/WApjZx8BdR1+kSBVWW2DA82bWDDiMJ/kY6eN7BNqJtAdHa9O+zrHPhJJ7f6pT+NU4LoV9DgT5tyNp+NaWBJq/j4k3madXSikgGs+5crwf6+Orwt4O8ryed/rR9pNA88f+X9D5QAvgEuBH7+d8KpBS+FUSKXzFNoHhnPvNPD0N2gL/MU+X2pwMT0PeraCXKOBxIFg+MRzCe4uPeVqWUwCcc4u8J2XXAh+Z2Uv5ZEuPlknbn+Px4RzPD5O9PRieqzNrcr2o54r/bp9qVAS8VxlbAo2dc3vM03NgDVBQr4oQb9m9BcwPJvmtwxA82fUGBSyTc93mXD6/7duABOdc4wJeqyjX87G2yQx82x7z248ADjqX1dUsg+ztfAQw3Dk3xbstDS4gppzL+EN+cR8ttpzy3aat4LO+o7UNR67zd/DcT/wr8N5Rlis0BezTZcm9DrO2EefcYcu+17ugumW1pV5lczwuaNsIZjnX0yNAMnAxnjru804/Wp0Dfbw7msJqC3rgubp4iffL6XqyPwNfjoGBdCLtwTHbNO8+c+T+FOh6F+o50FHaEfCtLQk0vx0Tzawu0Ado5O2N8T6524dA8se5cH7tna/7UyD4Y/8/2vnAB865fv883JIltNj1Uzh5FecxME4D9jjnPgZeJvuWgTBvkR+AK807voWZlTOznFenuuT4n7NnRiDMxZMRDwdP10dgPZ7MKMB1eK60YWa1gRTn3BhgLJ56Axz0ZqIBFgEdvXUujyfz+u1xxPMN8GDmlyAza/hPK+ZnlYBt3hOUc/H0uikHxJhZFe/JSOcc5Wfh6YINgPeqZbD6Dmhvnvv6K+A5SO8B/jSzGyFrfIuLj/E6i4CuZhbqzcrHeaevASLMrLH3tUqbp+tiMPJ1ezxy/VY5xutWAjZ5H/f0IY6c7Uthym//Lyi2I2MoaJv+DrjJO601kPlZ+Nw2OOf+D8+Vy+5k91jzt/z2aV8twvPFFW9bXwvPdr4eaGBmIWZWE7jMh9fy17oubJWARG/Pq1vwXFkH2ICnZ04Z89xe2cI7/VegrmWP61FQgj9Y+doWVMJznDxonrFQah/n+wRy/Z9Ie3C8bdqRAlXvwj4HOpF2BIJ//z+RY2JFPEmOdPP01LwmR/lA17uwt4P8Xg98358CwR/7f0HnA3OBG8yseuZ7eT9XkaBXbBMYwEXAEjNbDjyN576/0cDXZjbfOZcK9AI+NbN4PAmNc3MsX8bM/g/PIIWPFGXgR3LOJQDPAQvNbAWee/7G4PkivgTImVWPBZab2TI8X85f904fDcSb2Tjn3FI897kvwXOP+zvOuWXHEdJQPAeJeDNb5X0ejGYCpbzrdyiedbwJeB5PvefguVc03Vv+38Cl5hkcaTWeAZCCknPuRzzd+lfguR/yJzz16AHc7t1OEvAc0I9mEp573lcCo/CMe4Fz7gBwA/Ci97WWE7yjWfu6PT4LVDHPgF4ryE7WFGQwnttxvsUzxsJROefS8NyStsoKcRDPAvb/gmKbClxv2YOMFbRNPwO0NrOleE5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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'corr': step customer age gender merchant category \\\n", + " step 1.000000 0.091561 0.081676 0.010605 0.218892 0.057168 \n", + " customer 0.091561 1.000000 0.002931 0.032947 0.006908 0.035071 \n", + " age 0.081676 0.002931 1.000000 0.115579 -0.020316 0.032859 \n", + " gender 0.001423 0.032947 0.115579 1.000000 0.026731 0.003207 \n", + " merchant 0.218892 0.006908 -0.020316 0.026731 1.000000 0.449156 \n", + " category 0.016173 0.035071 0.032859 0.006763 0.449156 1.000000 \n", + " amount 0.099530 -0.000815 -0.011677 0.043971 -0.082459 0.805309 \n", + " fraud 0.067233 0.026313 -0.018114 0.105551 -0.150286 0.870595 \n", + " meramt 0.109209 0.001455 -0.009584 0.053934 -0.101626 0.992498 \n", + " catamt 0.107599 0.000476 -0.009397 0.050372 -0.090733 1.000000 \n", + " custamt 0.071864 -0.001731 -0.024820 0.093464 -0.135225 0.581235 \n", + " mercat 0.106171 -0.006412 -0.003669 0.026906 0.449156 1.000000 \n", + " custcat 0.099459 0.035071 -0.011782 0.060799 -0.082126 1.000000 \n", + " catage 0.098104 -0.012575 0.032859 0.042876 -0.050149 1.000000 \n", + " \n", + " amount fraud meramt catamt custamt mercat \\\n", + " step 0.099530 0.067233 0.109209 0.107599 0.071864 0.106171 \n", + " customer -0.000815 0.026313 0.001455 0.000476 -0.001731 -0.006412 \n", + " age -0.011677 -0.018114 -0.009584 -0.009397 -0.024820 -0.003669 \n", + " gender 0.043971 0.105551 0.053934 0.050372 0.093464 0.026906 \n", + " merchant -0.082459 -0.150286 -0.101626 -0.090733 -0.135225 0.449156 \n", + " category 0.805309 0.870595 0.992498 1.000000 0.581235 1.000000 \n", + " amount 1.000000 0.450215 0.811395 0.805309 0.470454 -0.162678 \n", + " fraud 0.450215 1.000000 0.529481 0.498312 0.600583 -0.231696 \n", + " meramt 0.811395 0.529481 1.000000 0.992498 0.472516 -0.200491 \n", + " catamt 0.805309 0.498312 0.992498 1.000000 0.453809 -0.202007 \n", + " custamt 0.470454 0.600583 0.472516 0.453809 1.000000 -0.157477 \n", + " mercat -0.162678 -0.231696 -0.200491 -0.202007 -0.157477 1.000000 \n", + " custcat 0.010933 0.579601 0.013475 0.013577 0.291554 -0.182845 \n", + " catage -0.230294 -0.428122 -0.283825 -0.285970 -0.286136 -0.111651 \n", + " \n", + " custcat catage \n", + " step 0.099459 0.098104 \n", + " customer 0.035071 -0.012575 \n", + " age -0.011782 0.032859 \n", + " gender 0.060799 0.042876 \n", + " merchant -0.082126 -0.050149 \n", + " category 1.000000 1.000000 \n", + " amount 0.010933 -0.230294 \n", + " fraud 0.579601 -0.428122 \n", + " meramt 0.013475 -0.283825 \n", + " catamt 0.013577 -0.285970 \n", + " custamt 0.291554 -0.286136 \n", + " mercat -0.182845 -0.111651 \n", + " custcat 1.000000 -0.358553 \n", + " catage -0.358553 1.000000 ,\n", + " 'ax': }" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from dython.nominal import associations\n", + "associations(data, theil_u=True, figsize=(20, 20))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see our features have a nice correlation with the target" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "l = ['age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", + "for i in l:\n", + " plt.figure(figsize=(8, 8))\n", + " sns.distplot(data[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that except age all the features are skewed, of which catage and mercat are negatively skewed and others are positively skewed" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It can be seen that the data has outliers, however the number of outliers is significant. Thus we wont remove them" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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IAQgAEDl79kjWht8Bktx5QHSAkBCNjdLOnYkNQCUlB0YiApBEAAIARFDwfi8Re0l2hw4QEmbLFndM1BI4yX0KUFvrPhEAIIkABACIoGTsARQIOkC8v0SfBSOwE90Bam2V9u5N3GMCaY4ABACInCAAJWMJ3JAhUksLp1kgASor3TGRASj4S8AyOOAtBCAAQOTs2eOm/xYUhP9c7AWEhAk6QIleAicRgIBOCEAAgMiprXXL3zKS8L9cEIA4Dwh9VlXlUnthYeIeMwhAjMIG3kIAAgBEzu7dyVn+JrklcBIdICRAokdgS+6TAGPoAAGdEIAAAJGzZ0/yAhAdICRMVVXiA1BmpusoEYCAtxCAAACRU1ubvAA0YIDUvz8dICRAVVViz/8JFBezBA7ohAAEAIiU+nq3n2SyApAxrgtEBwh90t7u9gFKdAdIOrAXEABJBCAAQMQEe0kmKwBJ7jwgOkDok+3b3X49YQSgkhICENAJAQgAECnBJOFkBiA6QOizMEZgB4qLpYYGqbk58Y8NpCECEAAgUoIOUFFR8p6TDhD6LIxNUAOMwgYOQgACAERK0IlJdgeotlbavz95z4mICTpAYS2Bk1gGB3QgAAEAIqW6WsrJkXJzk/ecwV5A27Yl7zkRMVVVUlaWVFGR+MemAwQchAAEAIiU6mq37YkxyXvOYC8glsHhmFVVuSSdmZn4xw4CEB0gQBIBCAAQMdXVyT3/R2IzVCRAZWU4y98kKS/PXQhAgCQCEAAgYoIOUDIFS+DoAOGYhbUJaqCkhCVwQAcCEAAgUnwEoPJyt+SODhCOWVVVeB0gic1QgU4IQACAyGhqknbtSv4SuODcdTpAOCZ1dVJ9PQEISBICEAAgMrZvd8dkByCJzVDRB2GOwA4UF7ug1dYW3nMAaYIABACIjKADk+wlcBKboaIPggAU9jlA7e0uBAExRwACAERG0IHxEYDoAOGYVVa6Y9gdIEnasye85wDSBAEIABAZQQfGxxK4IUPcRqjt7cl/bqS5oAM0dGh4zxH8peA8IIAABACIjiAADRiQ/OcePFhqbZV27kz+cyPNVVVJZWVSv37hPQcdIOAtBCAAQGRUV7v3kVlZyX9u9gLCMQt7BLbkPhUwhgAEiAAEAIiQ6mrXifEheF7OA0KvVVaGH4AyM93JcSyBAwhAAIDo8BmA6ADhmFVVhTsBLlBURAcIEAEIABAhdICQdpqb3QZWYXeAJAIQ0IEABACIBGtdAAo6MclWUCDl59MBQi9t3epevMkIQMXFLIEDFHIAMsZcYoxZZYxZY4y5+Qj3OccY85oxZpkx5tkw6wEARFd9vbR/v78OkOTCFx0g9MqmTe44YkT4z1VU5P6itLWF/1xACgstABljMiXdKuntkqZIus4YM+WQ+xRL+qWkK6y1UyVdFVY9AIBoCzovPgPQ4MF0gNBLGze646hR4T9XsBcQy+AQc2F2gE6TtMZau85a2yzpr5KuPOQ+10u6x1q7SZKstdtDrAcAEGFB58V3B4gAhF5JZgBiLyBAUrgBaJikzZ2+r+y4rrMJkkqMMc8YY142xtwQYj0AgAhLlQ4QS+DQKxs3ShUV4W6CGiAAAZKkMLeKM11cZ7t4/lMknS+pn6QXjTELrLVvHvRAxsyRNEeSRo4cGUKpAIB0lwoBaMgQqa5OamiQ+vf3VwfSyMaNyen+SAeWwDEIATEXZgeoUlLnM/qGS9rSxX0etdbus9bukDRP0omHPpC1dq61doa1dkZ5eXloBQMA0ld1tZSdLZWU+KshCF8sg0OPJTMADRggGUMAQuyFGYAWSRpvjBljjMmRdK2k+w+5zz8lvc0Yk2WM6S/pdEkrQqwJABBR1dXSoEFShscNHtgMFb1irZsCl6wAlJHBXkCAQlwCZ61tNcZ8QtJjkjIl3WmtXWaMuanj9tustSuMMY9KWiKpXdId1to3wqoJABBdPjdBDbAZKnqlpsbNbk9WAJIIQIDCPQdI1tqHJT18yHW3HfL9DyX9MMw6AADRV12dnK1UjoYOEHolmRPgAkVF0q5dyXs+IAV5XCgAAEDipEIHaOBAt8qIDhB6xEcAKi7mHCDEHgEIAJD22tqk7dv9B6DMTDfRmA4QesRXB2jvXqm1NXnPCaQYAhAAIO3V1Ejt7f4DkOSWwdEBQo9s2CAVFh7YnycZgueqq0vecwIpJtRzgAAASAYfewDNndv19S0t0htvHH77nDnh14Q0k8wR2AH2AgLoAAEA0l8qbIIaYMgWeowABHhBAAIApL1UCkCFhVJ9vVuSBxzVxo3S6NHJfc5gCRwpHTFGAAIApL0gAA0a5LcOyX3A3t7uzjMHjmjPHndJdgeooMCNKqQDhBgjAAEA0l51tTRggJSf77sS1wGS+IAd3fAxAU5y4SdoUwIxRQACAKS96uoDm5D6FpxiQQDCUfkKQJILQLxAEWMEIABA2kuFTVADQQBiyjCOigAEeEMAAgCkvVQKQMESOAIQjmrdOqlfP7dzbrIVFfECRawRgAAAaW/r1tQJQLm5Ul4eH7CjG6tWSRMnSsYk/7kLC10AamtL/nMDKYCNUAEAaa2hwb2XS5UAJLHCCN2YO1dauNCNwD7SjrphKiqSrJV27EiN0YlAktEBAgCktW3b3DGVAhCboeKoWlqknTv9hY/gRLVgfjwQMwQgAEBaS6VNUAPBCiOgSzU1rgPj60UbnKhGAEJMEYAAAGktFQMQHSAcle8XbdAB2rrVz/MDnhGAAABpzfd7ya4UFUlNTVJjo+9KkJKCF62PCXASHSDEHgEIAJDWqqvd5va+3kt2hb2AcFTbtknFxW5coA/BqEICEGKKAAQASGvV1VJ5uZSZ6buSA9gLCEe1bZv/6WuFhSyBQ2wRgAAAaS2VNkENBB0gzgPCYaxNjRdtUREdIMQWAQgAkNZSaRPUQNABIgDhMNu3S/v3+3/RFhYSgBBbBCAAQFpLhQ/TD1VQ4M5LIgDhMKtWuaPvJXBFRSyBQ2wRgAAAaStVVhMdKiODvYBwBKkUgOrrpX37/NYBeEAAAgCkrd27pZaW1AtAkgtAdIBwmJUrpexsqbTUbx3BOs1t2/zWAXhAAAIApK1U3AMowGao6NKqVa77k+H5LRh7ASHGevS3zxhztzHmMmMMgQkAkDJSOQCVlEi1tb6rQMpZscL/8jfpwKhCzgNCDPU00PxK0vWSVhtjvmeMmRRiTQAA9EgQgIYM8VtHV4qKpL173RI9QJK0c6e0bp00cqTvSg4EIDpAiKEeBSBr7ZPW2vdJOlnSBklPGGPmG2M+ZIzJDrNAAACOJJU7QMXF7sgyOLxl0SJ3HDPGbx3SgVGFBCDEUI+XtBljyiTdKOmjkl6VdItcIHoilMoAAOhGdbWUl3fgdIZUEgQglsHhLQsXSsakRgcoI8MtxWMJHGIoqyd3MsbcI2mSpD9IutxaG/xt+ZsxZnFYxQEAcDTBCGxjfFdyODpAOMzChdLkyVK/fr4rcQYPpgOEWOpRAJJ0h7X24c5XGGNyrbVN1toZIdQFAEC3tm5NzeVv0oEAtHu31zKQKqx1Aeiyy3xXcsDgwXSAEEs9XQL3nS6uezGRhQAA0FupuAlqID9fysqiA4QOmzZJNTXSaaf5ruSAwYPZBwixdNQOkDFmsKRhkvoZY06SFCwyKJTUP+TaAAA4qupq6ayzfFfRNWNcF4hzgCDJdX8kF4BeftlvLYFBg6Tt2113KhXXkQIh6W4J3MVygw+GS/pJp+vrJX0lpJoAAOhWS4u0Y0fqdoAkN2mYAARJLgDl5krTpqVWAGppces0S0t9VwMkzVEDkLX2d5J+Z4x5j7X27iTVBABAt7Zvd8dUDkDFxdLmzb6rQEpYuFA66SQpJ8d3JQcEG7Ju20YAQqx0twTu/dbaP0oabYz53KG3W2t/0sUvAwAgdKm8CWqguFhautStMEKMtbZKixdLH/mI70oO1jkATZ7stxYgibpbApffcSwIuxAAAHojlTdBDRQXS83NUmOj70rg1dKlUkNDag1AkA4OQECMdLcE7vaO438npxwAAHomXQKQxCjs2HvgATdk4MILfVdyMAIQYqqnG6H+QG4U9n5Jj0o6UdJnOpbHAQCQdEEACt7DpSI2Q42guXO7v8+cOQd/f++90plnpt6LtbRUyswkACF2eroP0EXW2jpJ75BUKWmCpC+EVhUAAN3YulUqKXGDtVJVEICYBBdjGzZIr70mvfOdngvpQkaGVFFBAELs9DQAZXccL5X0F2vtrpDqAQCgR1J5E9QAAQi67z53TMUAJLmuFAEIMdOjJXCSHjDGrJRbAvcfxphySZzSCQDwJh0CUE6O1L8/ASjW7r1XOv54adw435V0jQCEGOpRB8hae7OkmZJmWGtbJO2TdGWYhQEAcDTpEIAkNkONtZoa6fnnpXe9y3clR0YAQgz1tAMkSZPl9gPq/Gt+n+B6AADokXQJQMXFBKDYeuABqb09PQKQtW5SHRADPZ0C9wdJYyW9Jqmt42orAhAAIAkOHbzV2Cjt2ydt3NizoVw+FRcfmFiHGLFW+sUvpPHjpenTfVdzZIMGSU1NUl2da1cCMdDTDtAMSVOsZS9rAIB/wVjpwkK/dfREcbGrt63NTRxGTDz0kPTqq9Kdd6Z2Z6XzXkAEIMRET6fAvSEpDRYaAADioK7OHdPh/VpRkVsFtX2770qQNNZK3/62NHq09P73+67m6NgMFTHU0w7QQEnLjTELJTUFV1prrwilKgAAjiLoAKVDACopccctW6QhQ/zWgiR54glp4ULp9tul7Ozu7+8TAQgx1NMA9M0wiwAAoDfSKQAFewFVVUmnnOK1FCRDe7v0zW9Kw4dLH/yg72q6RwBCDPUoAFlrnzXGjJI03lr7pDGmvyRWMgMAvKirc+fT5Of7rqR7QUjbssVvHUiSZ5+VXnzRnfuTm+u7mu4NHChlZBCAECs9OgfIGPNvku6SdHvHVcMk3RdSTQAAHNWePW4AQiqfWx4I6qyq8l0JQldT4zY+vfhi6cYbfVfTM5mZLgQRgBAjPR2C8HFJsyTVSZK1drWkirCKAgDgaPbsSY/lb5J7f1lYSAco8trbpd//3qXdX/86PdJ5gM1QETM9DUBN1trm4JuOzVAZiQ0A8CLdtiwpLqYDFHnz5klvvilddZU0YoTvanqHAISY6WkAetYY8xVJ/YwxF0r6h6QHwisLAIAjS6cOkOQCEB2gCNuxQ7rnHmnKFGnWLN/V9B4BCDHT0wB0s6QaSUsl/bukhyV9NayiAAA4krY2ae/e9NgENUAHKMLa26Xf/c4tefvAB9Jr6VuAAISY6ekUuHZjzH2S7rPW1oRbEgAAR1ZX5/aZTLcO0K5dUmOjlJfnuxok1PPPu6VvH/iAVFrqu5pjM2iQ1NDgPlkoKPBdDRC6o3aAjPNNY8wOSSslrTLG1Bhjvp6c8gAAOFiwB1C6dYAkqbLSaxlItJYW6aGHpHHj0nPpW4C9gBAz3S2B+4zc9LdTrbVl1tpSSadLmmWM+WzYxQEAcKi6OndMpw5Q0BjYvNlvHUiwBQuk2lrpssvSc+lbgACEmOkuAN0g6Tpr7frgCmvtOknv77gNAICkCjpA6RSASkrckQAUIW1t0mOPSaNGSZMn+66mbwhAiJnuAlC2tXbHoVd2nAeUHU5JAAAcWTougQsC0KZNfutAAr38stv49O1vT+/uj0QAQux0F4Caj/E2AABCUVcn5edLWT0a45MacnKkigoCUGRY67o/Q4ZIJ57ou5q+Ky93RwIQYqK7/z5ONMbUdXG9kcQcGwBA0qXbHkCBkSMJQJGxZYubaHH99VJGT3cUSWHZ2VJZGQEIsXHUAGStzUxWIQAA9EQ6B6AVK3xXgYRYvNgtezvpJN+VJA57ASFGIvCxBQAgTurq0jcAbdrkVk8hjVnrzv+ZODG9TkTrDgEIMUIAAgCkDWtdBygd33eOHCnt2yft3u27EvRJZaULCqec4ruSxCIAIUbS6BRSAEDcNTRIra3p2wGS3CjsYF8gpKGXX3bn/URh+dvcuQe+3r7dhbvO10nSnDnJrQlIAjpAAIC0kY57AAVGjHBHBiGksc7L3wYM8F1NYhUWSo2NUjNDfhF9BCAAQNpIxz2AAkEHiACUxpYscZ2SGTN8V5J4wV+quq6G/wLRQgACAKSN4L1ZOnaAKircfkAEoDT22GPuOG2a3zrCEHS06uv91gEkAQEIAJA20nkJXEaGWwZHAEpjTz/tNj9Nxxdgd+gAIUYIQACAtFFX5/ZszEvTrbjZDDWNNTdLzz3nzv+JIgIQYoQABABIG8EmqMb4ruTYEIDS2KJFbo75pEm+KwlHsASOAIQYIAABANJGEIDS1ciR0pYtbpQ30sy//uWS94QJvisJR3a21K8fAQixQAACAKSNurr0DkAjRkjt7S4EIc08/bQ0fbqUn++7kvAUFjIEAbFAAAIApI09e9JzBHaAUdhpav9+af586bzzfFcSrgED6AAhFrJ8FwAAQE80N0sNDendASIApakXX5SamlwAqqzs/v5z54ZfUxgKC6WqKt9VAKGjAwQASAvpvAdQYMQIdyQApZl//UvKzJTe9jbflYSLJXCICQIQACAtpPMeQIGCAqm0lACUdl54QTr55AOT0qKqsNC1WVtafFcChIoABABIC0EHKJ3PAZLcMrjNm31XgR5rbZUWLpRmzvRdSfiCgEcXCBEX6jlAxphLJN0iKVPSHdba7x3hfqdKWiDpGmvtXWHWBABIT1HoAEkuAG3Y4LsKHNGh5+9s3uy6Ivv2pe+5PT3VeTPU0lK/tQAhCq0DZIzJlHSrpLdLmiLpOmPMlCPc7/uSHgurFgBA+qutlTIy0n8VEpuhppl169zxuOP81pEMQQCiA4SIC3MJ3GmS1lhr11lrmyX9VdKVXdzvk5LulrQ9xFoAAGmutta9P8tI88XbI0a43wvThtPEunXuhVdW5ruS8HXuAAERFuZ/I8MkdV7lXNlx3VuMMcMkvUvSbSHWAQCIgNpaqbjYdxV9F4zC5jygNLF+vTRmjGSM70rCRwBCTIQZgLr6l8Ie8v3PJH3JWtt21AcyZo4xZrExZnFNTU2i6gMApJGoBSCWwaWBvXulbdvisfxNknJypNxcAhAiL8wAVClpRKfvh0vacsh9Zkj6qzFmg6T3SvqlMeadhz6QtXautXaGtXZGeXl5SOUCAFIZAQhJt369O8YlAEnsBYRYCHMK3CJJ440xYyRVSbpW0vWd72CtHRN8bYz5f5IetNbeF2JNAIA01NQk7d8vlZT4rqTvhgyRsrOZBJcW1q93S99GjfJdSfIUFtIBQuSFFoCsta3GmE/ITXfLlHSntXaZMeamjts57wcA0CO1te4YhQ5QZqZ7Px00F5DC1q2Thg93y8LiYsAAt+wPiLBQ9wGy1j4s6eFDrusy+FhrbwyzFgBA+opSAJLciqq1a31XgaNqb3cp9fTTfVeSXIWF0urVvqsAQpXmw0QBAHGwe7c7RikABdvLIEVVV0uNjW4CXJwUFrpNX9uOOp8KSGsEIABAyotiB2jXrgO/L6SgOG2A2hmboSIGCEAAgJRXWyvl5blLFATvqTkPKIWtWyfl50sVFb4rSa4BA9yRQQiIMAIQACDl1dZGYwJcYOxYd2QZXAqL0waonbEZKmKAAAQASHm1tVJRke8qEic4rYQAlKL275e2bo3f8jeJJXCIBQIQACDlRWUT1EBRkVRWRgBKWevXS9bGOwDRAUKEEYAAACmtvV3asydaAUhiElxKCzZAHT3adyXJl5vrduolACHCCEAAgJS2fbsLQQQgJM26ddKQIVK/fr4rST5jXBeIJXCIMAIQACClVVW5Y5SGIEguAG3YwHYrKcdaF4DiuPwtUFhIBwiRRgACAKS0IABFsQPU2ipVVvquBAfZvl1qaIjfBqid0QFCxBGAAAApLcoBSGIZXMpZs8Yd49wBGjCADhAijQAEAEhpVVVSRsaB4VRREby/XrvWbx04xOrVUkGBOwcoroIOUHu770qAUGT5LgAAgKOpqnLvxzIi9pHd8OFSVhYdoISaO/fot8+Z0/1jvPmmNH58/DZA7ayw0J0LtXev70qAUETsvxMAQNRUVUVv+Zvkws+oUQSglLJpk7RzpwtAccZmqIg4AhAAIKVFNQBJjMJOOfPmueOECX7r8G3AAHfkPCBEFAEIAJDSCEBImmeflfr3l4YN812JX0EHiACEiCIAAQBS1r590p490dsDKDB2rFtxtWeP70ogyQWgsWOjd8JZbxGAEHEx/xsOAEhlwQjsoiK/dYQlmAS3fr3fOiBp61Y3AS7uy98kqV8/d5IaAQgRRQACAKSsqO4BFGAvoBTC+T8HGOPOA2IIAiKKAAQASFlBAIrqEjgCUAp55hm3/8+IEb4rSQ2FhXSAEFnsAwQASFlR6gAdaYua/HzpwQe73ui1J9vWIAHa26UHHpDOP1/KzPRdTWooLJRqa31XAYSCDhAAIGVVVbmVOHl5visJz8CBUk2N7ypibuFC92J7z3t8V5I66AAhwghAAICUVVUV/YnE5eUEIO/uuUfKzpYuv9x3JamjqMgFoLY235UACUcAAgCkrC1boh+ABg2SduyQWlp8VxJT1kp33+2Wv0VhrWWiFBe7P5vt231XAiQcAQgAkLI2bYr+OemDBrn3mXSBPHn9dTeFguVvBwtmz2/d6rcOIAQEIABASmpudu+9Ro3yXUm4Bg92x+pqv3XE1t13u41Pr7zSdyWpJQhAW7b4rQMIAQEIAJCSNm92nZGoB6BBg9xx2za/dcRSsPxt9mx3MhYOoAOECCMAAQBS0saN7hj1AJSX5063oAPkwSOPSCtWSO97n+9KUg8dIEQYAQgAkJLiEoAk1wWiA5Rk7e3SV77idqO94Qbf1aSezEw3g54OECKIjVABAClp40bJGGn4cN+VhG/wYGnRIrciyxjf1cTEP/7hBiD88Y9STo7valJTUREdIEQSHSAAQEratMkFg9xc35WEb9AgqaFBqq/3XUlMtLRIX/uadPzx0rXX+q4mdRUV0QFCJNEBAgCkpI0b47H8TTp4Elxhod9aIq+5WZozR1q9WrrvPrfUC10rLpbWr/ddBZBwdIAAACkpTgGISXBJYK0bLXjhhdLvfid94xvSFVf4riq1FRa6F2Vbm+9KgISiAwQASDnt7e69alz2piwtlbKzmQSXEO3tbv1ksMFpa6t7A19TI910k1tT+Ze/sPStJ4qLD/zZBW1KIAIIQACAlFNd7VYqxaUDlJHBJLiE2LNH+tWv3LItY6SRI13gyc6Wpk+XrrrKdYAmT/ZdaXrovBcQAQgRQgACAKScOI3ADgwa5LpeOIK5c49+e1WV9ItfSHv3un19Tj5ZKig4+D5z5oRXXxQVF7vj1q3SSSd5LQVIJAIQACDlxDUAvfKKG1CWne27mjRTUyP98IdunPV//me8XjhhYjNURBRDEAAAKSeOAWjwYHeefk2N70rSTHu79Nvfuj+8L34xXi+asAUjCRmFjYghAAEAUs7GjVJJiduIPi6YBHeMHn9cWrtWuu46aeBA39VES1aW+zOlA4SIIQABAFJOnEZgB4IAxCS4Xqiqku6/353vc/rpvquJpqFD6QAhcghAAICUs2mTG+AVJ/36uVMu6AD1wl13SXl5buiBMb6riaYhQ+gAIXIIQACAlGJtPDtAkjsPiA5QD735prR8uXTJJYdPe0Pi0AFCBBGAAAAppbZWqq+PZwAK9gKy1nclKc5a6b773Jjmc87xXEzEDRniUnl7u+9KgIQhAAEAUkocJ8AFBg2SGhpcAMRRvPGGG3xw6aVu9DXCM3So1Noq7djhuxIgYQhAAICUEucANGSIO7Li6CisdYMPBg6UZs3yXU30BS9KzgNChBCAAAApJc4BaPhwd6yq8ltHSlu1yk3JuOQSN6YZ4QpelJWVfusAEogABABIKRs3uolo5eW+K0m+wkK39xHvNY/i8cfdH9QZZ/iuJB6CcYybNvmtA0ggAhAAIKVs3Ojec8VxqrEx0rBhBKAjqqyUli2Tzj1Xys72XU08VFS486wIQIgQAhAAIKXEdQR2YNgwd7oFQ7e68MQTUm6udPbZviuJj4wMtwxu82bflQAJQwACAKSUuAegESOklhZp+3bflaSYXbukhQuls86S8vN9VxMvI0fSAUKkEIAAAClj/36ppibeAWjYMHdkGdwhnnrKHc8/328dcUQAQsQQgAAAKSN4jxWcdx1HQ4a4VUcEoE5qa6XnnpNmzJDKynxXEz8jR7rRhK2tvisBEoIABABIGatXu+PYsX7r8Ck7Wxo8mFHYB7ntNqmpSbroIt+VxNPIkVJbGxtUITIIQACAlBEEoPHj/dbhG5PgOmlqkm65RZoyxZ0gheQL/twZhICIIAABAFLG6tVSUZE0cKDvSvwaPtyd819b67uSFPDHP0rV1XR/fGIvIEQMAQgAkDJWr3bdnzjuAdTZ8OHuuHSp3zq8a2+XfvhD6aSTpEmTfFcTX0EHiACEiCAAAQBSxurV0oQJvqvwL5gE9/rrfuvw7sEHpVWrpC98gVTs04ABUkkJAQiRQQACAKSExkb3/iru5/9IUnGx2+pmyRLflXj2gx+4mehXXeW7EowYwTlAiIws3wUAACBJ69ZJ1hKAJNfsGD485h2g+fOlF15wAxCyeLviHXsBIULoAAEAUgIT4A42fLj0xhtu+nAs/eAHUmmp9JGP+K4EEgEIkUIAAgCkBALQwYYNkxoaXGcsdl59VfrnP6VPftKtBYR/I0e60YR79/quBOgzAhAAICWsXi2VlblzrXFgElwsl8F94xvuRKjPftZ3JQgEo7A5DwgRQAACAKSEYAQ2nKFDpczMGAaghQulBx6Q/vM/3aZQSA1shooIIQABAFICAehg2dnS1KkuD8TKN77hWoGf+pTvStAZm6EiQghAAADvGhqkykoC0KFmzpReesntBxoL8+dLjz4qffGLbu8ZpI6hQ6WMDGnjRt+VAH1GAAIAeLdmjTsSgA52xhnSnj3SypW+K0mSr39dqqiQPv5x35XgUFlZbhnc+vW+KwH6jAAEAPCOCXBdmznTHRcs8FtHUjz7rPTUU9LNNzP5LVWNH3/g0wogjRGAAADeEYC6Nn68m4r34ou+KwmZta77M2SIdNNNvqvBkYwbd+AvK5DG2FoZAODd6tVu5VNhoe9KUktGhlsGF4kO0Ny5R75txQpp3jzp5z+X+vVLXk3onfHj3V5Au3a5TWqBNEUHCADgHRPgjuyMM6Rly6S6Ot+VhMRa6f773cZH//ZvvqvB0QR/SVkGhzRHBwgA4N3q1dIll/iuIjWdcYbLCAsXShdc4LuaECxbJq1bJ912m5SbG+5zHa0Lhe6NG+eOq1dLp53mtxagD+gAAQC8qq+XqqvpAB3J6adLxkRkGdyhgu5PWZn0oQ/5rgbdOe44ty6T84CQ5ghAAACvGIF9dEVF0uTJER2EsGSJ21fmssuknBzf1aA7ubluQ1QCENIcS+AAAF4xAa57M2dK997rGibG+K4mQayVHnhAKi936/xYnpYexo3jHCCkPTpAAACvggAUnF6Aw51xhhu8FakP3pculTZvli69VMrM9F0Nemr8+Ii9EBFHBCAAgFfLlrkN5gsKfFeSus44wx0jcx6QtdJDD7lzf04/3Xc16I3x46Xdu6WdO31XAhwzAhAAwKslS6QTT/RdRWqbMsXtkRSZ84BWrJA2bHCj/+j+pJegVcsyOKQxAhAAwJumJmnlSumEE3xXktoyMtzU4cgEoIcekkpK3MlNSC/ByXosg0MaIwABALxZsUJqayMA9cTb3ua6ZTt2+K6kj9ascZeLLpKys31Xg94aM4ZR2Eh7oQYgY8wlxphVxpg1xpibu7j9fcaYJR2X+cYYFkEAQIwsWeKOBKDuXXSRO3XmySd9V9JHTzwh5edLs2b5rgTHglHYiIDQxmAbYzIl3SrpQkmVkhYZY+631i7vdLf1ks621u42xrxd0lxJnA0JABHWedrxXXdJWVnSM89Izz3nraS0cOqpbtXYY49J117ru5pjVFMjvf66O/cnN9d3NThW48dzDhDSWpgdoNMkrbHWrrPWNkv6q6QrO9/BWjvfWru749sFkoaHWA8AIMVUVkpDh3IefE9kZkoXXCA9/rjrBKWlJ590y6fOPdd3JeiLCROkVavS+IWIuAszAA2TtLnT95Ud1x3JRyQ9EmI9AIAUU1UlDTva/ww4yMUXS1u2SG+84buSY7BvnzR/vpvmUFTkuxr0xbRpUl2dtGmT70qAYxJmAOpqr+ouPyowxpwrF4C+dITb5xhjFhtjFtfU1CSwRACAL3V17jKc3n+PXXyxOz72mN86jsnzz0vNzdL55/uuBH0VnLT3+ut+6wCOUZgBqFLSiE7fD5e05dA7GWNOkHSHpCuttV3uqmWtnWutnWGtnVFeXh5KsQCA5Kqqckc6QD03fLjbE+jxx31X0kvt7dKzz7qlUyNGdH9/pLZp09yRAIQ0FWYAWiRpvDFmjDEmR9K1ku7vfAdjzEhJ90j6gLX2zRBrAQCkmCAA0QHqnYsvlubNkxoafFfSC48/Lu3cKc2e7bsSJEJBgTR27IExjkCaCS0AWWtbJX1C0mOSVkj6u7V2mTHmJmPMTR13+7qkMkm/NMa8ZoxZHFY9AIDUUlkpFRZKAwb4riS9XHyx20B23jzflfTCbbe5H/RJJ/muBIly4ol0gJC2QhuDLUnW2oclPXzIdbd1+vqjkj4aZg0AgNRUVUX351jMni3l5bnzgC65xHc1PbB5s/TAA24jo6xQ33YgmU48Ubr3XjfcIj/fdzVAr4S6ESoAAF1pa3PTzDj/p/f69XMhKG0GIdxxhxuX/La3+a4EiXTCCe7nmpYjCRF3BCAAQNJt3y61ttIBOlYXXyytWJEGU4hbWqRf/9q1qgYO9F0NEunEE92R84CQhuhFAwCSrrLSHekAHd3cuV1fv3evO37hCwdPlZ4zJ/yaeuXBB6WtW6Xbb3dHRMeoUe68Ls4DQhqiAwQASLqqKikjQxo82Hcl6WnwYGnkSOmll3xX0o1f/cqNvb70Ut+VINEyMtwyOAIQ0hAdIABA0lVWujfx2dm+K0lfp58u/eMfUnV1igbJNWukJ56QvvUtKTPTdzU4VkdqQ0puqMWrr7pzgYxJXk1AH9EBAgAkXWUly9/66tRT3XvOlO0CzZ3rgs9HPuK7EoRl+HCprk7auNF3JUCvEIAAAEm1e7e7jBnju5L0VlQkTZ7sApC1vqs5RFOTdOed0pVXSkOH+q4GYRkxwh1fftlvHUAvEYAAAEm1bp07jh3rt44oOP10aedOae1a35Uc4q67XGEf+5jvShCmESPcplQvvOC7EqBXCEAAgKRau9ad+xN8eIxjN326+7NcuNB3JYe47TZp3DjpvPN8V4IwZWW5tZgEIKQZAhAAIKnWrpVGj+a8+ETIy3MhaPFit69SSnjjDen556V//3c3KQzRNmuW9MorUkOD70qAHuNfJgBA0jQ0uM07Wf6WOKefLu3bJy1b5ruSDrffLuXmSjfe6LsSJMOsWS59L1rkuxKgxwhAAICkWbxYam+XjjvOdyXRMWWK24/yued8VyK3Q+vvfy9ddZU0cKDvapAMZ57pjiyDQxohAAEAkmb+fHekA5Q4mZnSOedIS5dKS5Z4Luavf3VjkW+6yXMhSJrSUjeOkACENEIAAgAkzfz50qBBUkGB70qi5dxz3flA3/2uxyKslX7+c2natANdAcTDrFnuL3d7u+9KgB4hAAEAksJa9x6J7k/i5edLZ58t/f3v0urVnop45hnXgvr0p90OrYiPWbOk2lppxQrflQA9QgACACTF6tVuaxgCUDguuEDKyZG+9z1PBdxyi1RWJl1/vacC4M2sWe7IMjikCQIQACApgvN/GIAQjsJC6aMfdTMINm1K8pOvWyfdf78796dfvyQ/ObwbN06qqJDmzfNdCdAjWb4LAADEw/z5UnGxNHiw70qi6wtfcHuQ/uhH0v/9XxKf+Oc/d9MY/uM/Ev7Q7e3S3qZs1e7PUaaxqijcr+xMm/DnwTGaO9cdR492Ifi22w7e/2nOHC9lAUdDAAIAJMX8+e7cePbGDM/IkdINN7j3pB//uDRxYhKedPdu6Te/caOvhw496l2tlTbsHKClVaXasTdPe/bnqLYhxx3356i2IbfT1zmq3Z+ruv3ZarcHv2jK8hs1qqxeV5+yTjfMfFNDivaH+TtET0ydKi1cKFVWuhcikMIIQACA0NXWuo06r7vOdyXR953vSPfdJ33wg9Lzz0tZYf9P//OfS/X10s03d3nzpk1uOvZjd16mVzYPVG1D7mH3KcxrVnH/JhX3b1ZRXrP6t+9TReEuFQxsVkF2kwpymlWQ3aw2m6Fdjf20e38/ra0t0833nq7/uu9Uvf34zfrGO17WjNE7Qv7N4oimTHHHZcsIQEh5BCAAQOief94dzzzT45SymBgyRLr1Vhc2f/SjI+aSYxaseJKk7MZ6Xff9n6n6xCv0+IITpAXu+pYW6aWXpBdflNascddNH5Grq09Zp5NH7tCJw3dqcGGDivs3a0BeizIzDl7S1tNTSTbXFemRdRP0yOqJOuN779S/n/SSrpq0VBndDKGbPbuHv1n0XGGhNGKEC0Bvf7vvaoCjIgABAEL3yCNuVDMBKDmuuUa65x7p61+XLrvMbc0ThinP/kp5Dbv16qVflSQ1NkrPPis99ZS0Z48LY1deKZ16qvS2Ffe89euaK6VNcpe+GFG4R3OmL9K1k5fo+wtm65evzNQr1cP05ZnPqDivsY+Pjl6bOlV6/HFp/36GYSClsRIbABAqa6WHH5bOP1/KPXz1E0JgjPTLX0olJe6coObmxD9HZnODpj3xY22ecrE2DTpVDz0kffnLLngNHSp95jPSN74hXXqpVF6e+OfvrDC3Sd+Z/YQ+M+N5vVw9TP/+6Lu0dS+77Sbd1KluasWqVb4rAY6KDhAAIFSrVkkbNkhf+pLvSuJl4EC3XO2d73Rb8/zpT4kNoNOeukX967frO2Vf1a1fbFRdc57OGr5B75/9qiaX1Ug1cpckMUZ618TlmjSwRv/5r0v12afeoVsueECD8vclr4i4O+449yJbtkyaPt13NcAR0QECAITqkUfckdMCku/KK6Wf/ES6+27piiukfQnKAq1btuv4B7+rBzOv0HefO0tTB27T3Evu0f+c/bgLPx5NLqvRj897SPVNufrMk5dre0O+13piJStLmjTJBSDLqHKkLgIQACBUjzwiTZ4sjRrlu5J4+uxn3ZTqJ5+ULrrITeQ7Vq++Kv35z1LGt7+p7Nb9umP8D3TzzdL3zn1ME8tSZwLbpLId+uF5D2tPU54+8+Q7tHM/56MkzbRp0s6dbhw2kKIIQACA0Ozd606Kv/RS35XE24c/LP3tb9KiRe40jZ/+tOfdoPXrpVuuma/pI3bo5JOl3fOW6t/a52rt6PP1uVOe1ds3z+3+QTyYMrBGPzj3Ye3a319ffPrt2tuc7bukeDjxRLce8bXXfFcCHBEBCAAQmqefdifgs/zNv/e+V3rmGWnCBOlzn3Mdua98xe3Rs2CBtGWLtHKl9MQTrmP0sY9J48a50zo+8/czlZVhdeu1z+mp8mtls7O1+5QLff+WunV8+XZ9621PaH1tqf5r3sVqasv0XVL0FRZKY8cSgJDSGIIAAAhNMP76rLN8VwLJjSF/+mlp/nzpu991lyMpKJDOOUf61KekC3f/XZOH1LoNnbYv1+pTr1dL3oBkld0npw2t1JdnPqPvzD9P/zP/XH1j1lOSOD8lVCedJP3jH1KN3/PBgCMhAAEAQmGtC0CMv06eub1YjXb55dJf/iJt3Oim9G3adGAvyxEjpOHDpexg1djcWnfy0F13qbZivLaOf1viiw/RhWPWaHdjP936ykz9OLtZZ8+epwzWwIRn+nQXgF591XclQJcIQACAUKxc6d5Y33yz70pwJAUF7pygqVO7uaO1bvpBa6vePP0Dkkm/9HD15KWqb87V7984WR/9g9GvPzBPmRl0gkIxcKA0ciQBCCmLAAQACAXjr9NET9pGzz4rvf669N73qjF3UPg1heTDJyxWpmnXb+fPUFu70Z0ffJYQFJbp06X775e2bpWGDPFdDXAQAhAAIBT33isdf7z7IBipae5cadK8o9+nYNcmTX/sH9o99Hgtyzk/OYWFxBjpxhNe0XFjrL52/6lqas3UnR98Rv1z2nyXFj0nn+wC0N13S5/4hO9qgIOkXw8bAJDyNm5058tfd53vStAXmc37Nfm5uWrJG6BVMz+UlkvfuvLVy17VD969QH9/+Tid/t13aWV1ke+SomfIEGnoUDd/HUgx0fiXDACQUv76V3ckAKWx9jZNfn6ucvft1IpZH1VrXoHvihLqCxcv0aOfeljVdf0043/frT+9NM53SdFz6qnuk5DNm31XAhyEAAQASLg//1maOVMaM8Z3JTgm1mrc4r+pdOtyrTntfaqriGY4uGhKlV776t06ecQOvf/O83Tpzy/Rsi0lvsuKjhkz3PEf//BbB3AIAhAAIKHeeENaskS6/nrfleBYDV31tIauflabJ1+k6nHR3sRpWEmD/vW5B/XD9yzQ/LWDdMK33qM5f3ibtu7p57u09FdRIZ1yyoGWMJAiCEAAgIT6y1+kzEzpqqt8V4JjUVq1VGNf+bt2DJ+u9Se9y3c5SZGVafWfFy3R2u/8VZ88d5l+O3+ijvuv6/T5f5yhbXUEoT655hpp0SJp7VrflQBvIQABABIm2C7mggukQek7LTm28ndv1qTnf629JSO0ctaHIzP0oKfKCpr0s2te1Mpv/U3XzFirnz11vMZ85Tp96e7TVLc/u/sHwOGuvtodGYaAFBKvf9kAAKFasMBtfsryt/STs3+Ppj5zq9qy+2nZ2R9Xe1au75K8GVter/9347Na+d9/13tPWacfPnGiJn79Gv3ppXGybBvUO6NGSWeeKf3pT+IPD6mCAAQASJg//1nKy5Pe+U7flaA3MlqbNfWZW5Xd3KA3zvm4mvsX+y4pJYwfVKfff+gZLbz5Xo0o3av333mezvnxO7R6W6Hv0tLL+98vLV/uNtMFUgAboQIA+mTuXHdsbZV+9ztp6lTOeU4rtl0TX/ytCnZt0rKzP6Z9pdHfuXZeN5u/Hm6HFnzpPv3mhUn60j2n6ZT/fbfu+MA8XT1jXRjlRc/VV0uf/rT0xz9K06f7rgYgAAEAEuPVV6X6erfaBelj9Ov3q3zTK1p78nu1a/iJvstJWc8/L03USt1+0Wb99/Pn65pfX6C/PrtM/3Hyi8rJbD/s/rNneygyVZWVSZde6lrE3/++m5ICeMQSOABAQjz9tJt6O2WK70rQU+Nf/J1GLntEW8edpapJF/guJy0Myt+n/7vwAV0z+XXd++ZUffqJy7VrP5PiuvX+90tbt0r/+pfvSgACEACg7zZtclNuzz5byuB/lrQw+M15mv2Hf9PuwZO05tTrJWN8l5Q2sjKs/uPkl/Tttz2udbWl+thj79SGPcW+y0pt73iHVFTklsEBnvHfFACgz555RsrJYflbuijcvkYX3fYu1Q88TivOmiObwZKkYzF75AbdcuEDam7L1Mcfu1KLtw7zXVLqystzm4Pdfbe0d6/vahBzBCAAQJ/s2yctXCidcYbUv7/vatCdnH27dckvLpNk9MgnH1Jrbr7vktLapLIduu2Se1Xef5+++PTb9dCaib5LSl033uj+wfj7331XgpgjAAEA+uSFF6SWFumcc3xXgu5ktDbrwtvfqwE71uvxm+5RfflY3yVFwqD8fbr14n/q5MFV+sFLZ2vuq6eq/fC5CDjzTGniROk3v/FdCWKOAAQAOGZtbdKzz0oTJkjDWP2T2qzV7D/8m4at+pfmfeAOVU9gTFki5We36HvnPKorxi3Xn5afpGvvOF/7m1laeBBjpI9+VJo/X1qxwnc1iDECEADgmD3wgLRjB92fdHDKA9/QhAW/1+LL/1urZ97gu5xIysqw+txpz+tjJy3QXa8cpzN/cKXWbGfT1IPccIOUlUUXCF4RgAAAx8Ra6VvfksrL2dsw1U18/jc65aFva+WsD+uVy77mu5xIM0a6dsoSPfDxR7VxZ4FO/p93666Xx/guK3VUVEiXXy79/vdSc7PvahBTBCAAwDH55z/d5qeXXca+hqls+BuP6m1/+ndtnnKRnnvfbYy7TpLLpm3Wq1+9R1OG7NZVcy/Uf/x5lvbsz/ZdVmr4yEekmhr3jwjggbHW+q6hV2bMmGEXL17suwwAiLX2dunkk6WGBumznyUApaqyTa/qyu/PVOOAcr1+4X+qLZsNO5NldscpVs2tGfryvafpp09N06AB+/Wj9y7Q9aetiU8OnTPn8Ova2qTx492Jg889l/yaEAvGmJettTO6uo0OEACg1+67T3r9delrXyP8pKqi6pV6+/9dotac/nrjnE8SfjzJyWrXj69aoIU336sRpXv1/jvP07k/eYeeWTVEafYZdOJkZkqf/KT0/PMSH2rDAwIQAKBX2tulb37TTX677jrf1aArA2rW6h0/PV+StPS8z6i5f7HfgqAZo3foxS/9U7e/b56Wby3RuT+5XKd9953626Lj1NoWl3ZQJx/+sFRQIN1yi+9KEENZvgsAAKSXe+6Rli6V/vhHN8wJqWXAjvV6x0/PV2ZLox74/DMatPZF3yXF0rx5XV1rNUkr9adLV+ux9RP0txXTdO0dF6gkr0Hnj1qrL717tU4ZtSMey+OKilwI+tWvpB/8QBoyxHdFiBE6QACAHmtslL7yFWnSJOnaa31Xg0MVbluty380W9n76/Twpx/X7mHTfJeELuRmtemK8Sv0h8v/rv89+1GdUF6tf66eolO/+25N+sbV+vZDJ2ldzQDfZYbvk5+UWlulW2/1XQlihs/uAAA99sMfSqtXS489xrk/qaZkyzJd+rMLldHWogc/97R2jTjRd0noRoaRZg3fpFnDN6m+KUdb+43RH18ar6/ff6q+fv+pOnNstd532hpdPWOtBhY0+S732Myde/Tbp0+Xfv5zN02lrCwpJQFMgQMA9MjatdLUqdKVV0p/+9uB67t7f4PwDVrzvC659XK1ZeXpoc8+qd1Dp75126R5/IDSzbZ9+Xpqwzg9vn681u8pVaZp1+lDN+vC0as1a/hG5Wa1STowaS6tbdniNhT7/OfdJyxAghxtChwBCADQLWulSy+VXnhBWrlSGjr0wG0EIH8mzZursk2vaPILv1FjfpmWnvcpNRUM9F0WEsRaaW1tqZ5YP15PbhinHfvz1T+rWbNHrtdFY1br0+/doowonMzwwgvS3/8urVnjRmMDCXC0AMQSOABAt+65R3r0UemnPz04/MCj9naNWvKARi19UHVlY/TGOZ9Qa16B76qQQMZI40p2aVzJS5ozfaFe3z5Ej68fr2c3jdGj6ybqp6/s1QdnvqkPznxT4yrqfJd77P77v6W//MV1gm6/3Xc1iAE6QACAo9q9W5o2TSovlxYtOnzyGx2g5MvZt1tn//7DGvPafdo25gy9efr7ZTOzfZeFJGlqzdTzlaO1sHa8Hl8+XO02Q2eN26obZ76pq2es04C8Ft8l9s6cOW4gwq9+JS1YIM3o8kN7oFdYAgcAOCbWSu98p/TII26VyqmnHn4fAlByDVvxpM7+fzeqf902rT/pXaqaeL7iMTcZh5o9W6ra3V9/fGm8fjt/olZtK1a/7FZdceJGvWv6er39+M0q7JcGYWjOHKm2Vjr+eKmwUHr5ZakfG/eibwhAAIAeOTTMPPaYW/52zTXSeef5qQlOvz1bdeo/v6pJL9yp2kET9a8P/1EDN73iuyykCGulFTvL9ci6iZq3aYxqm/opO6NNJw2q0imDt+ikQVv04St3KjMjBd/3zZnjjo8/Ll18sZsI95Of+K0JaY9zgAAAvbZmjXTffdLJJ0vnnuu7mvjqt6daU579pU548ifKaG3W6xd+Xouv+JbacvoTgPAWY6QpA2s0ZWCNPjPjBS3bUaHnK0frxapR+tWrIyVJX5zXpNnjt+rcCVt07sQtmjZsV2oNUbjoIuljH5N+9jPpggvc5BUgBAQgAMBh6uqkX/9aGjhQuuEGVlglW1bTPg1b8YSOe/kfOu7lfyizrUXrT3q3Xnr391VXMc53eUhxmRlWJ1Rs0wkV2/QfJ7+kHQ399eq2IarOGKqnVw3V/a+PliQV92/SqaNqdNro7TptjDsOLtrvt/gf/lCaP196z3ukhx/m0xeEggAEADjI/v1uX8J9+6RPfIKl+MmQv7tSFetfUvn6harY8JIq1r+krJZGNfUv1vKzP6bl53xcewZN8F0m0tTA/g26cMxazZ69VpK0eVe+nl41VPPXDdLC9RX63mPT1dbuWkEjS+t12ugDoeiUkTUqyGtNXrH5+dITT0jnnCNdfrkLQT3Z8Ki7kxGDZXaACEAAgE6amlz4qapyK1FGjPBdUfSYthZVbFikEx7/kQbsWK8BOzcod3+tJKk9I1N7S0ao+rgztWv4CdpTMUE2I1NDVj2jIaue8Vo30t+8ecFX+zRaqzV6xGpdP0JqbM3U6l0DtWJnhVbsLNcLb1borleOkyRlmHaNLtqtyWU1mlS2XVMGbtfY4l1H7AonZHPW8nLpqaeks892Jx9+6UvS178u5eYm4MEBAhAAoENjo5tCu26d+7B02jTfFUVHTkOtRi15QGNeuVtDVz6lnKa9kqT9AypUO2iC6geOUX3ZGO0tGc44ayRdXlabplVs07SKbW9dV9uYp5U7y7ViZ4WW7yjXc5tH66G1kyRJ5f33avaI9Zo9YoOmlVeHM1hh8GDppZekz31O+t//le6+243Kft/7pOLixD8fYoUpcAAA1ddLV1/tNju98UZp5kzfFaU/096mYSue1MQXfqPRr/9Tma3N2lsyXJumXaaqSRcof+cmNi5F2rBW2rJ3gJZsH+L2INo6XM1tWarov1eXjVupS8euUkX/fYnpAB1qxAjpK1+RXnvNrck9++wDlxkzpOxslsDhMIzBBgAc0caNbqn98uXS9ddLZ53lu6L0ltW4VxPn/1YnP/Rt9dtbo5acfG0fc7q2jz5V9WWjJZNKY7eAY9PQkqUFVSP10NpJWlw9XBmmXWcO26TvXLNUs8dvTezglCC8vPyy9LvfueVxy5e76/LzpTPPlPr3lyZMkEaPPny35s6PgdhgDDYAoEsvvug2Om1qcpudrl/vu6L0lb9rs45/+uea9Nxc5e7fo7qBY7ThxCu1Y8R0lrUhcvpnt+q80et03uh12lI/QA+umaQH107WOT8erZNH1uhzFyzV1TPWKjszgR+0n3KKu0jS9u3upKZnn3WXpUvd9dnZ0nHHuTW8s2a5YAQcgg4QAMRQW5vbZ/CrX3WrSx58UJo0qftVJDiEtRq07kUd/9QtGvPq3ZKk9Se9R0sv+KxKK5d4Lg5IrqbWTK3PGq+fPjVNK6tLNKx4rz513jL921krVJLffOwP3JPuzU9+Iq1eLb35prtUVrqhCTNnukEKX/vasT8/0hJL4AAAb1m1yp3ns2CB9K53uf1+ysrcbQSgnpn89C9Vvmmxhq38lwbs2qiWnP6qHjtLWyacq6aCMt/lAd7Mni21t0uPLhuhnzw5TU+tHK783BZ9aOYqffr8NzSuoq73D9qTAHToP16bNkn/+pe0aJHU2ipddpn0mc9I55/PxmYxwRI4AIDq6tyHpN//vjuP+E9/kq67jvcCPWatyja/qgkL/qCJL/xGOY31aigcrNWnXq9tY05Xe3ae7wqBlJCRIV06bbMunbZZr28u1U+fmqbbn5usW5+dqitP3KDPX7hEs8ZuC/ffnpEj3Sc97363WyK3cKF04YVuadxnPuNOeMzj72xc0QECgIhraJBuvVX63vekXbuk975X+r//k4YMOfy+dIAOlr1/jwaveUHDlz+mUa/fr8KdG9SWlaNdQ45X9biztHvIZIYaAD2wc38/3btqqv65eorqmvM0qWy7rp60VGePXKfzzknCe9EbbpD+8hfppz915wuVl0s33eRC0nHHhf/8SDqWwAFAzFjrBiZ94QtuBci+fdLUqdKVV0qjRvmuLjVltDSprGqJBm58WQM3vazyjYtVWrlEGbZdrdl5qpp0gTaecLnWn/JejXn5Lt/lAmmpsTVTj62boH+snKbN9cWq6L9Xn7hghW6c+aZGlO4L74mDZXTWSk8/7YLQgw+6684803WKLrlEmjKFtnhEEIAAIAaqqqQXXpCef1568klpxQo3DXb6dOncc6Vx43xXmBomzXNtruz9e1RUs1aFNWtUtH2N8msrldHeJklqzC/VjpGnaNvYM7V1/GxtO+4MteX0P+wxABybdistqBqpu1Ydr5erh8sYq4unbNYNZ6zWZdM2qbBfS2KfsKvziDZudF2hP//5wBS5khIXgqZOlcaPlwoLj/4YSFkEIABIU83N0rZt0s6dXV82b5Y2bHDjq3ftcr+mf383+Ojqq93yN6bASrJWxdUrNXjN85ow/7cq2r5G/fbWSJLaMrNVXzZGdQOP096yUaovHamm/DI+BQaSZPjkAfp/L07Qb+dPVOXuAuVktenCyZV65/QNOnfiFh03sL7vfx27Cy+bN0v/9V/SsmXu06P9+9315eXS2LHu8sUvSpMnu1HbSHneApAx5hJJt0jKlHSHtfZ7h9xuOm6/VFKDpButta8c7TEJQACiZM8e9yFkcNm06eBjdbVbsdGV/Hxp+HC379+YMdLEiW4T0xNPPPD/c1zP6elXt00DN7plbOUbFmnQuheVt2+nJKk5d4DqysdqT8U41ZWP096SEbKZzAQCfJk92x3b2o0WrKvQ3a+M0T2vjdHGnQMkSYMKG3TWuGqdMGyXJgzaowmDajW6bK+K+zUpo6en4PVmklxbm/tkae3aA5f6endbTo50/PHuH9rp090/vKNGuUu/fr35bSNkXgKQMSZT0puSLpRUKWmRpOustcs73edSSZ+UC0CnS7rFWnv60R6XAAQg1bW3u2Czc6e0Y4e77Nwp1dQcCDYbN7qtKoIPGQNZWVJp6cGX4mIXdgoK3DG4xOZDyPZ2ZbY2vXXJaG1SZov7OqexTgW7Nqlg5wYN2LlRBbs2qrRqqQp2V0qSrDHaUzFB28aeqepxZ6l63FkasvJpujtAirNW2rCnREtrBmvJ9sF6Y8cgbd1beNB9Mky7Svo3a2BBo8oKGlWW36SyfPd1af8mleZ3vrjbS/ObVJDb0rt/Aqx1G68ed5z0+uvSa6+5S03NwferqHBBaPBg1zmqqDj8Ul7uLrH5B9wfXwFopqRvWmsv7vj+y5Jkrf1up/vcLukZa+1fOr5fJekca+3WIz0uASi5unp5HHqdz/uken09uU+q19eT+6R6fZLbBqKxUWpq6v741teNVk2NVs2N7Wra366WpnY1N7pL8HVrU5s7Nrerbneb2lvdbca2KUPtb12sjNqVoZwco6KSDBUWZ6ioJEPFJUbFpe7rklKj/gUZMpkZsiZDMkbWdP91aG/mgz9Ia2VkO7531xlrD7o+s7VJWc0Nh1+a9im7aa9yGuuUvb9O2U31yul8bKxTdmO9spv2Hgg5LR0hJwg8HefldKcxv0z1ZaNkTabqy0Zpb+ko7S0dqTbGUwOR0Niaqar6QlXVF2lbQ4HqmvK0pym345inuuZc7WnKU31TrhrbjhwwsjLaVZrfeCAc9T84KJX0b1ZedquyMqwyM6yyMtqVldmurLe+tsoyberfuFMFdVvUv36b+tXXKK9um3LrdiirYY+y9+1R5r46mSP8+2WLS2QrKqRyF4xMhQtMZlCFOw+poODAJfjEKyPjwMVa9x/V/v0HLp2/f/JJqaXF/efX1nbg6/Z2KTNTOv10t1FsTo4bB96/v3ueIx379XOf0GVkuF8f1JHCfO0DNEzS5k7fV8p1ebq7zzBJRwxAqaKhwQX5zlLtDd+xvGkF4uhevVMX6omDAkuG2pWp9sQ/WbOkbR2XBGo3GZLJkO0IRzIZssF/Tta6wPJWiNFbwcV0CjVBoDEh/uNgZdSWnau2rDy1ZvdTW3aeu2TlqDmvUDYjS+0ZWWrPzHJfZ7rvbWZ2l9e3ZeWpKb9Ujfml7MMDRFxeVpvGluzW2JLd3d63qS1Te5tzVNcRjOqbcrWn2YWj4Pu65lzV78vVql35qm8uVV1TrhpacxJYsVWxalWuGlVo+0GX8toaVdRuV8Wb21WhFarQsyrTTvdvc1iC8NLWJj3ySOIes3Mouu466Te/ScxjhyjMANTVR5KH/lR7ch8ZY+ZIChZv7u3oFKH3Bkra4bsIJAU/6154l+8C+sb9rG27ZEMIbAlnpZZGd9lf67uYdMPf6/jgZx0RtR2X1Ue+S/J+1u3t7hLGY7a2uu/vvNNdUsMRN30IMwBVShrR6fvhkrYcw31krZ0rKaan8iaOMWbxkVqBiBZ+1vHBzzo++FnHBz/r+OBn7UeYi/cWSRpvjBljjMmRdK2k+w+5z/2SbjDOGZL2HO38HwAAAADoi9A6QNbaVmPMJyQ9JjcG+05r7TJjzE0dt98m6WG5CXBr5MZgfyisegAAAAAg1I0PrLUPy4Wcztfd1ulrK+njYdaAg7CMMD74WccHP+v44GcdH/ys44OftQehboQKAAAAAKkktQd4AwAAAEACEYBixBjzQ2PMSmPMEmPMvcaYYt81IbGMMZcYY1YZY9YYY272XQ/CYYwZYYx52hizwhizzBjzad81IVzGmExjzKvGmAd914JwGWOKjTF3dfx/vaJjY3lEkDHmsx3/hr9hjPmLMYbNzJKEABQvT0g63lp7gqQ3JX3Zcz1IIGNMpqRbJb1d0hRJ1xljpvitCiFplfR5a+1kSWdI+jg/68j7tKQVvotAUtwi6VFr7SRJJ4qfeyQZY4ZJ+pSkGdba4+UGhl3rt6r4IADFiLX2cWttx05VWiC37xKi4zRJa6y166y1zZL+KulKzzUhBNbardbaVzq+rpd7gzTMb1UIizFmuKTLJN3huxaEyxhTKGm2pN9IkrW22Vpb67UohClLUj9jTJak/upiL0yEgwAUXx+W9IjvIpBQwyRt7vR9pXhTHHnGmNGSTpL0kudSEJ6fSfqipARv4Y4UdJykGkm/7VjyeIcxJt93UUg8a22VpB9J2iRpq9xemI/7rSo+CEARY4x5smMt6aGXKzvd57/kltD8yV+lCIHp4jrGPEaYMaZA0t2SPmOtrfNdDxLPGPMOSduttS/7rgVJkSXpZEm/staeJGmfJM7njCBjTIncKo0xkoZKyjfGvN9vVfER6j5ASD5r7QVHu90Y80FJ75B0vmUGetRUShrR6fvhop0eWcaYbLnw8ydr7T2+60FoZkm6whhzqaQ8SYXGmD9aa3mjFE2VkiqttUFH9y4RgKLqAknrrbU1kmSMuUfSmZL+6LWqmKADFCPGmEskfUnSFdbaBt/1IOEWSRpvjBljjMmRO5nyfs81IQTGGCN3jsAKa+1PfNeD8Fhrv2ytHW6tHS33d/pfhJ/ostZWS9psjJnYcdX5kpZ7LAnh2STpDGNM/45/088XAy+Shg5QvPxCUq6kJ9zfNS2w1t7ktyQkirW21RjzCUmPyU2TudNau8xzWQjHLEkfkLTUGPNax3VfsdY+7K8kAAnySUl/6vgga52kD3muByGw1r5kjLlL0itypyW8Kmmu36riw7AKCgAAAEBcsAQOAAAAQGwQgAAAAADEBgEIAAAAQGwQgAAAAADEBgEIAAAAQGwQgAAAackY85UEPtb0js1GAQARRwACAKSrhAUgSdMlEYAAIAYIQAAAL4wxNxhjlhhjXjfG/MEY8/+MMe/tdPvejuMQY8w8Y8xrxpg3jDFvM8Z8T1K/juv+1HG/+4wxLxtjlhlj5nR+HGPM9ztue9IYc5ox5hljzDpjzBUdG05+S9I1HY93TZL/KAAAScRGqACApDPGTJV0j6RZ1todxphSST+R9KC19q6O++y11hYYYz4vKc9a+z/GmExJ/a219cHtnR6z1Fq7yxjTT9IiSWdba3caY6ykS621jxhj7pWUL+kySVMk/c5aO90Yc6OkGdbaTyTxjwEA4EGW7wIAALF0nqS7rLU7JKkjuBzpvosk3WmMyZZ0n7X2tSPc71PGmHd1fD1C0nhJOyU1S3q04/qlkpqstS3GmKWSRvf1NwIASC8sgQMA+GAkHboEoVUd/y8Zl4ZyJMlaO0/SbElVkv5gjLnhsAcz5hxJF0iaaa09UdKrkvI6bm6xB5Y7tEtq6njcdvFBIADEDgEIAODDU5KuNsaUSW75mqQNkk7puP1KSdkdt42StN1a+2tJv5F0csd9Wjq6QpJUJGm3tbbBGDNJ0hm9rKde0oBj/L0AANIIAQgAkHTW2mWS/kfSs8aY1+XO//m1pLONMQslnS5pX8fdz5H0mjHmVUnvkXRLx/VzJS3pGILwqKQsY8wSSd+WtKCXJT0taQpDEAAg+hiCAAAAACA26AABAAAAiA0CEAAAAIDYIAABAAAAiA0CEAAAAIDYIAABAAAAiA0CEAAAAIDYIAABAAAAiA0CEAAAAIDY+P9L0PKOKUJiqAAAAABJRU5ErkJggg==\n", 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lkkY0uetwSe8kOTYgLrTJAQAApFOiYcjMhjT553GScivNPSrpZDOrNLPtJY2S9GKSYwPiQmUIAAAgndpY36rjzOweSYdIGmhmyyV9X9IhZraXvAVuiaQzJSmEMNfMZkiaJykjaUoIoT6usQFJYs4QAABAOsUWhkIIpzSz+5ZW7j9V0tS4xgMUSr5La5eUUBkCAABIUiFWkwOKCm1yAAAA6UQYAmJGGAIAAEgnwhAQs3zb5JgzBAAAkCzCEBCzfJfWZs4QAABAsghDQMxokwMAAEgnwhAQM8IQAABAOhGGgJgRhgAAANKJMATEjIuuAgAApBNhCIgZlSEAAIB0IgwBMctVe/JZWpswBAAAkBzCEBAzKkMAAADplFcYMrMHzOyzZkZ4Atqpvl4y8+sItaakhDlDAAAASco33Nwk6YuS3jCzq81sdIxjArqV+vq2q0ISlSEAAICk5RWGQgjPhBC+JGmspCWSnjaz583sa2ZWHucAga4ukyEMAQAApFHebW9mNkDSVyV9XdLLkn4pD0dPxzIyoJugMgQAAJBObaxv5czsQUmjJd0p6egQwrvZm+4zs1lxDQ7oDhoa8gtDJSVSCH7/tuYXAQAAoPPyCkOSfhtCeKLpDjOrDCHUhBDGxTAuoNvIZNpeVltqDEx1dVJlZbxjAgAAQP5tcj9sZt8/ohwI0F21p01OolUOAAAgKa2+X21mgyUNk9TTzPaWZNmb+krqFfPYgG6BMAQAAJBObTXvTJQvmjBc0rVN9q+XdFlMYwK6lfasJpe7PwAAAOLXahgKIdwu6XYzOyGE8EBCYwK6FSpDAAAA6dRWm9yXQwh3SRppZt/Y/PYQwrXNPAxAE4QhAACAdGqrTa53dtsn7oEA3VV9fftXkwMAAED82mqT+012e2UywwG6n3wrQ7lrCzFnCAAAIBl5La1tZj8xs75mVm5mM81slZl9Oe7BAd0BbXIAAADplO91hv4rhLBO0uckLZe0s6RvxTYqoBshDAEAAKRTvmGoPLs9StI9IYQPYhoP0O20d2ltwhAAAEAy8pjWLUl6zMxel7RR0jlmNkjSR/ENC+g+2lsZYs4QAABAMvKqDIUQLpH0SUnjQgh1kqokTYpzYEB3QZscAABAOuVbGZKkXeXXG2r6mDsiHg/Q7bC0NgAAQDrlFYbM7E5JO0p6RVJ9dncQYQhoE5UhAACAdMq3MjRO0pgQQohzMEB3xJwhAACAdMp3Nbk5kgbHORCgu8p3NbncRVepDAEAACQj38rQQEnzzOxFSTW5nSGEY2IZFdCN0CYHAACQTvmGoSviHATQnRGGAAAA0imvMBRC+KuZbSdpVAjhGTPrJSmP0zuguDU0SCEQhgAAANIorzlDZnaGpPsl/Sa7a5ikh2MaE9Bt1GfXXsxnae3cnCEWUAAAAEhGvgsoTJE0XtI6SQohvCFp67gGBXQXuTBEZQgAACB98g1DNSGE2tw/shdeZZltoA2EIQAAgPTKNwz91cwuk9TTzI6Q9HtJj8U3LKB7yLW85dMmRxgCAABIVr5h6BJJKyX9W9KZkp6QdHlcgwK6i45UhpgzBAAAkIx8V5NrMLOHJT0cQlgZ75CA7oM2OQAAgPRqtTJk7gozWyXpdUkLzGylmX0vmeEBXVt7wlBJiWRGGAIAAEhKW21yF8pXkds3hDAghNBf0v6SxpvZRXEPDujq2hOGJKm8nDAEAACQlLbC0FcknRJCWJzbEUJYJOnL2dsAtKK9YaisjDlDAAAASWkrDJWHEFZtvjM7b6g8niEB3QeVIQAAgPRqKwzVdvA2AGrf0toSYQgAACBJbZ2i7Wlm65rZb5J6xDAeoFuhMgQAAJBerYahEEKep3AAmsOcIQAAgPTK96KrADogF2yoDAEAAKQPYQiIEW1yAAAA6ZXntG4AHUEYKkLTprV82+TJyY0DAAC0icoQEKNcGMp3NTnmDAEAACSHMATEiMoQAABAehGGgBgRhgAAANKLMATEqL1tcoQhAACA5BCGgBh1ZGlt5gwBAAAkgzAExKgjF12lMgQAAJAMwhAQI+YMAQAApBdhCIhRLgyV5PmbRhgCAABIDmEIiFF9vVeFzPK7P3OGAAAAkkMYAmKUC0P5Ys4QAABAcghDQIwymfyX1ZZokwMAAEgSYQiIUXsrQ4QhAACA5BCGgBgRhgAAANKLMATEqCNzhlhAAQAAIBmEISBGVIYAAADSizAExIgwBAAAkF6EISBGHQ1DIcQ3JgAAADjCEBCj9i6tnbtvQ0M84wEAAEAjwhAQo45UhiRa5QAAAJJAGAJiRBgCAABIL8IQEKNMhjAEAACQVoQhIEYduc6QxLWGAAAAkhBbGDKzW83sfTOb02RffzN72szeyG63anLbpWa20MwWmNnEuMYFJKmhgcoQAABAWsVZGfqdpCM323eJpJkhhFGSZmb/LTMbI+lkSbtlH3OjmbXjFBJIp/r69q0mRxgCAABITmxhKITwrKQPNts9SdLt2c9vl3Rsk/33hhBqQgiLJS2UtF9cYwOSwpwhAACA9Ep6ztA2IYR3JSm73Tq7f5ikt5rcb3l2H9ClMWcIAAAgvdKygII1sy80e0ezyWY2y8xmrVy5MuZhAZ3D0toAAADp1Y7ZDJFYYWZDQgjvmtkQSe9n9y+XNKLJ/YZLeqe5JwghTJM0TZLGjRvXbGAC0oI2uRhNm9b67ZMnJzMOAADQZSVdGXpU0mnZz0+T9EiT/SebWaWZbS9plKQXEx4bEDkqQwAAAOkVW2XIzO6RdIikgWa2XNL3JV0taYaZnS5pmaQTJSmEMNfMZkiaJykjaUoIoT6usQFJYc4QAABAesUWhkIIp7Rw02Et3H+qpKlxjQcoBJbWBgAASK+0LKAAdDshcNFVAACANCMMATGpzzZ6EoYAAADSiTAExKQjYYg5QwAAAMkhDAExyQUaKkMAAADpRBgCYkKbHAAAQLoRhoCYEIYAAADSjTAExCQXhjqytDZzhgAAAOJHGAJi0pkFFKgMAQAAxI8wBMSkI2GoosK3tbXRjwcAAACbIgwBMcm1urWnTa6y0rc1NdGPBwAAAJsiDAEx6UhlqEcP3370UfTjAQAAwKYIQ0BMOjpnqKSEyhAAAEASCENATDoShsy8VY7KEAAAQPwIQ0BMOhKGJG+VIwwBAADEjzAExKQzYYg2OQAAgPgRhoCYdDQM0SYHAACQDMIQEJOOLK0t0SYHAACQFMIQEBPa5AAAANKNMATEhDY5AACAdCMMATHJtclRGQIAAEgnwhAQEypDAAAA6UYYAmLCdYYAAADSjTAExCQXhjqymhxtcgAAAPEjDAExoU0OAAAg3QhDQExokwMAAEg3whAQk/p6qaREMmvf42iTAwAASAZhCIhJJtP+qpBEmxwAAEBSCENATOrrOxaGcm1yIUQ/JgAAADQiDAEx6UwYCqHxoq0AAACIB2EIiEl9ffuX1Za8TU6iVQ4AACBuhCEgJp2pDEmEIQAAgLgRhoCYdDQM5SpDrCgHAAAQL8IQEJNMpmNtclSGAAAAkkEYAmLS2TY5KkMAAADxIgwBMclddLW9WEABAAAgGYQhICYdXU2ONjkAAIBkEIaAmNAmBwAAkG6EISAmnV1NjsoQAABAvAhDQEy4zhAAAEC6EYaAmHR0aW2uMwQAAJAMwhAQEypDAAAA6UYYAmJSWytVVLT/cYQhAACAZBCGgJjU1DS2vLUHbXIAAADJIAwBMaEyBAAAkG6EISAGIXQ8DFEZAgAASAZhCIjBxo2+7UgYKimRysupDAEAAMSNMATEoLratx0JQ5K3yhGGAAAA4kUYAmJQVeXbjiygIHkYok0OAAAgXoQhIAadrQxVVlIZAgAAiBthCIgBbXIAAADpRxgCYpBrk+tMZYg2OQAAgHgRhoAYUBkCAABIP8IQEIMoFlAgDAEAAMSLMATEIIoFFGiTAwAAiBdhCIhBLgxRGQIAAEgvwhAQg84uoMB1hgAAAOJHGAJiwHWGAAAA0o8wBMSgqkoqLfWPjqBNDgAAIH6EISAG1dUdrwpJtMkBAAAkgTAExKCzYYg2OQAAgPgRhoAYVFV1fCU5iTY5AACAJBCGgBhEURmqq5MaGqIbEwAAADZFGAJiEMWcIYl5QwAAAHEiDAExqKqKJgzRKgcAABAfwhAQgyja5CQqQwAAAHEiDAExiGIBBYnKEAAAQJwIQ0AMopozRBgCAACID2EIiAFtcgAAAOlHGAJiwAIKAAAA6UcYAiKWyUi1tSytDQAAkHaEISBi1dW+7cwCCrnHUhkCAACID2EIiFguDNEmBwAAkG6EISBiUYQhFlAAAACIH2EIiFhVlW+pDAEAAKQbYQiIGG1yAAAAXUNZIb6omS2RtF5SvaRMCGGcmfWXdJ+kkZKWSPpCCGFNIcYHdEauMhTFAgq0yQEAAMSnIGEo69MhhFVN/n2JpJkhhKvN7JLsv79dmKEBHdctK0PTprV82+TJyY0DAAAgQmlqk5sk6fbs57dLOrZwQwE6rluGIQAAgG6oUGEoSHrKzF4ys9zbytuEEN6VpOx26+YeaGaTzWyWmc1auXJlQsMF8hfFAgplZZIZbXIAAABxKlSb3PgQwjtmtrWkp83s9XwfGEKYJmmaJI0bNy7ENUCgo6KoDJl5dYjKEAAAQHwKUhkKIbyT3b4v6SFJ+0laYWZDJCm7fb8QYwM6K4oFFCQPQ1SGAAAA4pN4GDKz3ma2Re5zSf8laY6kRyWdlr3baZIeSXpsQBRylaHy8s49T2UllSEAAIA4FaJNbhtJD5lZ7uvfHUJ40sz+JWmGmZ0uaZmkEwswNqDTqqulnj2lkk6+1UCbHAAAQLwSD0MhhEWS9mxm/2pJhyU9HiBqVVVSr16df57KStrkAAAA4pSmpbWBbqG6OpowRGUIAAAgXoQhIGLV1VLv3p1/HsIQAABAvAhDQMRokwMAAOgaCENAxGiTAwAA6BoIQ0DEqqpokwMAAOgKCENAxKKqDNEmBwAAEC/CEBAxFlAAAADoGghDQMSiWkCBMAQAABAvwhAQMdrkAAAAugbCEBChEFhAAQAAoKsgDAERqq2VGhqirQyF0PnnAgAAwMcRhoAIVVf7NqrKUEODlMl0/rkAAADwcYQhIEJVVb6NagEFiVY5AACAuBCGgAjlKkNRtclJLKIAAAAQF8IQEKFcZSiqNjmJyhAAAEBcCENAhKKsDBGGAAAA4kUYAiIU5QIKtMkBAADEizAERIgFFAAAALoOwhAQIdrkAAAAug7CEBChKBdQoE0OAAAgXoQhIEJUhgAAALqOskIPAN3AtGmt3z55cjLjSAEWUAAAAOg6qAwBEaqqkkpKpIqKzj8XlSEAAIB4EYaACFVXe4ucWeefizAEAAAQL9rkgAhVV0fTIifRJleUWms5LaJ2UwAAkkJlCIhQVVU0iydIVIYAAADiRhgCIhRlZYgwBAAAEC/CEBChKCtDtMkBAADEizlDQIRyCyhEoaREKi+nMtRlLVsmPfec9Prr/p/Zq5fU0CCddprUs2ehRwcAAERlCIhUlG1ykrfKEYa6mNpa6bbbpKlTpX/8Qxo6VBo2TKqrk84+Wxo5UvrDHwo9SgAAICpDQKSibJOTvFWONrkuZPly6ac/9arQUUdJhx/emI5DkHbZRbroIumYY6Rf/lI699zCjhcAgCJHGAIiFGWbnERlqEv54AMPP++/L51zjrTnnpvebiYdcoi3zn3pS9J550kbNkiXXFKQ4aZea8uMSyw1DgCIBG1yQISqqqJtk6My1EXU1EjHHSctXuzVns2DUFN9+kgPPih98YvSpZdKDzyQ3DgBAMAmqAwBEaIyVKTOPlt69lnpnnukdevavn9pqXTLLR6eTj3V5xHts0/swwQAAJuiMgREpKFB2riRBRRitWqVNGOGz7f54x+lRYv8B19I997rCyZ897vSySfn/7gePaSHH5YGDpROOcXLigAAIFFUhoCIbNzoWxZQiMGyZdJVV0m/+93H02GfPtKkSdKECb6EdZKWLpXOOkv65Cel732v/Y/femvpjjukQw+VvvUtaa+9Ih8iAABoGZUhICLV1b6lTS5ijz/uIeHWW6Uvf1l68UWvEF1zjfT1r/vS1dOnS9deK61Zk9y4Ghqkr3zFt3fdJZV18L2lQw7xFeZuukmaMyfSIQIAgNYRhoCI5LqcaJOL0I9+JB19tM+pmTtXuvlmad99pQEDvCK0777SN77hoeStt3xZ6xUrkhnbr3/t84R+8Qtphx0691xTp0pjxniooxQIAEBiCENAROKoDBV1m9z110vf+Y5Xg55/Xtppp+bvZyaNH++hqKbGA9E778Q7tqVLpW9/WzriCOlrX+v88/XoIf3mN7489+OPd/75AABAXghDQERyYSjKylDv3tL69dE9X5cxY4Z0/vk+F+i22zwstGW77XzeTUmJ9KtfSW+/Hc/YQpDOPNO306Z5GIvChAke6p55Jr6xAwCATRCGgIjk2uSirAwNGSK9956fdxeNmTO9GjR+vC9V3Z65OIMH+8VMq6ulo47Kb5nr9rrzTl/J7qqrvH0vSscfL/XsKd19d5H9pwMAUBiEISAiuakqAwdG95xDh3rn1wcfRPecqTZ7tnTssdIuu0iPPurBoL1GjPAV3ubNk046Saqvj258770nXXihB7UpU6J73pw+ffz7X7hQmjUr+ucHAACbIAwBEVmyxLdRFguGDfNtUXRNLVwofeYzvjjCH/8obbVVx59rzBjphhukJ5/0uT1RCEE691yvOt1yS3zLeE+Y4IHugQek2tp4vgYAAJBEGAIis2SJ1L+/1LdvdM85dKhv414PoODee0+aONGrOH/8Y+M33hmTJ3t4ueYavz5RZ911lweUK6/0ylVcSkq8orVmjYc5AAAQG8IQEJElS6KfQlIUlaG1a6Ujj/Q+wyeeiDZo/Pzn0uGH+4IHzz/f8edZvNjb4g46SPrmN6MbX0tGjfJlw596Slq9Ov6vBwBAkSIMARGJIwwNGeLbblsZ+ugjnyMzd65XXfbbL9rnLyuT7rtP2nZb6bjjpGXL2v8cdXW+oENJiS+eUFoa7Rhbcvzxvn3ggWS+HgAARYgwBEQghHjCUGWlL8jQLStDmYyHjL/8xdvYJk6M5+v07y899pgHr6OOklatyv+xIUhnn+1VpV//2pfvTkr//j6H6qWXpAULkvu6AAAUEcIQEIGVK6WNG6MPQ5JPn+l2YSiTkU47zase114rfelL8X690aOlRx6R3nzTL5S6Zk1+j/vxj32xhMsvl04+Od4xNueII3xBiRkz/GcGAAAi1Y4LeABoSRwryeUMG9bN2uTq6qSvftWvpXPVVdJFFyXzdQ85RHr4YemYY6RPf1p68EFphx2av28IPrbvfMdD0A9+kMwYN1dRIZ1wgl/c9eabvUqFeE2b1vrtkycnMw4AQCKoDAERWLrUt3GFoW5TGVqzxlu/ckHokkuS/foTJ/r1i5YulcaO9flEm1+H6P33vVL1ne/49rbbJLNkx9nU2LHSzjt7dapoLjgFAEAyqAwBEchVhtqaUjL62fa/6zx0qJ+f19VJ5eUdG18qvPyyV1kWL5ZuvVX62tcKM46JE/3iriee6OMZOdI/79lTWrTIW9Lq6qQf/cjDWiGDkORf/6STpKlTpe9/X7ruusKOBwCAboTKEBCBJUv8GqFRXmMoZ9gw79p6773onzsR1dVe1dh3X19Ge+bMwgWhnO23l/7xD68MjRwp/exn3gr3yCPSGWdI8+ZJl15a+CCUM3y4dNZZ0k03SXPmFHo0AAB0G4QhIAJxrCSX02UvvLp6tXT11f6DmTrVV46bN8+v1ZMG5eXSF74g/fnPUkODJ85166Trr/cFF9LmBz/wtH3BBT5WAADQaYQhIAJxhqEuc+HVhgbptdekG27wJawHD/bqytix0nPP+fLZ/fsXepRd14ABHoj+9CdfCAIAAHQaYQjopLiuMZST2spQXZ20cKFXfz77WQ86e+4pnXuu9Prr0sUXS6++Kj35pDRhQqFH2z2cdZa0++7SN77ha7kDAIBOYQEFoJNWrfJpMXGFoUGDpLKylFSGMhkPOC+95HNXamp8/+jR3nJ20EH+sd126Zlv052UlUm/+pV06KFeJbrqqkKPCACALo0wVExau34G187osDivMSRJJSXSkCEFrgxt3OjtWX/9qy+C0LevtN9+0m67+Un5oEEFHFyR+fSnfQGKn/7UV8Pbc89CjwgAgC6LMAR0UtxhSCrgtYYyGV/B7PLLpQ0bvEXrK1+RxozxlCYRhArhZz+T/vAH6fTTpX/+0ytGAACg3ZgzBHRSvtcY6oyhQwtQGZo7VzrwQOn88z2NXXaZdN55HohKeOkoqP79/XpDL73kFSIAANAhnNEAnbR0qV9jqF+/+L5GopWhEHx56bFj/QKp994rXXRRvGkP7XfiiT5P63vf8wvaAgCAdiMMAZ0U50pyOcOG+SVwNmyI9+towwbplFO8AnTEEV4dOukkFkNIIzNvYRw0yK/h9NFHhR4RAABdDmEI6KQkwlAiy2u/9ZYvgf373/sqZY8+Km29dYxfEJ3Wv790221+MduLLir0aAAA6HIIQ0An5K4xFHcHWewXXn3xRV8dbvFi6YknpEsuYV5QVzFxovTtb0u//rV0112FHg0AAF0KSxAhfw0N0oIF0r/+5RfbXLLE26refFPq2dMnzQweLO24o7TNNkXRWrV6tVRV1cUrQ7//va8QN3iw9Mwzvlx2G2ozJSotCSotCTEMCO32wx9K//iHdOaZvtT2HnsUekQAAHQJhCG0rrbWT5BnzPC2qTVrfH9JiTR8uF9vZu1aL1msXetLMUvSlltK++wj7b9/wYaehCSW1ZZiqgyFIE2dKn33u75q3MMPt7lM9pJVfXTdn3fXzX8brcNHv60HznpacUTezS+JVV/v+fvll/1ar/36SUdtuZs+NWKxBvaqliQdfHAMA+kqysp8oYuxY6Wjj/bltgcPLvSoAABIPcIQPi6T8QtszpghPfigB6B+/aRjj/ULPu63n7TTTlJ5ud8/d+ba0CCtWOGVotde8wt0zpwpPfus9M1vSscc0+2qRUmFoS22kPr0ibAyVFXlF+78/e998v3NN0s9erR49w+qKnX29Am6f/b2MpP23/59PfTK9rrxL2M05cyIxrSZhgZp0SLphRek2bO9CFleLo0e7RW5Xy0cr+tmHahPDlumKw96WlJDPAPpKoYMkR5/3FPhMcdIf/mL1KtXoUcFAECqEYbg6us9tNx3n/TAA9KqVX4GPmmSL9/7X/8lVVa2/hwlJX5CNmSIT8SvrvbWnRdf9CB1wAF+scjx4xP5lpKQxDWGciJbXnvpUv9//fe//Ro1F1/cZkj91gP768GXt9c3j3hN5356roZvVaXPXX+kLr7/AB18WSe6sjYvAckLVq9N20MPLNhd71VtocrSjMYPX6pD9l6k/Ya+pZ5lXn1csnZLPbV4lKbP3Vu3vLqvDv/0Cx0cRDeyzz7S3XdLxx0nff7z0kMPtf172xWsXu0tusuW+TsCH37o89oyGT92t9zSF/vYaSe/IHDuY9QoLkgLAGgVfyWKWUODV3FmzfJrlaxY4e8kH320L6d85JE+F6ijevWSDjtMmj5duv12b8eaMMFP1K66Stpll+i+lwJZssTPw7bcMv6vFcmFV5991k+Sa2u9ivCZz7T5kH/+U7r176N1yphX9NlBL2rxHGmxpMm7/EX/XPh5HXlkmS69VKqo+PhjJ09u3/Ay9aaz756g387eVXtv87ZO3/NfmjB8iXqVZz5235H9PtTkvf6l9TWVum/+J3TWf5bpUzu/274v2B1NmiT95jf+w//CF7z619x/TtqtXOlvpsyeLb2b/X+trPR3BYYP9zdXysv9dezDD/3164UXvF0wp0cP6ROf8PbBvff27e67t1oFBQAUF8JQsckFoNmz/ePDD/2E4phjPAAddZTUu3e0X7OsTDr9dOnkk6Wf/1z68Y99/tG550pXXJFMkohBCF702mmnZL7esGHSc8918MF1ddKVV3oI3Wkn//nnEUbr66UpU6ShW1bpK7tvemHPrXp8pMsO/LO++afP6v77pS9+sYNjy6quLdXJNx+ux17bTqfuNlun7zkrr67Kc/b5p15aMUxfue0Qvfa9+9WvZ13nBtIdnHGG/59PmSKdcIIHhKh/r+NQXy899pj0q19Jf/6zV3123tnfRBkzxudB5VY5bClpV1VJr7/u18h69VWfaHbPPb7anuSvRzvvLO2wg7T99r4dOdIXfdlmG6mmpntU0wAAeSEMFYO6Op8/MH269MorfvXOsjJfNeyEE/yd0/PPj38cvXtLl1/uJzHf+56f8EyfLv3oR9L/+39SaWn8Y4jQ88/7wnrXX5/M18tVhkJo59Sr55/34Pnyyz5P6Be/8IUv8nDzzZ6Z7/n6P9Vr48dDxr5D3tYRR0hPPy3ttZefr3bEh9UV+syvPqMXlmytG7/4nHaz+Xk/tmdZRpcf+Ced+/QknXfveN3xtb90bBDdzTnneHCYMsXn+j3+eHqvG1VT49Xjn/zE36wZMcIrXAcc4NdSao/evb1dcJ99Gvfl1sCfPbtxFY7Fi/11sbkrGVdU+O/IFls0bnOfDxvmK/YNG9bt5kACQDEiDHVXNTV+hvrAA14F+OAD/wO/xx7eLrLHHoVrFdl6a3+X9swzPYRNnizddJOHowkTCjOmDvjpT6UBAzxf5C0EldVWqzRTo5L6WgUrVUNpmeoq+yiUlrf60GHDPNeuWtXmom9uzhyvBN19tz/4wQe9RTFPq1ZJl13m59EnjXuzxarUpEn+Bvz06dL3v9/+jqxMvekL0w7XS8sG6v7JT+v4sUv07LPte44xA1fq8qNe1pWP76PP7r5MJ+27qH1P0F2ddZbP4TvlFGncOK8QHXhgoUfVaMMGnzd2zTWe9PfdV7r6ap9jeOut0X0dM68Cbb+9vwGUE4LPR1q61Nvs3n/fXy/XrZPWr/eP1as9OK1f7/e/7z5/7FZb+RtJ++wjHXqoL1yxxRbRjRkAkAjCUHeyerVfMPPRR6U//tH/ePfr53OATjhBWr48XXMH9t67cdGGb31LOuggP2m76qpkViTohAUL/Mf83e+2sGBXCOr9wVsauOxlDVw2WwPfellbvTNXfT5YppKGj89/kaTayj7SnBt9PsQOO3gb2+jR/jF0qIYN83eh33mnlTC0Zo23Gd19tx8DvXpJl17qqaZPn7y/vxB8XYX166XrrpPs7y3ft7xcOvVUP5997LFNzzXzcdGMT+rp+cP121P/quPHLmnfg5u4/KjZemreMJ1x18EaN3KlduzwM3UzkyZ5f+WJJ/oJ+w9+4L9v5a2H71itWOEH1o03+jF76KFeGTrssGSrLWbSwIH+kVNb2/x9Gxo8vB1wgK+W+dpr/i7ADTdI117r1fb99pMOP1z63Oc8JHHhYgBIPcJQV5c7K3/sMenvf/c/2EOG+Pyc447zk4tcAGpm5a6CM/OxHn20zyX6yU+k++/3OQ+XXurBIIWuucanFUyZ0mTnu+/6UuLPPCM984y+lF36rcFK9OHg0Vo5cl+tHbSTanv2U315DzWUlkshqKShThUb16mi+kMNHdFXeustX5a8aftOnz46csQuulc7qu6cwdLEAY3/r6tXe0J69VVp/nw/BoYP95Pec87x8lU7XX+9dMcdHvZ2201SK2FIapzW8cwz/ub+ttvm93Vu/MsYXf+X3XXxEa/q9AkL2j3OpspKg+49Y6b2+p8T9IVph+v5bzL14//ss4+3h51xhvSd7/gcmptuSr4S+/rr/stz550eOo49Vvrv//aAkXYlJd4mN2HCpj+3jRt9oYeZM/3jhz/0373Bgz0UHX20BySWOQeAVCIMdTUbN3ro+d//9QD0xhu+f889/STn6KO75juSvXv7CcQZZ/iFQKdN84+TTpIuuMBbfFLSn79ihQeFM7+4Xlv/61lvR3z6aWnePL/DgAHSoYfqb6Wf0qrt9tHq4Z9QfYWfCI1+tvVAOvSu7KTwEDzgLFjgJ5ALFqjXggU6aNnL6v38Cun5dY0Pqqz0id+f+ISvFHfUUZ5IOvjzeuop6cILvaBwxRX5P+744/3N8jvu8Bzb1hSwJ5+Uzr/vQH12j6X68fEvdmism9u2f5V+99W/atKNE/Wtb3nnJbL69fNrhz3yiHTeeV6JPfJIT7yf/GR8v19r1/qKdrffLv3tb96e+7WvSRdd5Cm6q+vZ0ytbhx7qr12rVze+Ps+YIf32t/49H3aYvz5/7nONV1EGABRc6sKQmR0p6ZeSSiX9NoRwdYGHVFjV1T7pN3cB0+ef9/lAFRU+meOCC/wPbL5vxafdiBE+n+jSS6Vf/tJn8E+f7nOcTj3Vz7h3LFAD1EcfSbNn69+XztRTNU/roDv/Id2W8ROdgw+WvvpVfwd4zz2lkhLN60whzsxPmIYN85MsSSapYpU0eg9pmwEZ/fO5OvWoDH4yFtGJ7IIFvhrz7rtLd93Vvkzdu7cX+aZN8/PeU05pvhhZX+/dnH/4g7RDvzWasuuf9Pe/hUjGL0nH7LlUFx72b/3iuj30qU+1v22v25s0yY/TG27wiW/jx/sx+/Wve6Umimrshx/6GwQPPeQfH33kbZ8/+pGvLJnWhRyiMGCAX8j4y1/26tdzzzVW7//wB7/P2LH+un3YYf5GT2cuYQAA6JRUhSEzK5V0g6QjJC2X9C8zezSEMK+wI0tACN5m9Z//eCXgpZd8qbI5c/zsUfITlilT/A/owQe3aw5Il7Pddt6H//3v+5yiW2/1dpr//m9p1109CE6Y4GftO+8cfT/U6tVedZs/3/8fXnxR4dVXZZmMDpVp0ZZjZWd9UzriCJ+QntBiFAMHSrfdJn3mM2W67H/KdO210TxvQ4NPMTr/fM/Zjz7ascNr7Fjps5/1sLNggfSlL3nBKmf1aumWW3zBsAMOkL6/7aPqVR79Utg/Pv4F/X3dHjrxRM+o//M/ybwZn8lIb7y7pea8s5U+qOqhyrJ6VZbVq09lncYMXaPtG1JStO3d23+XzjnHW9ZuvtmrReed58sCTpgg7b+//67ttJNXlZrT0ODXA1q0yCujL7/sLWOvvuqvW1tt5VWg007z+TQpqe62Vwi+4mF9MPWs8uyS1/9jRYW/Xh92mK/iOG+eh6LHHvNK+JVX+tytsWP9dWTcOJ8juMsuXWMpdADoBlIVhiTtJ2lhCGGRJJnZvZImSUp/GArBl/qqrfXKTW1t48fGjb460bp13jKyZo303nseft57T3r7bT/xbjpHZKut/OTh6KN9e8ABzc6aD8Gffv36xi/R0ud1s/ZX3x616tezVn171qpvjzr17VGrvj3r1HeBt8P37eut7fmes4QghQapIZiCpBDM98lkCjKTSrIXiS8p6cC5UL9+vtrc5Mm+4tPDD/tZ+x13+ORryfuxRo3yk4jBg/3nNGiQJ4cePfxkI/dRX+/vUuc+1q71FaTef99P6pYv9/+LNWv+bwgNfbbQe8P31WP9vqUnV++rRcMO1vQnB0i7t/N7iciRR/pK2T//uX/L++3nb+YPGJDfzzcEvxTLqlUeTv70Jy/GLVrkP76HHur4+hVmfsmqT3zCq0M33OALeGUyfnivXevnh6ef7uPu9Ww81wSqKGvQU0/59I3rrvNF1C680N9DGDHCf14tnd+3JgT/XVqzxosfb73l71fkPl5/Xaqt/UKLj+/7E39PY5dd/Ge83XZeJKmp8SJw1d920Ttre2np6i209IM+WrGupzbWlam6tkw1l/lhPXy4f+S+jxEjPOj169e4AnTeayP06SOdfbZ/5E7Un3zSE3fTNeN79PADrGdPXyigttb/Qz/4wP9zc3r39hB12WXSxIn+eVna/sxsqqHBXyfXrvWPd+YO16JVW2jRyr5avNq3i1ZtobUbs2+4XOybvn39ZWeXXRr/P3PF3IEDN33ZKS+XzMwn4O22m3TJJf4L+PzzjR833eSvSTnbbutfYMgQ/8UcMsQPlr59/efcp8+m28pK/+WqqEhJ4gaQdpmMnw9UVTUunrl6deP5Qe7zqio/N+zd2z8GDvTu/MGD/fN+/RqvQlBW1vXe97IQomtP6Swz+7ykI0MIX8/++1RJ+4cQzm3u/uPGjQuzZs1KcogtGzjQj5p8mfkftiFD/GOnnfwv6s47+3bEiGaPpsce82k09fWNH/koLZVKQ0a1DW2fmJg1funmDugQ/ASio3LPnwtHm29bkztcy0KdRof52rVhrnZtmKvRYZ5GNSzQoPC+Bmi1SpT/cd0g0yoN1CobpPdsiN60nfSGdtb8+lH6j3bWGxqloBLttZcvwnXiifmdbDbXItbWnKGDc3OG2lBd7eeZc+Y07israzwH2vzXuum/Q/j4cTNqlHTIIV4UaO7ctbVxv35w82POZPy8eu7cxnO2fv286JDL9W39PNrj4IM325G9KOfixY1rBmwudyy29iH5zyuTafm479/fT4KHDpXGrf+Ttu+3Rlv12Ki6hlLV1pdo590r9O+3++uVvp/SK69ICxf63LOWbNO3Wv3LN2hAz2r1KKtTZWm9NgwfrfXrPYitWeMn7i29fDf9/d38e2ltX05JqNcu4XXtWP8f7RgWalB4X/3DalWqRmWqU60qVKU+WmP99Y4N01u2reZpjJbaSDVY42Sx5saX9776j/+wN7mbNZ7wd+brtKSiJKPBfdZraJ/1GtJnnYb0Wa/ykga9te34/8uCFRVeAV22rO3nLi31142W5tKVh1rtFN7Qzg2va5eG+dq54XVtH97UNuE9DQ7vqodq8hr3r8q+ocsqr8n/GwUQi3xegwp1n9zn+bxu5d5rKS/3c48NGzZ9D6w5ZWX+MX68L6yUFmb2Ughh3Mf2pywMnShp4mZhaL8QwnlN7jNZUu7saxdJuSWoBkpaleBwAYnjDoXBcYdC4dhDIXDcIQrbhRA+1maVtv6F5ZJGNPn3cEnvNL1DCGGapI+9nWxms5pLe0CcOO5QCBx3KBSOPRQCxx3ilLbG4n9JGmVm25tZhaSTJT1a4DEBAAAA6IZSVRkKIWTM7FxJf5QvrX1rCGFugYcFAAAAoBtKVRiSpBDCE5Ke6MBDo5uJDeSP4w6FwHGHQuHYQyFw3CE2qVpAAQAAAACSkrY5QwAAAACQiNSFITMbYWZ/NrP5ZjbXzC7I7u9vZk+b2RvZ7VbNPHYXM3ulycc6M7swe9sVZvZ2k9uOSvhbQ4p15rjL3u+i7OPmmNk9ZtajPY9H8Yrx2OM1Dy2K4Li7IHvMzc39nW3P41GcYjzueL1Dh6UuDEnKSLo4hLCrpAMkTTGzMZIukTQzhDBK0szsvzcRQlgQQtgrhLCXpH0kVUt6qMldfp67PTs3Ccjp8HFnZsMknS9pXAhhd/niHydnb27z8Sh6cR17Eq95aFlnjrvdJZ0haT9Je0r6nJmNyt7Max5aE9dxJ/F6hw5KXRgKIbwbQpid/Xy9pPmShkmaJOn27N1ul3RsG091mKQ3QwhLYxoqupEIjrsyST3NrExSLzVeH6u9xy2KTIzHHtCiTh53u0r6ZwihOoSQkfRXScdlb+M1Dy2K8bgDOix1YagpMxspaW9JL0jaJoTwruS/TJK2buPhJ0u6Z7N955rZa2Z2K6V7tKS9x10I4W1JP5O0TNK7ktaGEJ7K3tze4xZFLOJjT+I1D3nowN/aOZIONrMBZtZL0lFqvGA6r3nIS8THncTrHTootWHIzPpIekDShSGEde18bIWkYyT9vsnumyTtKGkv+UnDNdGMFN1JR4677IvuJEnbSxoqqbeZfTm+UaI7iuHY4zUPberIcRdCmC/px5KelvSkpFfl7U9AXmI47ni9Q4elMgyZWbn8l2R6COHB7O4VZjYke/sQSe+38hSfkTQ7hLAityOEsCKEUB9CaJB0s7znFPg/nTjuDpe0OISwMoRQJ+lBSQe24/EocnEce7zmoS2d+VsbQrglhDA2hHCwpA8kvdGex6N4xXHc8XqHzkhdGDIzk3SLpPkhhGub3PSopNOyn58m6ZFWnuYUbdYil/slyzpOXm4FJHX6uFsm6QAz65V9nsPkfdD5Ph5FLK5jj9c8tKazf2vNbOvsdltJx6vxby6veWhRXMcdr3fojNRddNXMJkh6TtK/JTVkd18m7ymdIWlb+QnAiSGED8xsqKTfhhCOyj6+l6S3JO0QQljb5HnvlJdPg6Qlks7M9acCERx3V0o6SV6yf1nS10MINWY2oLnHJ/edIe1iPPZ4zUOLIjjunpM0QFKdpG+EEGZm9/OahxbFeNzxeocOS10YAgAAAIAkpK5NDgAAAACSQBgCAAAAUJQIQwAAAACKEmEIAAAAQFEiDAEAAAAoSoQhAEC3YWaXdeKxh5jZgW3fEwDQXRCGAADdSYfDkKRDJBGGAKCIEIYAAKlhZl8xs9fM7FUzu9PMfmdmn29y+4bsdoiZPWtmr5jZHDM7yMyultQzu296c8+X3Xe0mb1gZi+b2TNmto2ZjZR0lqSLso8/KPnvHgCQNC66CgBIBTPbTdKDksaHEFaZWX9J10p6PIRwf/Y+G0IIfczsYkk9QghTzaxUUq8Qwvrc7S09X/aq9ltJ+jCEEMzs65J2DSFcbGZXSNoQQvhZ8t89AKAQygo9AAAAsg6VdH8IYZUkZYNLS/f9l6Rbzaxc0sMhhFfyeb7s/uGS7jOzIZIqJC2O7lsAAHQltMkBANLCJG3erpBR9m+VeTKqkKQQwrOSDpb0tqQ7zewreT6fJF0n6foQwh6SzpTUI5LRAwC6HMIQACAtZkr6gpkNkKRsm9wSSftkb58kqTx723aS3g8h3CzpFkljs/epy1aLWno+SeonD1GSdFqTr79e0hYRf08AgBQjDAEAUiGEMFfSVEl/NbNX5fOFbpb0KTN7UdL+kqqydz9E0itm9rKkEyT9Mrt/mqTXzGx6C88nSVdI+r2ZPSdpVZMhPCbpOBZQAIDiwQIKAAAAAIoSlSEAAAAARYkwBAAAAKAoEYYAAAAAFCXCEAAAAICiRBgCAAAAUJQIQwAAAACKEmEIAAAAQFEiDAEAAAAoSv8fexDahTGqG/QAAAAASUVORK5CYII=\n", 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\n", 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AyMunMsRobQQIQwAAAIg82uRQCMIQAAAAIi9Mmxz3GUJnhCEAAABEHpUhFIIwBAAAgMgjDKEQhCEAAABEHm1yKARhCAAAAJFHZQiFIAwBAAAg8rjPEApBGAIAAEDkcZ8hFIIwBAAAgMijMoRCEIYAAAAQeWEqQzU1khlhCB0IQwAAAIi8MJUhyVeHCEMIEIYAAAAQeWEqQ5IPQ+wZQqCu3AsAAABAD5o/v+uxefN6fx29LGxlqKaGyhA6hKoMmdk9ZnaRmVFJAgAAQMXJpzJEGEIgbLi5UdK7Jb1gZv9lZtNLuCYAAAAgL+wZQiFChSHn3EPOucslnSBpjaQFZvY3M3ufmYXI4AAAAEBpOBe+MkSbHNKFbnszsxGS/kXSByQtlnSDfDhaUJKVAQAAACEkkz4QURlCvkINUDCzeyVNl3SbpDc75zamnrrTzBaVanEAAABAd1pb/SN7hpCvsJWhnzrnjnLOfSMIQmbWR5Kcc7MyvcDMbjazzWa2PO3YcDNbYGYvpB6HpT33GTN70cxWmdn5RfyeAAAAUEUSCf8YtjLEaG0Ewoahr2Y49vduXvMLSRd0OvZpSQ875w6X9HDqc5nZUZLeJeno1Gt+ZGa1IdcGAACAKkZlCIXK2SZnZodIGiepn5nNlGSppwZL6p/rtc65x8xscqfDF0uak/r1LZIekfSp1PE7nHP7JTWZ2YuSTlL3gQsAAABVLghD7BlCvrrbM3S+/NCE8ZK+k3Z8l6TPFvD1Rgdtds65jWY2KnV8nKSFaeetSx0DAAAAcgra5Orrpba23OcShpAuZxhyzt0i6RYze5tz7p4SrsMyHHMZTzSbJ2meJE2cOLGESwIAAEAUpFeGwoQh9gwh0F2b3Hucc7+UNNnMruv8vHPuOxlelssmMxuTqgqNkbQ5dXydpAlp542XtCHTBZxz8yXNl6RZs2ZlDEwAAACoHumVoe7U1HSEJ6C7AQoDUo8DJQ3K8JGv30q6MvXrKyX9Ju34u8ysj5lNkXS4pCcLuD4AAACqDHuGUKju2uR+knr8Ur4XNrPb5YcljDSzdZK+IOm/JN1lZldJekXS21PXf9bM7pL0nKQ2SR9yzvHHFAAAAN3KpzJEGEK6sDdd/Zb8eO0WSQ9KOl7Sx1MtdBk55+ZmeersLOd/TdLXwqwHAAAACFAZQqHC3mfoPOdcs6Q3ye/vmSbp30u2KgAAACCkfPcMEYYQCBuGgj9ab5R0u3Nue4nWAwAAAOSFyhAKFapNTtIDZrZSvk3uWjNrlLSvdMsCAAAAwsl3zxCjtREIVRlyzn1a0mxJs5xzrZL2SLq4lAsDAAAAwqAyhEKFrQxJ0pHy9xtKf82tPbweAAAAIC9Mk0Ohwk6Tu03SVElLJAV/fJwIQwAAACgzKkMoVNjK0CxJRznnXCkXAwAAAOSLPUMoVNhpcsslHVLKhQAAAACFyKcyxGhtpAtbGRop6Tkze1LS/uCgc+4tJVkVAAAAEBJ7hlCosGHoi6VcBAAAAFCofPcMOedb5WrC9kghtkKFIefco2Y2SdLhzrmHzKy/pNrSLg0AAADoXr6VIclXhwhDCPVHwMyulnS3pJ+kDo2TdH+J1gQAAACElu+eIYlWOXhh8/CHJJ0mqVmSnHMvSBpVqkUBAAAAYQWVodoQfUvplSEgbBja75xLBJ+kbrzKmG0AAACUXWurrwqZdX8uYQjpwoahR83ss5L6mdm5kn4t6YHSLQsAAAAIJ5EIt19I6ghD3GsIUvgw9GlJWyQtk/RBSb+X9J+lWhQAAAAQVlAZCoPKENKFnSbXbmb3S7rfObeltEsCAAAAwiukMkQYgtRNZci8L5rZVkkrJa0ysy1m9vneWR4AAACQG5UhFKq7NrmPy0+Re51zboRzbrikkyWdZmb/VurFAQAAAN3JpzIUjNZmzxCk7sPQFZLmOueaggPOudWS3pN6DgAAACgrKkMoVHdhqN45t7XzwdS+oZD5GwAAACgd9gyhUN2FoUSBzwEAAAC9gsoQCtXdNLnjzaw5w3GT1LcE6wEAAADyQmUIhcoZhpxztb21EAAAAKAQVIZQqLA3XQUAAAAqEpUhFIowBAAAgEgrpDLEaG1IhCEAAABEXCH3GaIyBIkwBAAAgIhjzxAKRRgCAABApLFnCIUiDAEAACDS8qkM0SaHdIQhAAAARBqVIRSKMAQAAIBIY88QCkUYAgAAQKTlUxmqq/OPhCFIhCEAAABEXD6VoSAMtbWVbj2IDsIQAAAAIq2QyhBhCBJhCAAAABHmnA82+UyTq6khDMEjDAEAACCyWpP+x9mwlSHJD1EgDEEiDAEAACDCgjAUtjIk+eBEGIJEGAIAAECEJdoKqwwxTQ4SYQgAAAARVkhlqK7OT6AD6sq9AAAAAETY/Pldj82b12tfPpH0d1HNpzJUX09lCB6VIQAAAERWIZUhBiggQBgCAABAZBUyTY42OQQIQwAAAIisYIBCvnuGaJODRBgCAABAhBVaGaJNDhJhCAAAABGWYJocikAYAgAAQGQVWhmiTQ5SGUZrm9kRku5MO3SopM9LGirpaklbUsc/65z7fe+uDgAAAFGSaPOjtfOtDNEmB6kMYcg5t0rSDEkys1pJ6yXdJ+l9kr7rnPvv3l4TAAAAook9QyhGudvkzpb0knPu5TKvAwAAABFU6DQ5whCk8oehd0m6Pe3zD5vZUjO72cyGlWtRAAAAiAYqQyhG2cKQmTVIeoukX6cO3ShpqnwL3UZJ12d53TwzW2Rmi7Zs2ZLpFAAAAFSJRDL/PUO1tYQheOWsDF0o6Rnn3CZJcs5tcs4lnXPtkm6SdFKmFznn5jvnZjnnZjU2NvbicgEAAFBpCqkM1dcThuCVMwzNVVqLnJmNSXvuEknLe31FAAAAiBT2DKEYvT5NTpLMrL+kcyV9MO3wt8xshiQnaU2n5wAAAIAuCqkM1dZK7e3+o6bcO+hRVmUJQ865vZJGdDr23nKsBQAAANGVSOZfGQqCU1tbfq9D/JCFAQAAEFmFVoYkKZkswYIQKYQhAAAARFaiLf9pcnWp3qjW1hIsCJFCGAIAAEBkFTpNTmKIAghDAAAAiLBEW41qa/MbhECbHAKEIQAAAERWa7Imr6qQRJscOhCGAAAAEFmJZG3eE+GC8ERlCIQhAAAARFYhlaGgTY49QyAMAQAAILISbTV5V4Zok0OAMAQAAIDIKmbPEG1yIAwBAAAgshLJwitDtMmBMAQAAIDIYpocikEYAgAAQGQl2vKfJkebHAKEIQAAAERWMZUh2uRAGAIAAEBksWcIxSAMAQAAILKoDKEYhCEAAABEVjH3GSIMgTAEAACAyKIyhGIQhgAAABBZiWT+0+Rqa/0jYQiEIQAAAERWIZWhmhofiAhDIAwBAAAgsgrZMyT5VjnCEAhDAAAAiKxCKkMSYQgeYQgAAACRlWirLSgM0SYHiTAEAACACGst4KarklRfTxgCYQgAAAARlqBNDkUgDAEAACCyCq0M0SYHiTAEAACACEu0URlC4QhDAAAAiKRku6ndFT5aO5ns+TUhWghDAAAAiKTWpP9RttDKUGtrDy8IkUMYAgAAQCQFYYibrqJQhCEAAABEUqKtuMoQbXIgDAEAACCSqAyhWIQhAAAARFKCPUMoEmEIAAAAkVRsZYg2ORCGAAAAEEmJtlpJhVeGaJMDYQgAAACRxJ4hFIswBAAAgEgqdpocYQiEIQAAAERST1SGnOvhRSFSCEMAAACIpNYip8k5J7W39/CiECmEIQAAAERSIukHKBRaGZJolat2hCEAAABEUjGVoVqfowhDVY4wBAAAgEhKJPyGn0IqQ0GAIgxVN8IQAAAAomflSl3wi7k6XY8VvGdIIgxVO8IQAAAAoiWZlO68U332N+t6fUIN9fmPhKNNDhJhCAAAAFHz979LGzaoafIcvU6LNOThe/O+BG1ykAhDAAAAiJrnnpNGjNDDp35eWzRSAx/7fd6XoE0OEmEIAAAAUfPyy9LkyUq4ei3WTDU8tzjvS9AmB4kwBAAAgCjZvVvaulWaNEmJthot1kzVrXpWSiTyugxtcpDKFIbMbI2ZLTOzJWa2KHVsuJktMLMXUo/DyrE2AAAAVLCXX/aPkyerNVmjJZohSySklSvzukxQGUome3h9iJRyVobe4Jyb4Zyblfr805Ieds4dLunh1OcAAABAhzVr/OPEiUoka7VEM/znS5bkdZlgz1Bra08tDFFUSW1yF0u6JfXrWyS9tXxLAQAAQEV6+WVp9GipXz+1Jmv0vKbJ9euXdxiiTQ5S+cKQk/QnM3vazOaljo12zm2UpNTjqDKtDQAAAJVq40Zp/HhJUqKtRrW1kh17bN5hiDY5SFJdmb7uac65DWY2StICMwvd5JkKT/MkaeLEiaVaHwAAACpNMilt2ybNnClJak3WqL62XZo2TXr88bwuRZscpDJVhpxzG1KPmyXdJ+kkSZvMbIwkpR43Z3ntfOfcLOfcrMbGxt5aMgAAAMptwwYfiEaOlCQlkjVqqGuXJk2S1q3Lq+eN+wxBKkMYMrMBZjYo+LWk8yQtl/RbSVemTrtS0m96e20AAACoYKtX+8dUGDpQGZo82Yek9etDXyoIQ7TJVbdytMmNlnSfmQVf/1fOuQfN7ClJd5nZVZJekfT2MqwNAAAAlaqpyT8GlaG2WjXUJn1lSEpNmpsU6lK0yUEqQxhyzq2WdHyG49sknd3b6wEAAEBENDVJZtLw4ZI6VYakVBg6M9SlqAxBqqzR2gAAAEB2q1dLw4YdSDIH9gwFQ7WCG7KGEEyTY89QdSMMAQAAIBqamg60yElplaE+faQxYzpuyBqCmc9UtMlVN8IQAAAAoqFTGPJ7htr9J5Mn51UZknwYok2uuhGGAAAAUPlaWvxo7YMqQ+YrQ5IfopBHZUjyYYg2uepGGAIAAEDlC6o+nStDdanSzuTJ0iuvyNrDl3oIQyAMAQAAoPJ1useQlLZnSJImTJDa2tR31+bQlyQMgTAEAACAytfpHkNSappcEIbGjJEk9d+5MfQlCUMgDAEAAKDyNTVJfftKgwcfOHRQZYgwhAIQhgAAAFD5Vq+WpkzxM7FT/J4hwhAKRxgCAABA5Wtqkg499KBDB1WGDjlEUn5hqLaWMFTtCEMAAABx1tyc98jpiuNcR2UoTSJZ0zFNrk8facQIDdixIfRlqQyBMAQAABBXO3ZIX/uadNppUmtruVdTuNde86GuUxg6qDIkSWPG5FUZqq8nDFU7whAAAEBczZ/vQ8SGDdJvflPu1RQumCTXqU0u0ZY2TU7KOwzV1krJ8LclQgwRhgAAAOKouVl66SXpzW+WJk6Ubryx3CsqXHCPoR6uDNXVRbtghuIRhgAAAOIo2Cc0bZr0gQ9If/6z9OqrZV1SwYLKUJc9Q7Ude4YkaexY9Wt+VWpvVxi0yYEwBAAAEEdr1kg1NdKECdIZZ/hj//xnWZdUsKYmacSIg+4xJGWuDNUmW9V3z7ZQl6VNDoQhAACAOGpqksaO9VPWjjvOH1u6tLxrKlSGSXLOpe4z1CkMSeHHa9MmB8IQAABA3DjnK0OTJ/vPhw3zFaIoV4Y6DU9Itvubr3auDEn5hSEqQ9WNMAQAABA3W7ZIe/d2hCHJV4eiWBlKJn2wy3CPIUlqqCsuDLFnqLoRhgAAAOJm0yb/OHZsx7Hjj5dWrJD27y/Pmgq1YYPvZcswSU4qvjLU1uYLaahOhCEAAIC42bLFPzY2dhw77jj/k//KleVZU6Gy3mOoVpLUUJvW59a/v/b3G5JXGJLYN1TNCEMAAABxs3Wr1NAgDRrUcezYY/3jsmXlWVOhctxjSOpUGZK0d8gY9d+5IdSlgzAUtWIZeg5hCAAAIG62bfOjqM06jgWVlSBcREVTkx8RPnHiQYcTbRn2DCkIQ/lVhghD1YswBAAAEDdbt0ojRx58rG9fady4jrazqHjpJT8Jr6HhoMO5K0P5haFEovhlIpoIQwAAAHHinA9DI0Z0fW7KlOhVhp5/Xpo2rcvhRDK1Z6ju4NnYe4eM9WEoxFQEKkMgDAEAAMTJ3r3Svn0HD08IHHpotCpDzkkvvCAdfniXp3JVhupa96mhZWe3l6cyhLpyLwAAAAA9KJgk17lNTvJh6LbbfCmkT5/eXVc28+dnPj5vnq9w7diRuTIU7BnKEIYkqf+ODUr0H5rzS1MZApUhAACAONm2zT9ma5NzTnr55d5dU6FeeME/5lkZksLda4gwBMIQAABAnGzd6h+zVYak6LTKPf+8f8y4Zyj7NDkpvzBEm1z1IgwBAADEyY4dfnJcv35dnwvu1ROVIQrPP+8Ty+TJXZ7KWhkaOlYSlSGEQxgCAACIk507pSFDMj83ZozfKxSVMPTCCz7A1XXd5r6v1R/rW9920PHWvoPU2meABoS48WqtH0hHGKpihCEAAIA4yRWGamqkSZOkNWt69mtu2SI9/LDU1tb9ufl4/vmM+4UkaWeLv+/Q4L6tXZ4Le6+h+nr/SJtc9WKaHAAAQJzs3JmxreyASZOkV17pua/33HPST37ix3lv2ya94x3Zz802OS6TREJasUK68MKMTze3+CQzpF/XJLN38Bj1o00OIVAZAgAAiAvn/J6hoUOznzNxYs+GoXvvlQYPlk45xVeHVqzomeuuWCG1tkozZmR8unlfUBnKEIaGjg1VGQra5KgMVS/CEAAAQFw0N/sAka1NTvKVoVdf9ZWcYq1YIa1dK82ZI73nPdKgQdLjjxd/XUlassQ/ZglDO1sa1FCXVJ/69i7P7R0yJtSeoaBNjspQ9SIMAQAAxMWGVADIFYYmTvSP69YV//Vuv10yk2bN8snihBOkpUul3buLv/aSJX4iXpY9Q8376jO2yEk+DNXv36P6fbtyfgna5EAYAgAAiIuNqdawMGGoJ1rl7rrL3wMo+HqzZvnK1AMPFH/tJUuk447r6GXrpLmlIWOLnCTtGRJuvDZtciAMAQAAxEWYMDRpkn98+eXivtaWLdKqVdLRR3ccO+wwv1/p7ruLu7ZzPgzNnJn1lJ0tDRknyUlpN17dkbtVjjY5EIYAAADiImiTyzVAYdw439pWbGXoH//wj4ce2nGspsaHoz//WUomC7/21q1+EESW/UJS921yEpUhdI8wBAAAEBcbN/qbqvbtm/2cPn2kQw4pPgwtXOjTRFBpCkyf7oPM4sWFXzuYSDdnTtZTmvc1aHC2MDQ0fJucGZWhakYYAgAAiIsNG3K3yAUmTSq+Te4f//B7ehoaDj4+fbp/fOihwq+9YoU0YYLfj5RFrja5RL8haqvvq/4hJsrV1RGGqhlhCAAAIC42bgwXhoq911B7u/Tkk9LJJ3d9bvBg6Zhj/D2HCr32ypXSOef4sk0WzS0NWdvkZKa9Q8aEutdQXR1tctWMMAQAABAXGzbk3i8UCMKQc4V9nVWr/D2NMoUhyQeZv/61sHsZvfKKtHevdO65WU9xLqgMZU8xe4eEu/EqlaHqRhgCAACIA+d8ZWjw4O7PnTTJJ4DNmwv7WsuW+cdsAw7OPtsHob/9Lf9rL1rkBzGcc07WU/a11qqtvSbrniEpdePVbqbJSYShakcYAgAAiINdu6Q9e8K3yUmFt8otX+4DS7A/qLMzzvDTCfJtlUskfICaOVNqbMx6WvM+v08pa5ucpD3DxmvAjnXdVr9ok6tuhCEAAIA4CO4xFLZNTiouDB1+ePapdYMH+xa6fMPQ00/7QHfmmTlP29niw1C2AQqStHvYeNXv36OGlp05r0VlqLoRhgAAAOIgzA1XA8XeeHX5cj8kIZezz5aeesqP2Q5j3z7pgQeksWNzTpGTpOYWf7fUXHuG9gwdL0ka8Nq6nNeiMlTdCEMAAABxEOaGq4GhQ6WBAwurDO3dK734onTssbnPO+88Pxnuj38Md93775e2bZPe/e6cU+SkkG1ywydICheGqAxVr14PQ2Y2wcz+YmYrzOxZM/tY6vgXzWy9mS1Jfbyxt9cGAAAQWflUhswKH6+9YoXfh9NdZWj2bL/v5777ur/mX/7iP846y7ffdeNAm1y/3G1ykjTwtbU5r0UYqm51ZfiabZI+4Zx7xswGSXrazBaknvuuc+6/y7AmAACAaNuwQerfP/s+ns4KvfHq8uX+sbswVFsrXXyxdMcdvgUu27oWLvTnHH+8dNlloZbQvK/7Nrm9Q8bImdEmh5x6vTLknNvonHsm9etdklZIGtfb6wAAAIiVjRulMWO6bTE7oNDK0PLlUp8+0tSp3Z976aXS7t3SQw9lfn7JEumWW6QjjpCuvtoHqBCaW7pvk3O19do7+BA/US4HKkPVrax7hsxssqSZkv6ROvRhM1tqZjeb2bDyrQwAACBiNmzwYSisiROlrVv9HqB8LFsmHXWUTxHdOessaeRI6Uc/6vrcqlXSTTf5dVx7rVRfH3oJQZvcoBzT5KTUeO1uKkO1tYShala2MGRmAyXdI+njzrlmSTdKmipphqSNkq7P8rp5ZrbIzBZt2bKlt5YLAABQ2TZu9JPYwip0olyYSXKBPn2k666T/vAHPzY70NQk/fCH0qhR0kc/Gr61L6V5X4P61repoa4953l7hnYfhurraZOrZmUJQ2ZWLx+E/tc5d68kOec2OeeSzrl2STdJOinTa51z851zs5xzsxpz3IwLAACgquRbGTr0UP/40kvhX/Paa9L69eHDkCR96EN+et2HPuTvIbR8ufS970mDBkkf+5g0YED4a6XsbGnI2SIX2DNsPAMUkFOvD1AwM5P0M0krnHPfSTs+xjmXGoOiSyQt7+21AQAARNLu3f4jn8pQsOcnnzD07LP+MZ8wNHiwb4e7/HJ/36H2dmn8eN8aF2YMeAbN++pzDk8I7B42QQ37dqm+Zada+2WesldbS2WompVjmtxpkt4raZmZLUkd+6ykuWY2Q5KTtEbSB8uwNgAAgOgJxmqPGSO1tIR7TWOjv9dQPmEomCTX3T2GOrvsMh/UPvc53xp36qm+ha5AzS0NGtzNfiGp415DA7e/otfGZV4zlaHq1uthyDn3V0mZxpz8vrfXAgAAEAvBDVfHjg0fbsykww7LLwwtW+YrPePH57/GU0+V3vnO/F+XQdg2ueaRvhVw8NYmwhAyKus0OQAAAPSA9MpQPqZOzb8ydMwx4cd3l0jzvnoNDhGGdo2cIkkatLUp6zn19f42SM712PIQIYQhAACAqAsqQ4WEoaYmKZns/lzn8pskV0LN+8K1ye0bOFKtfQbkDEMDB/ptTDt29OACERmEIQAAgKjbuNGPp853IMHUqX56wPr13Z/76qvS9u0VEYbCtsnJTLtGTNHgrauznjJwoH/cvLmHFodIIQwBAABEXTBWO9/2tXwmyi1b5h/zHZ7Qw5yTmlvCTZOTfKtcrsrQoEH+kdtXVifCEAAAQNTle8PVwGGH+ccXX+z+3GCS3NFH5/91etDeRJ3aXY0G9+u+TU6SmkdO0aBtTVk3BRGGqhthCAAAIOryveFqYMIEf9PT4P5BuSxfLo0e7Udyl9HOlgZJCtcmJ2nXyENVv3+P+u7emvF5wlB1IwwBAABEXaGVoZoaX+lZHuJe9xUzPKFekvJqk5OyT5QL9gwRhqoTYQgAACDK9uyRmpsLqwxJPuAE+4GyaWvz1aMy7xeSOipDYUZrS75NTlLWIQr19b46xACF6kQYAgAAiLJC7zEUOPZYnwRypYHnnpP27pVmzSrsa/Sg5jzb5Jobp8qZacim57Oe09hIZaha1ZV7AQAAAChCsWEoaH1bvlw66yxp/vyu5zz+uH88+eTCvkYPat6XqgyFuM+QJCUb+mvX8Eka+urKrOeMGkUYqlZUhgAAAKJs3Tr/OH58Ya8PWt9y7RtqapKGD+8YxV1GB9rkQu4ZkqQdh0zPGYaoDFUvwhAAAECUBWFowoTCXh9MiFu6NPs5TU3SSSflfx+jEmhu8QMUwrbJSdKOQ47UkE2rpPb2jM83NrJnqFrRJgcAABBla9dKgwd3zIguxIknSgsXZn5u3z7finf11YVfvwcFbXKDQrTJTX/Mt/z13bVZ9Ym9Ov7Bb2r/wBFaeca8g85rbJS2bvW3IqqAvIdeRGUIAAAgytauLbwqFDjzTD8tLlOv2OrVPiWcckpxX6OH7GxpUP+GVtXVZr6JaiYtgw+RJPVvfjXj842NUmurtHNnjywREUIYAgAAiLJ16wrfLxSYM8c/PvZY1+eWLfPzp884o7iv0UOa99Xn1SInSXuH+OES/bKEoVGj/CP7hqoPYQgAACDKeqIydOKJ0oAB0iOPdH1u+XLpiCOk/v2L+xo9pLmlIfQkuUBrn4FqbRig/juzV4YkwlA1IgwBAABEVSIhbdpUfGWovl469dSuYWjTJj9ZIBi/XQF2tjSEvuHqAWbaM3ScBu5Ym/HpIAwxRKH6EIYAAACiav16/1hsZUiS3vhGXwVamxYYlizxj8H47QpQSJucJO0ePkEDXlsntSe7PEdlqHoRhgAAAKKq2HsMpbvySqlfv47qUGur9PDD0rRp0siRxV+/h+wsoE1OknYPn6jaZKv6N2/q8hxhqHoxWhsAAETH/Pldj82b1/VYtQiqOD1RGRo2THrPe6Rf/MJXiZYs8ePVrrqq+Gv3oOZ9DYVVhoZNlCQN3P5Kl+f69ZMGDiQMVSMqQwAAAFHVk5UhSbruOqm2VvrKV6S77vKDE6ZN65lr9xA/QCH/MLR38Ggla+s18LWuYUjy1SHCUPUhDAEAAETVyy9LQ4cWd8PVdNOnS5/+tDRmjHTuudK111bUXUjb26Vd++vzH6AgSTW12jN0vAZuzz5EgQEK1Yc2OQAAgKh66SVp6tSeveaYMdKnPtWz1+whu3dLzllBbXKS3zc0qmmhLNkmV3vwj8GNjR3zKFA9qAwBAABEVSnCUAVrbvaPhQxQkKSdow5TXdt+jVj3zy7P0SZXnQhDAAAAUdTWJq1ZU1VhaOdO/1jIniFJ2jnqcEnSIS883uW5UaN8GHKu4OVFUktLx9azakQYAgAAiKK1a30gqqIwFFSGCm2TS/Qfpn0DRmjMi13DUGOjv4ftrl3FrDBadu+WzjhDOvLI6t0vRRgCAACIopde8o9VGIYG9yusTU7y1aFDXny8SwkouNdQtYSCtjbpne+UnnlG2rNHuv76cq+oPBigAAAAEEVVGIaKbZOT/L6h0U0LNfTVldox5sgDx9NvvHrYYcWssrJkujWXc9Jtt0lPPCFdfrn0/PPSDTdIo0f7+y1V0627qAwBAABE0UsvSQ0N0tix5V5Jrym2TU6SXjvEB6AJzz540PH0MBR3//d/PghddJFvk7voIt8iuGBBuVfW+6gMAQAARNHq1dKUKf4mqVXiQGWoiDC0f+BI7Rk8RtMfv0mtDQMOHB91vi+HxD0MvfqqD0OzZ0tvfrM/NmaMdOKJ0l/+4m8vVU2oDAEAAETRCy/Eq58rhKAyNLBPW1HX2T7uGA3Z/IJqWvcdOFYte4aeecY/XnzxwffTDapDDz1UnnWVC2EIAAAgalpbpRUrpGOOKfdKelVzszSob0K1NcXNv35t7DGqaW/T0E2rDhzr399/xL0ytHixLygOG3bw8bFjpRNO8NWh7dvLs7ZyIAwBAABEzapVPhAdd1y5V9Krdu4sbnjCges0Hqa2+n4auXbxQcfjfuPVbdukV16RZs7M/PxFF0n79kk/+lHvrqucCEMAAABRs3Spf6yyMNTcXNxY7YCrrdPWCTM0cu0SWbLjesGNV+NqcSr7zZiR+flx46QjjpB+8YvqufksYQgAACBqli6V6uv9T65VpLlZGtIDlSFJ2jJplupaWzRs43MHjsW9MrR4sQ88o0dnP2f2bD+o8G9/6711lRPT5AAAAKJm2TLpyCN9IKoiO3dKQ4uYJJduxyFHqrVhgEateUrS8ZJ8GAqKbnHT3OxDzkUXHXx8+mMH34hoYmu97ur/Pt16q3Taab24wDKhMgQAABA1S5dWXYucc34sdE+FIVdTqy2TZvl9Q3v2SOqoDMWxReyf//S/r2wtcoH+9a1629ukO++UWlp6ZWllRRgCAACVbdcu6Xvfky69VLrrLmnt2nKvqLy2bJHWrauoMLRtdx+9+Qfn68LvXaDd+0rTeLRihd/8f+a0jT12zY2Hna6a9jbpH/+Q5MPQ/v3S7t099iUqxuLF0siR0vjx3Z97xRW+CvfAA6VfV7kRhgAAQOVauVI66STpYx/zP8099pj09a9LCxaUe2Xl8/jj/jFkD1Nb0rRqVen2wvxz7XDN+vol+tOK8VqwYrwu/P6F2rWr57/Offf5x4uPX9Nj19wzfIKaR0z2/02d06hR/njc9g21tPhvpZkzD763UDZveIPfW3TrraVfW7kRhgAAQGXaulU67zw/D/jhh6WmJumb35SOP166++7quztk4JFH/A1xZs3KesrufXW66tYzdPQXL1P/j7xf06dLhx7qfyDuSXfcIc3+5lvVmqzR45/8rW7/wMP6++rRuuCCjhuk9pT775dOPlkaN2xvj1534+FnSBs2SA89dODGq3ELQ8uWSclk9pHandXWSu99r/Tgg9KmTaVdW7kRhgAAQOVJJqXLL/c/if3hD9JZZ/njAwZI8+b5u0P++td+I0S1eeQRXxVqaMh6yv+792T9/G9HaGrjLn3i3KX66U+lvn2lyy47sD2mIPPnd3xcc400d650+NAt+sFZ92nf2i0avadJXzjtYS1c6Pem3HCDP7dYa9dKixZJb31r8dfqbPPkk6QhQ6RvfetAGNq8uee/Tjk9+aT/LU6ZEv41V1zhvw1/9avSrasSEIYAAEDl+cpXpD/9Sfr+96UTTzz4uZoa6f3vlyZM8DdEWb26LEssi61b/T/zz5lz4FB6QJk/X7r+znG68dGj9Y7pS/XJY/+oC0c8dSBbPvecdM45xQ8I2LNHuv12/xZ85+zfaXi/jp32Z05s0rx50ssvSzfe6O8NW6z77/ePl1xS/LU6c7X1Pmw/9JDGbXhKUrwqQ+vX+z8yp5/uv3XCOvJI6XWvk265JZ4DJQKEIQAAUFkefFD68pf9P01ffXXmc+rrpQ9+0P/67W+X9u3rvfWVU9AamBaG0u3dK31z4ZmaOPg1XXXcooOeO+ooP1Z54ULpZz8rbhn33uuHDFxxhVRf297l+ZkzpSuvlFat8nm1vespebn/fv/Decluq3TmmdLIkRr93U9JcrEKQw8+KPXp01FczcdVV/ni629+0/PrqhSEIQAAUDleecWXMI45xpcVcu32bmyU/uVfpGee8QMWqsFtt/lxYCefnPHpu+6Strf012dnP6I+dckuz190kQ8VH/6w9PTThS1h1Srpr3/1FaaJE7Ofd8opfgDgokXSddcVXl3Ytk169NHSVIUO6NdP+sIXVPfYXzR38O/12GMl/Fq9qKnJ//c/4wzfYdqd+padalzzlJ/eeO+9ev/F23TMMdJHP1pce2Ul46arAACgMuzf76s8bW3SPff4IQHdOf546VOf8oMVTjvNlyriauNG/8/8n/603+HeyT//Kf3979J7j16iI0dmLm3U1Ph/7f/e96Q3vlF64gnpsMPCLyGRkH75S59D3/zm7s8/7zw/ovmGG3zV6sgdx6pvfZsaatu1s6VBm5r7afOufurX0Kbrzlmmw0Z1nbrwu9/5vSul2C90kHnzpB/+UDe+eq0m/H6Z/v73wZo9u8Rfs8S+/W3/np9zTu7z+u7arClL7tPItYtlzklP+OP1DQ166JzLNfP3X9VXvjJW//VfpV9zbyMMAQCA8nPOV3eefNIHocMPD//ar37V3yfmmmt8f9axx5ZuneV0yy2+3+zKK7s8tW6ddPPNfg/Plcc+k/MygwZJf/yj9PrX+7DyxBPSmDHdf3nn/HjrzZulf/u3nPMbDjDzQxsmTJBuukmSDk4XDXVJjRrUom27++qmx4/UVa9fqc9f9IzGDu2YGHfffb4YlmN4Xs9oaJBuvlmDX/96/aTvx/TZz9ysP//FQo2irkSvvur/TJxyijR0aJaT2ts1bsUCTVlyv1xNrdYeeZ62TpqlE37+Eb8X71e/0uj587W67tf62Le/q+fee5WOOjqi/0GyIAwBAIDy+/rXpZ/8xFc9Lr00v9fW1fnd/CecIL3tbb48MmJEadZZLlu2+OrXuedK06Yd9NT27X7ORN++0rXXSvXLu9+gM326H9L3hjdI55/vb9+U9QdmSTv2Nuj9b5P+/Ge/vWb69PBLr6mRZs/2YWbKoz9XIlmn1vYaDahPaEB9q8ykbS39dNvyE/Szv07Xz5+YptPHr9HcWunUU31wu+qqcPfHKdrs2bLPflZzv/pVPfnocXr44X/rtqpSqf7nf/zwivPPz/z8wK1rNOeW92ns849o6/jj9cJJl6u13xD/5OjR/mP2bOnjH1fN++bpJ49frb+fcb/csptkY0Ok54iouD1DZnaBma0ysxfN7NPlXg8AACih9nbps5+V/vM/pfe8R/ra1wq7ziGHSHfe6fccnX66H2UWF85Jn/ykn1hwww0HPbV9u29527/f7+sYPjz8ZV/3Oj+YYNUq6eyzfeFp27au5z398kid8LVL9cADvotx7tzCfhv19dLAhlYN79ei0QP2aGBD64GAM6Jfiz7+uid025vu0rmTX9DiTWP1gQ/4oQ8tLSXeL9TZl76k5Fsv1Xd1nZa//zuRnKT24ot+y93b364DN5INWLJNxy64Xm//0tEa+fIirTrlCj13xr92BKHOpk5VwyML9MQ7b9CM7Q9r3+HHqP1Xd8RmxFxFhSEzq5X0Q0kXSjpK0lwzO6q8qwIAACXx7LP+p/BvfMNPjfv5z/Ob/dvZ6af7PTXr1vm9RD/9ac/MdS6ntjbp3/9duvVWXzU78sgDTz3/vPSWt/ii0bXXSuPG5X/5c87xGXLzZj+LYtQoac71b9I75p+ts75zkY778ts0+5sXqy1Zo8ce8+eXskIzdtAu/b9THte9l/5Szz7rg95//IcfANBrampUe/v/qmnW2/XxtZ/QxtmX+EkEEdDW5vcJBZ2in/tcx3OWbNPkZ+7VJV+fpdl3f1Ibpp+tX3/xWW2aelr3b2pNjWb/6qP6+BmLtWzvVNVcPle7TzzTl+2KHRVYZpXWJneSpBedc6slyczukHSxpOfKuqo8Oef/haa52X/s3On/onr1Vb/3cfNmv4mwpcV/1NRIw4Yd/DF0aNdjQ4YU9/8IAKgEpfzHxFJdm+v2wLUTCWn1atlLL8pWPKeaBQ+q5pG/yA0erOSPf6rEe96v3dtNu3Yp48fu3alf//Vk1dW0a1j//Ro+IPXxqP//5PDh0qCZc1T/xGL1/eCVqrn6arkvfUl26aX+XkXTp/vNK/37+4/6+p78T5M/5zr+gwa/bmvzPzCsXy899ZTfaPPcc2q75sPaeu2XtWOln659221+e1Vdnb/lUqfOuby89a3SxRf7oXz33y/93y1+sMHIgfs0tbFZ50xfr/9442KNmH2lli3rid9498z8xLo+ffzEuptv7nhueoZJbyt7egF9+2rCE3fo2+Nm6SNPfkHtU3+rHSefr75vOlf9Zx7hp06MHOl7E/v2Lc8PaM4p2ea0ZbPTxvXtWvuK0ze+7rR4sdNlF+7V9Z/ZqtHbXtXOhxercc1TGrdigfrv2qydow7Tgnm/VtMJb8sr2dbUSD9+ZLpu+/nfdNfHfqbrFn9JAy+4QHtGTNDuU89X/9NmauBpx8sOGe3bVCPyg2ulhaFxktamfb5OUubZkRVm0iT/d1dbW/cBecAAaeBAP8Vx/35//t69fmRhrteadfyZTR8iExzL9pjtWE+rqv+px+y6pbw21y39tWPSqYCYu0Uf0BW67cDny3W07tBXdGPzv2r7NSOka8Jdp6HmaLWrRm3taT9k/bjzWVMlPa6L9DvNWzdf533vJ+qr/V2u1ao6tXX6Ucip6/8oOx/r/LnJHfjo/Hmm4zUK/027zI7Vl2vu0d0/vkT6ccfXPf54XwGYO9dPW8vX/PmZj0+YIN1wxr1djj/7jLQyy2viqq6hRsf98v9p5mXv1nt3/0hvX/hrHb7wDxnPTaheSXWd8Nfdn51Mf946/py0d/lzVKP2g/781Eo6JPUxU9Jbgif+kPqQdKqkPUPHauO0M/XiSe/WK8e9Wa6m61rDMJOueH+dXrvkg/rCZ96n7fPv1ju23aHTHrhXgx746cEnn3KK379X4cxV0P9Fzeztks53zn0g9fl7JZ3knPtI2jnzJM1LfXqEpFW9vtDKNlLS1nIvAr2G97u68H5XF97v6sL7XV14v3vfJOdcY+eDlVYZWidpQtrn4yVtSD/BOTdfUpX920R4ZrbIOVfq4ZOoELzf1YX3u7rwflcX3u/qwvtdOSqtke8pSYeb2RQza5D0Lkm/LfOaAAAAAMRQRVWGnHNtZvZhSX+Ub4O82Tn3bJmXBQAAACCGKioMSZJz7veSfl/udUQYLYTVhfe7uvB+Vxfe7+rC+11deL8rREUNUAAAAACA3lJpe4YAAAAAoFcQhiLAzPqa2ZNm9k8ze9bMvpThnIvNbKmZLTGzRWb2+rTn1pjZsuC53l098hXm/U4793VmljSzy9KOXWBmq8zsRTP7dO+sGoXqgfeb7++ICfl3+hwz25l6X5eY2efTnuN7PEJ64P3mezxCwv6dnnrPl6TOeTTtON/fvYw2uQgwM5M0wDm328zqJf1V0seccwvTzhkoaY9zzpnZcZLucs5NTz23RtIs5xzz7CMgzPudOq9W0gJJ++SHjdydOva8pHPlR9U/JWmuc+65Xv1NILRi3u/U8TXi+ztSQv6dPkfSJ51zb+r0Wr7HI6aY9zv13BrxPR4ZId/voZL+JukC59wrZjbKObeZ7+/yoDIUAc7bnfq0PvXhOp2z23Uk2wGdn0d0hHm/Uz4i6R5Jm9OOnSTpRefcaudcQtIdki4u5XpRnCLfb0RQHu95JnyPR0yR7zciJuT7/W5J9zrnXkm9Jvh7ne/vMiAMRYSZ1ZrZEvkfhBY45/6R4ZxLzGylpN9Jen/aU07Sn8zsaTOb1ysLRlG6e7/NbJykSyT9uNNLx0lam/b5utQxVLAi3m+J7+9ICvN3uqTZqVabP5jZ0aljfI9HUBHvt8T3eOSEeL+nSRpmZo+k3tcrUsf5/i4DwlBEOOeSzrkZksZLOsnMjslwzn2p1ri3SvpK2lOnOedOkHShpA+Z2Rm9sGQUIcT7/T+SPuWcS3Y6bpku1/MrRE8q4v2W+P6OpBDv+TOSJjnnjpf0fUn3p47zPR5BRbzfEt/jkRPi/a6TdKKkiySdL+lzZjZNfH+XBWEoYpxzOyQ9IumCHOc8JmmqmY1Mfb4h9bhZ0n3yZVhEQI73e5akO1K95JdJ+pGZvVX+X5EmpJ03XtKGUq8TPaOA95vv74jL9p4755qDVpvU/ffqU3+n8z0eYQW833yPR1iOv9PXSXrQObcntRfsMUnHi+/vsiAMRYCZNaY228nM+kk6R9LKTuccltq0JzM7QVKDpG1mNsDMBqWOD5B0nqTlvbh85CnM++2cm+Kcm+ycmyzpbknXOuful99sebiZTTGzBknvkvTbXlw+8lTM+833dzSF/Dv9kLS/00+S///1NvE9HjnFvN98j0dPmPdb0m8knW5mdWbWX9LJklaI7++yqCv3AhDKGEm3pKaM1MhPivs/M7tGkpxzP5b0NklXmFmrpBZJ73TOOTMbLem+1N+xdZJ+5Zx7sCy/C4QV5v3OyDnXZmYflvRHSbXyU8ee7Y1Fo2AFv9+S+P6OpjDv+WWS/tXM2uT/Tn9XakgO3+PRU/D7zf/DI6nb99s5t8LMHpS0VFK7pJ8655ZLEt/fvY/R2gAAAACqEm1yAAAAAKoSYQgAAABAVSIMAQAAAKhKhCEAAAAAVYkwBAAAAKAqEYYAAJFkZnPM7NRyrwMAEF2EIQBAVM2RRBgCABSM+wwBACqKmV0h6ZOSnPxNCe+S9J+SGiRtk3S5pH6SFkpKStoi6SOShnY+zzm3ycwaJf1K0gj5O7xfIOlE59xWM3uPpI+mXvMPSdc655K98zsFAJQbYQgAUDHM7GhJ90o6LRVWhsuHoh3OOWdmH5B0pHPuE2b2RUm7nXP/nXrtsCzn/UDSeufcN8zsAkl/kNSY+viWpEudc61m9iNJC51zt/b27xsAUB515V4AAABpzpJ0t3NuqyQ557ab2bGS7jSzMfIVnKYsrx2f5bzXS7okdb0Hzey11PGzJZ0o6Skzk3y1aXPP/5YAAJWKPUMAgEpi8pWgdN+X9APn3LGSPiipb5bXZjvPcnytW5xzM1IfRzjnvljU6gEAkUIYAgBUkoclvcPMRkhSqk1uiKT1qeevTDt3l6RBaZ9nO++vkt6Rut55koalfa3LzGxU8LXMbFLP/VYAAJWOPUMAgIpiZldK+nf54QiLJd0n6bvyQWehpNc55+aY2TRJd0tqlx+gMDzLeaMk3S4fgh6V9E5JU5xz+83snZI+I/+Pg62SPuScW9hrv1kAQFkRhgAAsWZmfSQlnXNtZjZb0o3OuRllXhYAoAIwQAEAEHcTJd1lZjWSEpKuLvN6AAAVgsoQAAAAgKrEAAUAAAAAVYkwBAAAAKAqEYYAAAAAVCXCEAAAAICqRBgCAAAAUJUIQwAAAACq0v8HPgkfPTqJjYkAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "l = ['amount','age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", + "for i in l:\n", + " plt.figure(figsize=(14, 8))\n", + " sns.distplot(data[df['fraud'] == 0][i],color = 'blue')\n", + " sns.distplot(data[df['fraud'] == 1][i],color = 'red')" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for i in ['gender', 'category']:\n", + " plt.figure(figsize=(20, 10))\n", + " sns.barplot(x = i,\n", + " y = df['fraud'],\n", + " data = data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the numerical column the values which were fraund and those which were not visibily seperated after a certain value, clearly showing patterns with the exception of age column. The gender column is an interesting one as it tells that the number of females being cheated is significantly higher" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "#adjusting skewness\n", + "import numpy as np\n", + "data['meramt'] = np.log((data['meramt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "data['catamt'] = np.log((data['catamt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "data['custcat'] = np.log((data['custcat'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "data['custamt'] = np.log((data['custamt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "data['mercat'] = (data['mercat'])**(1/3)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "data['catage'] = (data['catage'])**(1/3)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['step', 'customer', 'gender', 'merchant', 'category']\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "filtered = data.dtypes[data.dtypes == np.object]\n", + "colname = []\n", + "colname = list(filtered.index)\n", + "print(colname)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "data = data.drop('fraud', axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "data_num = data.drop(colname, axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat = data[colname]" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SimpleImputer(strategy='median')" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.impute import SimpleImputer\n", + "imputer = SimpleImputer(strategy=\"median\")\n", + "imputer.fit(data_num)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "data_imp = imputer.transform(data_num)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "data_tra = pd.DataFrame(data_imp, columns=data_num.columns,\n", + " index=data.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "StandardScaler()" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "scaler = StandardScaler()\n", + "scaler.fit(data_tra)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "scale_train = scaler.transform(data_tra)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "data_sc = pd.DataFrame(scale_train, columns=data_tra.columns,\n", + " index=data_num.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat = data_cat.drop(['customer', 'step'], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat_encoded = pd.get_dummies(data_cat)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "data_join = pd.concat([data_sc, data_cat_encoded], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(25200, 74)" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_join.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Above we have imputed and scaled the features, imputation is not necessary in this case as there is no missing value present, yet I have used it just to show end-to-end data science pipeline as asked in the task.
\n", + "After this we have one-hot encoded the categorical features and dropped customer and step colimns as given in the assignment notebook" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "y = df['fraud']\n", + "X_train, X_test, y_train, y_test = train_test_split(data_join, y, test_size=0.75, random_state=42,stratify=y)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestClassifier(class_weight='balanced', criterion='entropy',\n", + " random_state=42)" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "forest_reg = RandomForestClassifier(criterion='entropy', class_weight='balanced', random_state=42)\n", + "forest_reg.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "y_pred = forest_reg.predict(X_test)\n", + "y_prediction = forest_reg.predict_proba(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.9971902606310015\n", + "[[13272 228]\n", + " [ 142 5258]]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.metrics import roc_auc_score\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "if df['fraud'].nunique()> 2:\n", + " rules_score = roc_auc_score(y_test, y_prediction[:,1], multi_class = 'ovo')\n", + "else:\n", + " rules_score = roc_auc_score(y_test, y_prediction[:,1])\n", + "\n", + "print(rules_score)\n", + "\n", + "from sklearn.metrics import confusion_matrix\n", + "cf_matrix = confusion_matrix(y_test, y_pred)\n", + "print(cf_matrix)\n", + "\n", + "import seaborn as sns\n", + "sns.heatmap(cf_matrix, annot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As seen above just with simple feature engineering we reduced 79 false positives and improved roc score. Let's use regularization by cross validation to see what happens" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "def display_scores(scores):\n", + " print(\"Scores:\", scores)\n", + " print(\"Mean:\", scores.mean())\n", + " print(\"Standard deviation:\", scores.std())" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scores: [0.99759259 0.99767215 0.99580316 0.99845885 0.99724417 0.99762346\n", + " 0.99698217 0.99722977 0.99861934 0.99639575]\n", + "Mean: 0.9973621399176956\n", + "Standard deviation: 0.0008087641314100779\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import cross_val_score\n", + "forest_scores = cross_val_score(forest_reg, X_test, y_test,\n", + " scoring=\"roc_auc\", cv=10)\n", + "display_scores(forest_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[13288 212]\n", + " [ 130 5270]]\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import cross_val_predict\n", + "from sklearn.metrics import confusion_matrix\n", + "cm_score = cross_val_predict(forest_reg, X_test, y_test, cv=10)\n", + "conf_mat = confusion_matrix(y_test, cm_score)\n", + "print(conf_mat)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see that with 10 fold cross validation we get the roc score with a maximum value of 0.99861934 and reduce the number of false positives to 212" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The hyperparameters for this model were tuned using Random Search, and gave an roc score of 0.99989934 however it worsened the false positive number, which is why we have chosen the base model itself" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From 83db3e7812bc2b0f6a301e296238300e7f2b3d68 Mon Sep 17 00:00:00 2001 From: Cheril Shah <79891166+Cheril311@users.noreply.github.com> Date: Fri, 15 Oct 2021 10:15:19 +0530 Subject: [PATCH 2/3] Delete datarobot_CherilShah.ipynb --- datarobot_CherilShah.ipynb | 2185 ------------------------------------ 1 file changed, 2185 deletions(-) delete mode 100644 datarobot_CherilShah.ipynb diff --git a/datarobot_CherilShah.ipynb b/datarobot_CherilShah.ipynb deleted file mode 100644 index 5d6a190..0000000 --- a/datarobot_CherilShah.ipynb +++ /dev/null @@ -1,2185 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## DataRobot Internship Task" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Loading the dataset:" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "data = pd.read_csv(r'sampled_data2.csv')\n", - "df = data.copy()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Noting the feature names for directly manipulating or analyzing these. " - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['step' 'customer' 'age' 'gender' 'merchant' 'category' 'amount' 'fraud']\n" - ] - } - ], - "source": [ - "print(data.columns.values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "preview the data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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22021-06-03C168158960026to35FemaleM348934600Transportation43.760
32021-07-01C125174929436to45FemaleM1823072687Transportation41.570
42021-03-06C170534621636to45MaleM348934600Transportation42.970
52021-03-27C3467668626to35MaleM348934600Transportation32.610
62021-03-18C76036840536to45MaleM980657600Sports&Toys410.671
72021-07-16C165503714726to35FemaleM480139044Health16.451
82021-05-13C178945787226to35FemaleM3697346Leisure300.621
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" - ], - "text/plain": [ - " step customer age gender merchant category \\\n", - "0 2021-07-16 C1326593353 36to45 Male M1823072687 Transportation \n", - "1 2021-08-22 C483912131 26to35 Female M1198415165 Beauty&Wellness \n", - "2 2021-06-03 C1681589600 26to35 Female M348934600 Transportation \n", - "3 2021-07-01 C1251749294 36to45 Female M1823072687 Transportation \n", - "4 2021-03-06 C1705346216 36to45 Male M348934600 Transportation \n", - "5 2021-03-27 C34676686 26to35 Male M348934600 Transportation \n", - "6 2021-03-18 C760368405 36to45 Male M980657600 Sports&Toys \n", - "7 2021-07-16 C1655037147 26to35 Female M480139044 Health \n", - "8 2021-05-13 C1789457872 26to35 Female M3697346 Leisure \n", - "9 2021-07-23 C477542874 26to35 Female M85975013 Groceries \n", - "\n", - " amount fraud \n", - "0 15.78 0 \n", - "1 608.32 1 \n", - "2 43.76 0 \n", - "3 41.57 0 \n", - "4 42.97 0 \n", - "5 32.61 0 \n", - "6 410.67 1 \n", - "7 16.45 1 \n", - "8 300.62 1 \n", - "9 47.47 0 " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.head(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "get basic information of the dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 25200 entries, 0 to 25199\n", - "Data columns (total 8 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 step 25200 non-null object \n", - " 1 customer 25200 non-null object \n", - " 2 age 25200 non-null object \n", - " 3 gender 25200 non-null object \n", - " 4 merchant 25200 non-null object \n", - " 5 category 25200 non-null object \n", - " 6 amount 25200 non-null float64\n", - " 7 fraud 25200 non-null int64 \n", - "dtypes: float64(1), int64(1), object(6)\n", - "memory usage: 1.5+ MB\n" - ] - } - ], - "source": [ - "data.info()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that we have 8 columns, each column has 25200 non-null rows, this can mean that their is a high probability that the dataset has no null values, but it's better to check. Of the 8 columns/features only 2 are numerical while the rest are categorical." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "checking for null values" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "step 0\n", - "customer 0\n", - "age 0\n", - "gender 0\n", - "merchant 0\n", - "category 0\n", - "amount 0\n", - "fraud 0\n", - "dtype: int64" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.isnull().sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "this shows that there are no null values in the dataset" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " step customer age gender merchant category\n", - "count 25200 25200 25200 25200 25200 25200\n", - "unique 180 4061 8 4 48 14\n", - "top 2021-06-18 C1350963410 26to35 Female M1823072687 Transportation\n", - "freq 177 147 7984 14596 9192 15925" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.describe(include = 'O')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It can be noticed that the age column has varied values thus scaling is required. Also the gender column might have an unknown attribute as it has 4 unique values or it might be some human error which needs to be corrected. Also there are many values of the same attribute (female in gender and transportation in category) which might lead to skewed results without techniques for addressing overfitting." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['Male' 'Female' 'Enterprise' 'Unknown']\n" - ] - } - ], - "source": [ - "#checking the attributes of gender\n", - "print(data.gender.unique())" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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categoryfraud
7Leisure1.000000
13Travel0.993127
10Sports&Toys0.971569
6HotelServices0.935154
8OtherServices0.908367
5Home0.870317
4Health0.796992
11Technology0.738318
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" - ], - "text/plain": [ - " category fraud\n", - "7 Leisure 1.000000\n", - "13 Travel 0.993127\n", - "10 Sports&Toys 0.971569\n", - "6 HotelServices 0.935154\n", - "8 OtherServices 0.908367\n", - "5 Home 0.870317\n", - "4 Health 0.796992\n", - "11 Technology 0.738318\n", - "0 Beauty&Wellness 0.605907\n", - "9 Restaurants&Bars 0.405405\n", - "2 Fashion 0.362500\n", - "12 Transportation 0.017582\n", - "1 Contents 0.000000\n", - "3 Groceries 0.000000" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data[[\"category\", \"fraud\"]].groupby(['category'], as_index=False).mean().sort_values(by='fraud', ascending=False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This shows that high spending categories like leisure, travel, sports and toys have been involved in fraud most number of times, with leisure purchases always being fraud. This means that fraud is likely to be nicely correlated to a combination of category and amount" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "sns.distplot(data['amount'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The distanceplot of amount is extremely left skewed and the frequency of values starts becoming very less from around 1000" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As seen in the data description, the age column has object values of a particular age band, let us replace that with the upper limit of the groups " - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:670: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " iloc._setitem_with_indexer(indexer, value)\n" - ] - } - ], - "source": [ - "for i in range(0, len(data)):\n", - " if (data['age'].loc[i] == '36to45'):\n", - " data['age'].loc[i] = 45\n", - " if (data['age'].loc[i] == '26to35'):\n", - " data['age'].loc[i] = 35\n", - " if (data['age'].loc[i] == '56to65'):\n", - " data['age'].loc[i] = 65\n", - " if (data['age'].loc[i] == '19to25'):\n", - " data['age'].loc[i] = 25\n", - " if (data['age'].loc[i] == '46to55'):\n", - " data['age'].loc[i] = 55\n", - " if (data['age'].loc[i] == 'gt65'):\n", - " data['age'].loc[i] = 100\n", - " if (data['age'].loc[i] == 'Unknown'):\n", - " data['age'].loc[i] = 0\n", - " if (data['age'].loc[i] == 'lt18'):\n", - " data['age'].loc[i] = 18\n", - "data['age'] = data['age'].astype(int)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Feature Engineering" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "data['meramt'] = data.groupby('merchant')['amount'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], - "source": [ - "data['catamt'] = data.groupby('category')['amount'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], - "source": [ - "data['custamt'] = data.groupby('customer')['amount'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "for i in range(0,len(data)):\n", - " data['customer'].loc[i] = data['customer'].loc[i].replace(\"C\",\"\")\n", - " data['customer'].loc[i] = int(data['customer'].loc[i])\n", - "\n", - "for i in range(0,len(data)):\n", - " data['merchant'].loc[i] = data['merchant'].loc[i].replace(\"M\",\"\")\n", - " data['merchant'].loc[i] = int(data['merchant'].loc[i])" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "data['mercat'] = data.groupby('category')['merchant'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "data['custcat'] = data.groupby('category')['customer'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], - "source": [ - "data['catage'] = data.groupby('category')['age'].transform(lambda x: x.mean())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The first three features are based on previous observations of dependence of amount with the other features. The last three features might seem funny but are based on correlation and might make sense mathematically.
\n", - "Let's revisualize the correlation plot" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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FRxMXE8PAgQN5uUC/duaMGfS9//6yDrtUNbu1ITWq2+h2x9OMHvUhAwY+VGy5739YxZ3d+9GzR3/Kly9H164tAfhl3Rbu6fU8vXu/wMgR7/HiEO/88FYEnExgGIZRJM1X3L6ydF3DBhw6eJAjhw6RnZXFgrnziG3bulCZEykpbNu8hezsrAuu6+natmnDrJkzAdiwYQMBgYGEhYcXKdesWTPmz58PwMyZM2nbtu0F1fdUbdu0ZdbMWcCf8QcQFh5WpFxJ7U9JSWHz5s1kZ2WXXdClpH7Dhhw8cJBDhw6RlZXFd3Pn0rpN20JlWrVpy+zc87PpvPMTYbMR27IlM776qsxjLy2tW7dk9mzHG9ONGzcTGBhAWFhokXJNm97C9987PnGZNfMb2rRpBTg+pa9UqRIAFStWJC01jexsz78XLBG1yUlNwExPghw72btW43NF48KFTBPD18/xfTk/zMxTkJMDgP3oDse2F2tcL5qggIolHl+ybjtdYxthGAYN69Qg/XQmScfT2bznMDUjQ6huq0I5Xx86Nq/PknU7yjDyixdyXR1OHTrK6SMJ5GRnc3DBcqJimxUpd3Wv2zm05Ecyj6eWfZAudDnf/5dz2wGqXFeH04ePcuZIPGZ2NocXLCcy9tYi5a7s2ZUjS1ZxtoR7P/zmRpw+fJSM+CQXR1z6WrZszpxvFwCwefN2AgL8CQ0NKVLu9x27OXo0ocj+jh1bs3jRSuJz237ci34/NGjYkIMHDuT1e+bOnUubNm0KlWlToF+7ccMGAgv0a9etW0dqampZh12qYmIa8938lQBs3bqbgIBKhIRULlJu9U8b877ftm0P4RFVAMjIOJu3v0KF8pha0EG8mLMjMGYWs+/r0gzkQoVHRJBwND+7nBifQHhEhMvreooIm42jR4/mbSckJGA7rw3BwcGkp6djt9sBiI+PJ8Jmc7q+J4uwRRQTv61QmeLb7z1tLEmELYKE+AJtL6ZdEbYIEgqcn8SEBCJyz8/gYUMZN3oMOTne+9crwhbO0fj8DlpCQiI22/n3f2VOpp/Mu/4JCYl59/hnU6ZS+8orWLN2BfO//5YRI0djesFfc0ulKuScSsnbzjmVguFfpVCZc5t/wFKlGpUefJ9KvV4nc9VkLqelpxKPp2MLzR82bQsJJPF4OokpadhC8vdHhASReDzdHSH+YxXCQzmdkJy3fSbxGBXDQ88rE0JUXHP2zJhX9D8wTeLeHUv7L97hyu4dXB1uqbuc7//Lue0AfmGhZCTkJx0ykpLxCw85r0wIVeNuZf/Xxdz7uaLaxXF4wTKXxelK4eGhJBQ4B4mJyUREFE3cl6RWreoEBgYw+ZPxTJ/xIV26tHNFmC5hs9mIj8/vtyfEx2OzFe7zRdhsxBfo98R7Wb/274SFBZOYkP87ICkxhfDwKiWWt1qtdOjQgjWrN+Xti41tzIyv3+DNtwYwcsS7Lo33UpSDeUl+eaO/fAqJYRjXAPWAIMMwCk4YDAT8/qLeI8AjAFFVQgkJCCyFUIv8jCL7nH3/cTF1PUXxbTCdLuNMfU92se33Zgb/vO2xLVuSkpLCtq1bublJE5fF6Gr/+Prn/qK+rUVztu/4nd69H6BmzRp8OuUjOv1yB6dOnXZNwKWlmDad/8vLp0YDcpIPkjF7BEZQBBVvH8LpI89BVkYZBelexb3EDcMo9k90MWfTszlx39/43GNsHP8RZu4n7wUt6tuPjOQUygdXpuV7Y0nff4jk9VtcFm6pu5zv/8u57VBC+wtv1u//GFvf/ihv1EmR/8LHB1uLpmyb8JELAnS9i+3TWK1W6ta7moce7Ef58uX54st32bRpGwcPHi7NMF2iuN/Vl0uf708X2r4BAx5iw/odbNz4e96+5ct/YfnyX2jU6FoefbQHjz/uXdPHRf70d49RrQN0AioDnQvsPwmUuPKhaZofAB8ANKx1pUt+eyQmJGCrGpm3HRFpIznJufnMF1PXnfrcdx+9ejoWrtq0eTNVq1bNO2az2UhMKjwk8vjx4wQGBmK1WrHb7URGRpKU6GhnQnz839b3NH3u60Ovnr0A2LR5UzHxF76Gxbffs9vojISEBGyRBdpeTLsS4hOwFTg/ETYbSUmJtO/QgVatWxMTG0f58uXxD/Dn1bfe5Ln/9iuz+P+pe/v0okePuwDYsnkLVSNt/DnD32aLIDHx/Pv/BAGBAXnXv2CZO++8g/fec3RiDx78g8OHDnPFFVewebNnv5nLOZWCr3/+p44W/xDM0ycKlfGtG8e5374BwExLJCc9CUuVquQk7i3LUN3GFhJIwrG0vO2ElHTCgwPIyraTkJK/PzEljfAqpZ9cd6WMxGQq2fKnylWMCCUjOaVQmSp1r+LWVwYBUL5yEFWbN8a02zm8bHVe2bMnUjm87CdCrqvjVQmMy/n+v5zbDpCZlEwFW/401wrhYWSed+9Xrns1jccMBhz3vq35zZh2O/HLVwNgu/VmUn/fXeL0Ek/Uq9cd3HlXJwC2bvkdW4FzEBERRlJSSklVi0hMTOZEahoZGZlkZGTy66+bqHNNba9IYMQnJBAZmd9vt0VGkphYuM+XEB9PZIF+T6QX9Gv/zl13taVrV8fU1+3b9xJhC4HcARXhESEkJ58ott7D/76TysGBjB79erHHN2zYQbWoCIKCAkhLO+mS2EVc6S+nkJim+a1pmg8AnUzTfKDA11Omaa4uoxiLtW3TZmrUqkXVqCh8fH1p17kTKxYtcXldd/psyhQ6dOhAhw4dWLhwId26dwegUaNGnDx5kuRiflGvWbOGDh0cQ4W7d+/OwkWLAFi0eLFT9T3JZ1M+O6/9jkFB+fEnF6lTtP3evQI1wJZNm6gVXYuo6lH4+vrSsXNnluRe1z8tXbyIO3LPT4NGjTiVe35eHzeOFk2a0rJ5c/o9+SRrV6/2iuQFwOeffUnnTt3o3KkbCxct4Y47HKvwN2xY33H9k48VqbN27Tr+9S/H+iDdundl8eKlABw9Gk+zZo4RKCGhIURfEc2hQ4fKqCX/XE7iXiyVIzECw8BixefqZmTv/7VwmZPHsEZdD4BRIQhLcFXMNM9+bZemlo2v5ZvlGzBNk407/yCgoh/hVQK5vnY1DsQf41Dicc5lZfPdj5tp2bj4p9d4qpRtOwmoUY1KVW1YfHyo2S6WIyvWFCozp+N9zOnQhzkd+nBo8Sp+GT2Bw8tWY/Xzw6diBQCsfn7Ymt5I2p4DbmjFP3c53/+Xc9sBTmzbiX/1alSsasPw8SGqXSzxKwp3Qxd27sPCTveysNO9HFm8ko1j3s5LXgBEtfe+6SNffjmb7t0eonu3h1iyZBVdbndM+6hfvy6nTp7m2DHnExhLl/7IjTfWx2q14udXnvr1r2Xf3oOuCr1Ubd60iVrR0URVr46vry+dO3dm8Xn9nsUF+rUNvaRf+3dmzFhI794v0Lv3Cyxf/gsdO7QA4LrrruLUqTOkpKQWqXP77S1p2qQ+Lw4eX2iERlRU/nSaOnWi8fX1UfJCvNbfjcD40x7DMAYBtQrWMU3zQVcE5Qy73c7YoS/x7pRPsFgtfDv9a/bu3s2dvR2f0H899UtCwkL5Ys43VPL3xzRNej/Yl25t2nP61Kli63qTZUuXEhcXx4qVK8nIyOC5/v3zjk3+5BNeeP55kpKSGDtmDBMmTuTZ/v3Ztm0b06dN+9v63mDZ0mW58a/Ijf+5vGOTP5nMC8+/kNv+sUyYOIFn+z+b2/7pAISFhTFn7hz8/f0xc0wefPBB2rRuw6lTnr/Imd1uZ8TQoUyaMgWr1crX06ezZ/duevbuDcBXU6eyfOkyYuLiWJx7fgYWOD+XguXLVhIb24Kly34gMzOTF54fnHds0sfvMXDAEJKSkhn3yuuMf/s1nnnmabZt38GM6Y7lfCZOeJdxr45m/vffYGAw7pU3OHEi1U2tuQBmDpkrPqZil8FgsZC1fRk5xw/je51jMbOsrYs498tM/Fo/RsVer4EBZ1dPxcx0dFL82j2NtVpdDL8AKj3wLud+nk7Wdu/q0D/zxles27qfEydP0+LhsTzZszXZueuc9Gp3CzE31mHF+p20eex1KpT3ZfQTjg6tj9XK0Ie78PCIydhzTLq3upGranjX/GjTnsOvYycS9+4YDIuFfd8uIG3vQWrf6fiEds9fzP33C6lMizeGA2D4WDn4/TLiV/9aYnmPdDnf/5dz23Hc+5temcCt74wFi4WDc37g5L6D1OruuPcPzCz53gew+pUn/JYb2TDqrTKI1jVWrlxLixZN+f6HL8nMPMuLg8fkHXv3vXEMHfIKyckp9L63Ow8+2IvQ0CrM/mYyK1euZdjQcezbd5Aff/yZ2d9MJicnh5lff8eePfvd2CLn2e12hg0dypQpU7BYrcyYPp3du3dzT26/54upU/P6tctz+7XPF+jXjn/7bZo0bUpwcDCr167lrTffzOsPe4ufftrArbc2YvY348nMPMeIl/LXsHhr/ABeHvk+x46dYMDAh0lISObjjx3TQ5YtW8dHH82kZatb6NihBdnZdjLPnmPQwLfc1BLvdelMSPJ+hjPzwwzDWA2sAn4D7H/uN02zuMU9C3HVFBJvkGp6/lMNXMvrZpiXqnLuDsDN7NaSnxRxOdjY77q/L3SJCmjZw90huNUXvd9zdwhu1fmhYHeHIG6yePJxd4fgVi9mnnN3CG515rR3jOhwldAw711brDT88uu0S7rjX6dmrUvyPe3Ogwe87ro5OwKjommaL7g0EhERERERERGREjj7GNV5hmF43zPXREREREREROSS4OwIjKeBQYZhnAWycMwNME3T9K4l3EVEREREREQuwCU5f8RLOZXAME0zwNWBiIiIiIiIiIiUxKkEhmEYLYrbb5rmytINR0RERERERESkKGenkBR8BqMfcDOOJ5K0LPWIRERERERERETO4+wUks4Ftw3DqA6Mc0lEIiIiIiIiIh4iR6tgeAxnn0JyvsPAdaUZiIiIiIiIiIhISZxdA2MC+YuvWoCGwCYXxSQiIiIiIiIiUoiza2D8WuD7bOBL0zR/ckE8IiIiIiIiIiJFOLsGxqeGYZQDrs7dtdN1IYmIiIiIiIiIFObsFJJY4FPgAGAA1Q3DuF+PURUREREREZFLmZbw9BzOTiF5HWhrmuZOAMMwrga+BG50VWAiIiIiIiIiIn9y9ikkvn8mLwBM09wF+LomJBERERERERGRwpxexNMwjEnAZ7nbvYHfXBOSiIiIiIiIiEhhziYw/gM8DjyFYw2MlcD/XBWUiIiIiIiIiCfQGhiew9mnkJwF3sj9EhEREREREREpU06tgWEYRifDMDYYhnHcMIx0wzBOGoaR7urgRERERERERETA+SkkbwHdgC2maWoEjYiIiIiIiIiUKWcTGIeArUpeiIiIiIiIyOVEb4I9h7MJjOeB+YZhrADO/rnTNE2tiSEiIiIiIiIiLudsAmMUcArwA8q5LhwRERERERERkaKcTWBUMU2zrUsjEREREREREREpgVNPIQEWG4ahBIaIiIiIiIhcVsxL9MsbOZvAeBz4wTCMDD1GVUREREREROTSZxhGe8MwdhqGsccwjAHFHDcMw3g79/hmwzBucLbuP+HUFBLTNAMMw6gCXIVjHQwRERERERERuUQZhmEF3gHaAIeBXwzDmGOa5vYCxf6FI09wFXAL8C5wi5N1L5hTCQzDMB4GngaigI1AE2A10OpifriIiIiIiIiIeKSbgT2mae4DMAzjK+B2oGAS4nZgimmaJrDWMIzKhmFEArWcqHvBnF3E82mgMbDWNM04wzCuAV5ypuI5M+efxub1rO4OwM3sGO4Owa38jcv7DsgsX8XdIbiVT3iUu0Nwmy96v+fuENzqnqmPujsEt1rx7/HuDsGtzmQ527W69FxlO+3uENyqYlItd4fgVl9EnXN3CG41MOged4cgcsEMw3gEeKTArg9M0/ygwHY14FCB7cM4RlnwN2WqOVn3gjn7VzbTNM1MwzAwDKO8aZq/G4ZR52J/uIiIiIiIiIiUvdxkxQd/UaS4T6TPX/+zpDLO1L1gziYwDhuGURn4BlhkGMYJ4OjF/nARERERERER8UiHgeoFtqMomgcoqUw5J+peMGcX8bwj99vhhmEsA4KAHy72h4uIiIiIiIiIR/oFuMowjGjgCNATOH++1Bzgidw1Lm4B0kzTjDcMI9mJuhfsgidqmqa54mJ/qIiIiIiIiIh4LtM0sw3DeAJYgGOJx49N09xmGMajucffA+YDHYA9wBnggb+qe7ExXb4rTYmIiIiIiIj8rcv34QSmac7HkaQouO+9At+bwOPO1r1YltL8z0REREREREREXEEJDBERERERERHxeEpgiIiIiIiIiIjH0xoYIiIiIiIiIiW6fNfA8DQagSEiIiIiIiIiHk8JDBERERERERHxeEpgiIiIiIiIiIjH0xoYIiIiIiIiIiXSGhieQiMwRERERERERMTjKYEhIiIiIiIiIh5PCQwRERERERER8XhKYIiIiIiIiIiIx9MiniIiIiIiIiIl0RqeHkMjMERERERERETE4ymBISIiIiIiIiIeTwkMEREREREREfF4WgNDREREREREpET63N9T6EqIiIiIiIiIiMdTAkNEREREREREPJ4SGCIiIiIiIiLi8bQGhoiIiIiIiEgJDAx3hyC5NAJDRERERERERDyeV4/AaB7TgoHDhmG1Wvj6q2l89O57RcoMGj6MFnGxZGRkMqh/f3Zs3UatK67gjYkT8spE1ajOhDfe5LOPJ5dh9BenRUwMQ4YNw2q1Mu2rr3j/3XeLlBk6fDixcXFkZGTwfP/+bNu6lXLly/PV9OmUK1cOq48PP8yfz/g333RDCy7esOHDiItzXNv+/fuzbeu2ImWiqkcxccIEgioHsW3rNvr1e4asrCxu73o7jz76KABnzpzmxcFD2LFjR9k24CI0i2lB/6EvYrVamT1tOp+8+36h47WuvILhr77CNfXq8c5rr/PZh5Pyjg0bN4bbWrbkeEoKd7frUNahl5pBg56mRYumZGRmMmjQaHZs31WkzD33dOO+++6mRs0omjXtSGpqGgCNGzdi4jtjOHI4HoBFi1fw7v8+Kcvw/7Gfdicxbv52ckyTO26ozoMtahc6fjIzi8FfbyQhLYPsHJP7br2CrjdU58CxUzw/fUNeuSMnzvCfuKu5t1l0WTfhokQ2u4kbn38Mw2Jh7+zv2T55WrHlqtS7mrZT3uanF0ZxaPEqALrM/4zs0xmYOTnkZNtZ0Pvxsgz9og2cOJPlv/5OSFAl5o3/b5HjpmkyatI8VqzfiV/5cox9ojv1rqwGwMr1uxj18TxycnK4q3VjHukWU8bRl47gW26m9n+fwrBaiJ/7HYc+m1roeFCjhlz3ymgyjzpe28dWrOTg5E8xypWj4f8mYPH1xbBaSV62nIOTvOdvPkBo08Zc++wTGBYLh7+dz75Pvyx0vMoNDbjh9ZFkHE0AIHHZKvZ89JlTdb2B/41NiPy/Z8Bi4cSCORybMaVImUrX34DtkX4YPj7Y01PZ/8J/nK7rDZ7t35dbb21EZuZZXhr+Ljt37i9SZuTIJ7m27hVkZ9vZtm0Po0d9iN1up0XMTTz66N2YOSbZdjtvvP4pmzbtdEMr/pmAm5pQ9T/9MCwWjv8wh6RpnxU6Xqn+DUS/NI5zCUcBSPtxOYlTPwYgtFtPQtp3wcQkc/9eDr32MmbWuTJvw8X6vweup/EN4Zw9a+eNdzawd39aiWUfffB62sTVoHuf7wBocpONPj2vIceEHLvJ+59sYfvvx8sqdJFS5bUJDIvFwosjR/Bw7z4kJiQwbc63LFu8mL279+SVaREXS83oWrSPiaN+o4YMe/llena9gwP79tGtQ8e8/2f5z2tZsmChm1py4SwWC8NHjuT+3r1JSEhg9pw5LFm8mD27d+eViY2Lo1Z0NC1jYmjYqBEjXn6Z7l27cu7sWe7t1YszZ87g4+PDtK+/ZsXy5WzcsOEvfqLniY2LJTq6FrExcTRq1JBRL79M1653FCk3YMAAJk2axNy58xg16mV69Libzz+fyqFDh+hxdw/S09OJjY1hzJjRxdb3RBaLhRdGDOexe+8nMSGBz+fMYsWiJezfk3/vp6WmMm74COLatilSf+7Xs5j26eeMeOPVMoy6dLVo0YSaNavTvn1P6jeox7Ch/enZ85Ei5TZs2MLy5av5dMqEIsd++20Tj/3nhbIIt9TYc0zGzNvGe/ffQkSgH73f/5GYayK4Mjwgr8y0nw9yRbg/b9/bmOOnz9L17RV0rF+NWqH+TH/strz/p+1rS2hZN8JdTflHDIuFmwY+ydJHXyAj8Rjtpk7k8Io1pO/7o0i5hk8/TMKa34r8H0v+3Z+zqellFXKp6hZ3A/f+qwkvvD2j2OMr1+/iQHwKC995lk27DjH8g2+Z8cpj2O05jPhwDpOHPUhESCB3Pv8/Wja+htrVvev6Y7FwVf9+bH76Gc4mJXPDpA9IWfUjZw4cLFQsbdNmtj43oNA+89w5Nj35X3IyMjCsVhq+9w7H1/7MyW3by7IF/5zFQr3nn2bdE8+RmZhMs0/fJWnlak7tL9z2Exu28Nszg/9RXY9msVD1sefYP/hJso8lccVbn3By7SrOHsp/A2+p5E/k489zcMjTZCUnYg0KdrquN2h2a0NqVLfR7Y6nue66qxgw8CEe6PtikXLf/7CKIUMcf/NeHvUUXbu2ZObMRfyybgsrV/wKQO3aNRgz9r/cdeczZdqGf8xiodoT/dk34CmyjiVx1YTJpK1Zxdk/DhQqdnrLRvYP7V9on09IGKFd72bnw70wz52l5uCXqRzbhhOLvivDBly8mxqFUy2yEg8/uYQ6VwXzxL8b0G/QymLLXnVFZfwr+Rbat3FrMmv7O5KbtWoEMvCZm/i//y51edwiruC1U0iub9iAPw4c5PChQ2RlZfH93Lm0bFP4zVrLNm34duYsADZv2EhAYCCh4WGFyjS59Vb++OMgR48cKbPYL1aDhg05eOAAh3LbPm/uXFqf1/bWbdowe+ZMADZu2EBgYCBh4eEAnDlzBgAfHx98fH0xTbNsG1AK2rZpw6zca7sh99qGnXdtAZo1a8r8+d8DMHPmTNq2bQvA+t/Wk57ueBOzfv0GbJG2Mor84l3XsAGHDx7kyKFDZGdlsWDud8S2bV2ozImU42zfvIXs7Owi9dev+4W0tNQyitY1Wra8jW+//QGAzZu2ERDoT2hYSJFyO3bs5mjup5GXgq2HU6lepSJRVSri62Oh3fVVWf57YqEyhgGnz2ZjmiYZ5+wEVfDFaik8b/PnfceICq5I1coVyzL8ixZyXR1OHTrK6SMJ5GRnc3DBcqJimxUpd3Wv2zm05Ecyj6eWfZAu1LheNEEBJV+zJeu20zW2EYZh0LBODdJPZ5J0PJ3New5TMzKE6rYqlPP1oWPz+ixZ5z0jzv4UWPdaMg4fIfNoPGZ2NkmLlxByW3On6+dkZABg+Phg+PiAF/3tq1zvGk4fOkLGEUfb4xctJTym6L1f2nU9RYWr63L26GGyEo5iZmeTtnIRAU1bFCpTObYd6auXkZXs+J1oTzvhdF1vEBPTmO/mO96wbt26m4CASoSEVC5SbvVPG/O+37ZtD+ERVQDIyDibt79ChfLedPtTsU5dzh09zLnca5i6YhFBzZy/hobViqV8ebBYsZT3I+t4sgujdY0mjSNZsuIQADt3n6BSJV+CK5cvUs5igQf71GXSZ4VHJWdm2vO+9/OzetX19xiGcWl+eaESExiGYcw1DGNOSV9lGWRxImw2EuLj87YT4hMItxV+ExpuiyDhaH6ZxIR4IiIKl+nQpRPz58x1bbClLMJmI75Q2+OJOK/tETYbR48ezS+TkIAtwvFpm8ViYe78+axbv56fVq1i08aNZRJ3aYqwRXC0wLVNSIjHdt61DQ4OJj09Hbvd8Us7Pj6BCFvRTxx79OzB8uUrXBtwKQqLKHxfJ8UnEB7hZZ+kXqTwiFASEpLythMTkogID72g/6Nhw+uYNfsT3n//NWrX9o5pFEknM7EFVcjbjgj0Iyk9s1CZnrfUYn/yKdq8uoQ731nJc/+qi+W8BMaCLUf5V/2qZRJzaaoQHsrphPyO55nEY1Q877pXCA8hKq45e2bMK/ofmCZx746l/RfvcGV3750+VZLE4+nYQoPytm0hgSQeTycxJQ1bSP7+iJAgEo973yiUcmGhnE3Mf92fTU6mfFjRxHXgdfW48dOPuf71cVSMrpV/wGLhxk8m0ey7bznxy6+c3O49SRy/sFAyC7Q9M/EYfsW0vfL1dbl16ofcNH4M/lfUuqC6nsw3JJysY/nJ2uxjSfiGFG5DuWo1sPoHEj32f1w5/lMqt/yX03W9QVhYMIkJKXnbSYkphIdXKbG81WqlQ4cWrFm9KW9fbGxjZnz9Bm++NYCRI4pOPfZUvqFhnEvOv4ezkou/hhXrXs/V735G9Kg3KV/T8Xc9OyWZ5BlTufbzb6j31TzsZ05z6rd1ZRZ7aQmt4kdySkbe9rGUDEKrVChSrnP7K/j51wROpJ4tcqzpzZG8/1ZLXhrYhLfe9a6R1yIF/dUUktdy/+0G2IDPc7d7AQf+6j81DOMR4BEAW5UQgv0D/qr4P1LsSrDnpRONYrJKBUcb+Pr6Ete6NW++4l1D6YvNlV1A23NycujcoQMBgYG898EHXH311ezaVXT9AE/2d9fW2TJNmzahR4+7ubP7XaUboAs5065LXfHnwPn627fvpHWrOzlzJoMWLZowYeJo/tW+VylG6BrFtfH8U7F6TzJ1IoP48IEmHDp+hkc//ZkbalbB388xnDQrO4cVOxN5qs01ZRBxKXPi3r/xucfYOP4jzJycImUX9e1HRnIK5YMr0/K9saTvP0Ty+i0uC7esFX9/GBT30vDOz1z+/u/+qZ27WNvtbnIyMqjStAn1xo7mlx73OA7m5PBb34ew+vtz3ZiXqXhFNGf2eck0Aifu/fSdu1nepRf2jEzCmt3CDa+OYGX3+5yq6/GKu2HP/5tvtVKh9jXsH/g4lvLlueL1SZzZudWput7gQv/2DxjwEBvW72Djxt/z9i1f/gvLl/9Co0bX8uijPXj88ZddEmvpK+61X3gzY8/v7Li3KzmZGQQ0bkr08HH8/sBdWP0DCGzWgh33dcN+6iS1hoymcqv2pC75oWxCLy3FnoLCJ6FKsB/Nm1blhWE/FftfrFkXz5p18Vx3bQh9elzL4JGrXRGpiMuVmMAwTXMFgGEYI03TLDhOa65hGMVPusqv+wHwAUDdmtEu+SuRkBCPLTIyb9sWaSMpsfBQ6sT4BGxV88tE2CJJSsovc1tsLNu3biPl2DFXhOgyCQkJRBZqeySJ57U9IT6eqlWr8ucMcJvNRmJSUqEyJ9PTWbtmDS1iY70igdHnvj706tkTgE2bN1O1wLW12SJJTCp8Do4fP05gYCBWqxW73U5kpI2kAp9CXXPNNYx9ZSx973+A1NTUMmlDaUhKKHxfh0faSD7v2l6Ket3Tjbvu7AzAlq07sNnC845F2MJJSnb+dXz69Jm871euXMuQoc9SuXJQ3iKfnioi0I+EtPxPYBLTMwkL8CtU5tv1h3jwttoYhkGNkEpUC67I/mOnuT6qMgA/7k7imsggQvyLDj31dBmJyVSy5X/qVjEilIzklEJlqtS9iltfGQRA+cpBVG3eGNNu5/Cy1Xllz55I5fCynwi5rs4llcCwhQSScCz/Hk5ISSc8OICsbDsJKfn7E1PSCK8S6I4QL8q55GTKR+S/7suHhXH2vL/f9jP5r+3ja9ZyVf9++AQFkZ2W3377qVOkbthIlVtu8ZoERmZSMn4F2u4XEVqk7dkFfq8lr/6Zui88jW9QoFN1PV3WsSR8Q/NHGvqEhpN1/FiRMvb0VMyzmdjPZnJm6wb8oq9yqq6nuuuutnTt2gqA7dv3EmELgdwBFeERISQnnyi23sP/vpPKwYGMHv16scc3bNhBtagIgoICSEs76ZLYS1PWsSTKheXfw75h4UWmgeQUeO2f/GUNhtUHa2AQ/g1u5FzCUey5U2fTflxOpbrXe0UCo1O7aNq1rgnA7j0nCAvJH3ERGlKBlOOFR2BeGR1EpK0SkyY4phWXL2flowmtePjJJYXKbd2RQqStIoEB5Ug/6X2LmYo4swZGmGEYV/y5YRhGNOD2sXdbN22mZnQtqlWPwtfXl3917syyRYsLlVm6eDG3d+8GQP1GDTl58iTHkvJ/4XXo0pn5c9w+G+aCbd60iVrR0URVr46vry+dOndmyaJFhcosXryYO7p3B6Bho0acPHmS5KQkqlSpQkCgo+Navnx5bm3enL0FFn/0ZJ9N+YwOHTrSoUNHFi5cSLfca9so99omJxWd07hmzVo6dHAMI+3evTsLc89T1apVee/9d+nX7xn27/eODuyftm3aTPVaNakaFYWPry/tOndkxaIlf1/Ry335xSy6dXuAbt0eYMmSVdx+e3sA6jeox8mTpzh23hvZvxIamj/s9vrrr8ViWDw+eQFQr1oQfxw/zZETZ8jKzmHBlqPEXFN4+lBk5Qr8vM/ROU85dZYDx04RFZy/bsIPW47S/nrvmz4CkLJtJwE1qlGpqg2Ljw8128VyZMWaQmXmdLyPOR36MKdDHw4tXsUvoydweNlqrH5++FR0dP6sfn7Ymt5I2p4DbmiF67RsfC3fLN+AaZps3PkHARX9CK8SyPW1q3Eg/hiHEo9zLiub737cTMvG17o73AuWvuN3KkRF4RcZieHjQ3jrVqT8WPiTRt8q+a/tgGuvBcNCdloavpWDsPr7A2ApV47gm27kzEHvWcQybfvvVKpRjQpVbRg+PkS2aUnSysL3frmQ4Lzvg+peg2ExyEpLd6qup8vYtYPyVavjG+G49kEt2nBybeHP0k6uXUnFeg3BYsUoX54Kdepx9tABp+p6qhkzFtK79wv07v0Cy5f/QscOjs8Tr7vuKk6dOkNKSmqROrff3pKmTerz4uDxhUZoREXl/62oUycaX18fr0heAJzZuYNy1apTzua4hpVj2pC2ZlWhMj7B+a/9CnXqgsXAnp5GVnIila65DqO8I2nv3+imIot/eqp5C/bz5HPLefK55az5JYFWMdUBqHNVMKfPZBWZJvLL+kTu/fcCHnh8EQ88voiz5+x5yYtIW6W8cldGB+HjY1HyQryWM08h6QcsNwxjX+52LeD/XBaRk+x2O6OGDuPDKVOwWC3Mnj6DPbt306O3Y6jotKlfsHLpMlrExfHDyuVkZmQwuP/zefX9/Pxodltzhg8aXNKP8Fh2u52Xhg7lkylTsFitfD19Ort376ZX794AfDl1KsuXLiU2Lo6lK1eSmZHBC/0dqzKHhYfz6htvYLVYsFgsfDdvHsuWet8qxMuWLiMuLo4VK5eTkZHBcwWu7eRPPuaF5weQlJTE2DFjmTBxAs/2f5Zt27Yzfdp0AJ56+imCg4N5eeRIALLt2XTpfLtb2nKh7HY7rwx9iXemTMZitTJn+gz27d5N996OKRAzp35JSFgon8/5hkr+/phmDvc8+AB3tmnP6VOnGP32m9zY5BYqBwfz/Zofee/N8Xw7vfinGniqlSvW0KJFU35YMI3MzEwGDxqdd+y9919lyItjSU5O4d577+TBh+4hNLQK33z7KStXrmHokFdo2zaWnr3uIDvbztmzZ3n22WFubI3zfKwWBnS8jv9MWUdOjsntN0RROzyAGb843ojd1bgm/465iqGzN3HnxJWYmPy37TUEVyoHQMY5O2v3HuPFLte7sxn/mGnP4dexE4l7dwyGxcK+bxeQtvcgte/sBMCer4tZ9yKXX0hlWrwxHADDx8rB75cRv/rXsgi71Dzzxles27qfEydP0+LhsTzZszXZuWv89Gp3CzE31mHF+p20eex1KpT3ZfQTjiS2j9XK0Ie78PCIydhzTLq3upGranjhujl2O3veeIvr33wNw2ohYd58zuw/QGTXLgDEfzOHsLhYqt5xO6bdTs7Zs+wY+hIA5UJCqDNkEIbFimExSF6yjOOrvedNvGnPYfu4CTR++xUMq5XDc77n1L4DVO/mGJV2aNZcbC1jqHFnF8xsR9s3Dn75L+t6lRw7R999jVovv41hsXBi4VzO/rGf4A6Op4edmD+bs4cOcOq3tdT+31TIyeHEgjmcPejouhZX19v89NMGbr21EbO/GU9m5jlGvJS/hsVb4wfw8sj3OXbsBAMGPkxCQjIff+y4/suWreOjj2bSstUtdOzQguxsO5lnzzFo4Ftuask/kGPnyMTXuGL0eLBYOL5gHmcP7ieko+P6p3w3m6DbWhLaqZvjtX/uLAdHDwHgzO/bSF21lKv/9ymm3U7Gnl2kzP/GjY35Z35Zn0jjRhFMmtCas+fsvPlO/hoWLw1swvj3NnL8RGaJ9W+9JZJWMdXJtpucO2dn7Jve9ffPExS7fIG4heHMPEjDMMoDf06Y/t00zaIrw5TAVVNIvMFZis7BvpzYvfchN6WiimF1dwhulVnBe57s4gq/Db/Z3SG4zewxl860jH/inqmPujsEt1rx7/HuDsGtzmR57RPqL1r1sNPuDsGtHkiq5e4Q3OqjKt4zqskVBgYNdHcIbjV/xu2X9Dv8K6LrXJLvafft3+l11+1v/8oahnHfebsaGIaBaZpTXBSTiIiIiIiIiEghznxM0LjA935AK2A9oASGiIiIiIiIiJSJv01gmKb5ZMFtwzCCgM9cFpGIiIiIiIiIx7i8p8Z7kn9yJc4AV5V2ICIiIiIiIiIiJXFmDYy5wJ+LlliAusB0VwYlIiIiIiIiIlKQM2tgvFbg+2zgoGmah10Uj4iIiIiIiIhIEc6sgbGiLAIRERERERER8TSG4XVPG71k/e0aGIZhNDEM4xfDME4ZhnHOMAy7YRjpZRGciIiIiIiIiAg4t4jnRKAXsBuoADwMTHBlUCIiIiIiIiIiBTmzBgamae4xDMNqmqYdmGwYxmoXxyUiIiIiIiIikseZBMYZwzDKARsNwxgHxAOVXBuWiIiIiIiIiAcwnJm4IGXBmSvRJ7fcE8BpoDrQ3ZVBiYiIiIiIiIgU9JcjMAzDsAKjTNO8F8gEXiqTqERERERERERECvjLERi5a16E5U4hERERERERERFxC2fWwDgA/GQYxhwcU0gAME3zDVcFJSIiIiIiIiJSUIkJDMMwPjNNsw/QA3gTx2iNgLIKTERERERERMTdDKeWjpSy8FcjMG40DKMm8AcwoYziEREREREREREp4q8SGO8BPwDRwK8F9huACVzhwrhERERERERERPKUOBbGNM23TdO8FphsmuYVBb6iTdNU8kJEREREREREyszfLuJpmuZ/yiIQEREREREREU9jGIa7Q5BcWo1ERERERERERDyeEhgiIiIiIiIi4vGUwBARERERERERj/e3a2CIiIiIiIiIXLYMfe7vKXQlRERERERERMTjKYEhIiIiIiIiIh7P5VNI/Ayrq3+Ex/LDynEzy91huJHp7gDc6rSZ7e4Q3Con66S7Q3CrCtfd6u4Q3KbzQ4fdHYJbrfj3eHeH4FYxHz7t7hDEjWb3edfdIbhNtv2Uu0Nwq647490dgltVr77E3SG42e3uDkAuE1oDw4Uu7+SFiIiIXE4u5+SFiFzaDK2B4TF0JURERERERETE4ymBISIiIiIiIiIeTwkMEREREREREfF4SmCIiIiIiIiIiMfTIp4iIiIiIiIiJTD0ub/H0JUQEREREREREY+nBIaIiIiIiIiIeDwlMERERERERETE42kNDBEREREREZESGIY+9/cUuhIiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PK2BISIiIiIiIlICw7C6OwTJpREYIiIiIiIiIuLxlMAQEREREREREY+nBIaIiIiIiIiIeDytgSEiIiIiIiJSAsPQ5/6eQldCRERERERERDyeEhgiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PC3iKSIiIiIiIlICLeLpOXQlRERERERERMTjKYEhIiIiIiIiIh5PCQwRERERERER8XhaA0NERERERESkBIZhdXcIksurExjNYlrQf+iLWK1WZk+bzifvvl/oeK0rr2D4q69wTb16vPPa63z24aS8Y8PGjeG2li05npLC3e06lHXoFy0mJoahw4ZhtVqZ9tVXvPvuu0XKDBs+nLi4ODIyMujfvz/btm51uq43GDZ82Hnt21akTFT1KCZOmEhQ5SC2bd1Gv379yMrK4sorr+TV116lXr16vPbaa3z4wYduaME/d1tMDIOHDcVitTLjq2l8WMw1HDx8GDFxcWRmZDCgf3+2556fJT/+yOnTp8ix52C3Z9O9c5eyDr9UDBnyAjGxzcnIyOSFF4awfdvvRcrc26cnffv2pmbNGtzcOIYTJ1IvqL4nWrl+F6M+nkdOTg53tW7MI91iCh1PO5XBoIkz+SPxOOV9fRj9eDeurmkD4NN5PzFj0S+YwF2tG9O3861uaMHFsdZogF+LB8CwkLV9Ced++7ZwgXIVqND2KYyAEDCsnNswl+wdywHwa/UfrLVuwMxI48wX/cs++FIQfMvN1P7vUxhWC/Fzv+PQZ1MLHQ9q1JDrXhlN5tF4AI6tWMnByZ9ilCtHw/9NwOLri2G1krxsOQcnTXZHE/6xgRNnsvzX3wkJqsS88f8tctw0TUZNmseK9TvxK1+OsU90p96V1YC/f914g8v9tR/erDH1+z+GYbVwcPb37Prkq2LLVa5bh9hP32bdgJc5umQV/jWjaDz2xbzjlapFsuO9T9n7xayyCr3UPP/C/3Fr85vIzDzLsCFv8vvve4uUGTW6P3XrXUV2djZbt+5i1MiJZGfbna7vqVrExDBs2DAsuX3X90ro98bm9nsK9ntfefVVWrZsSUpKCu3bti3r0EvNU093p0nTupzNPMeY0VPZtetwkTJDht5HnWuqk51tZ8eOP3ht3FfY7TlUquTHi0PvIyIiGKvVwldfLuX7+T+7oRUiF89rp5BYLBZeGDGcJ/s+RPc27WnfpRPRtWsXKpOWmsq44SP47MOPitSf+/Usnrj/wTKKtnRZLBZGjBxJ3/vvp03r1nTp0oXaV11VqExsXBzR0dHExsQwaOBARr38stN1vUFsXGxu+2IZNHAQo14eVWy5AQMGMGnSJOJi40hLS6NHjx4ApKamMnzYcD780LsSF+C4hkNHjuDh+/vSsXUbOnXpwpVXFb73W8TFUis6mrYxsQwZOIjh552f+3v2omuHDl6bvIiJaU7NWjVo3aozQ14cwYiXXiy23PrfNnL/ff/H4cNH/lF9T2O35zDiwzl89GJfvhv/X+at2sSeQ4mFyrw3cznXRkcy982neOWpOxn18TwAdh1MYMaiX5gx7jG+feNJlv/2OweOHnNHM/45w8Av9iHOzBnN6an98Ln6VizB1QoVKVe/Pfbjhznz5fNkzBqOX/P7wOL41CRrx3Iy5ox2R+Slw2Lhqv792PLsc/xyz32Et25FxVo1ixRL27SZ3/o+xG99H+Lg5E8BMM+dY9OT/+W3+x/kt/sfpEqTWwioV7esW3BRusXdwEdD+pZ4fOX6XRyIT2HhO88y8tGuDP/Akdxy5nXj6S77177FQoMXnmT1k4NY3P0hotrHERBdo9hy1z39MIlrfs3bdergYZb1etTx1fsx7JlnObrsxzIMvnQ0b34TNWpU5fbO/+blERMY9OLjxZb7fv5y7rj9/7ir++P4lS/PHXe0u6D6nqhg37XtX/R7a0VHExcTw8CBA3k5t98LMHPGDPref39Zh12qmjSpS1T1MO7pOZJXX53GM/3vLrbcooW/cu89o+h731jKl/elU+dmANzR7TYOHkjgwb6v8NSTE3j8ia74+GhEgXgnr01gXNewAYcPHuTIoUNkZ2WxYO53xLZtXajMiZTjbN+8hezs7CL116/7hbS01DKKtnQ1bNiQgwcOcOjQIbKyspg7dy5t27QpVKZtmzbMmjkTgA0bNhAQGEhYeLhTdb1B2zZtmTXT8emJo30BhIWHFSnXrFkz5s+fD8DMmTNpm5t5T0lJYfPmzWRnFb03PF39hg05eOAgh3Ov4Xdz59KqTeFPFFq1acs3uedn04YNBJZwfrxV69ZxfDN7LgAbN25xXP+w0CLltm//nSNHjv7j+p5m857D1IwMobqtCuV8fejYvD5L1u0oVGbvoSSa1L8SgCujwjmSlMqx1JPsPZJMg6trUKF8OXysVhrXjWbRz9vd0Yx/zBJRm5zUBMz0JMixk71rNT5XNC5cyDQxfP0c35fzw8w8BTk5ANiP7nBse6nAuteScfgImUfjMbOzSVq8hJDbmjtdPycjAwDDxwfDxwdM01WhukTjetEEBVQs8fiSddvpGtsIwzBoWKcG6aczSTqe7tTrxtNd7q/9KtfV4fTho5w54rj3Dy9YTmRs0VEkV/bsypElqzh7PLXY/yf85kacPnyUjPgkF0dc+mLimjBv7lIAtmzZSUBAJUJDg4uU+/HH/OTN1q27CI8IvaD6nqhBMX3XNuf1XdsU6Pdu3LCBwNx+L8C6detITU0t67BLVfPbrmfBD+sA2L7tAP7+FQgJCSxSbu3a/Nf2ju0HCQsPAhy/7itULA9AxQrlSE8/g92eUwaRi5Q+pxIYhmEU+StR3L6yFBYRQULuEFmApPgEwiMi3BhR2Ymw2Tgan9/2+Ph4Imy2omWO5r9xS0hIwBYR4VRdbxBhiyimfYXbERwcTHp6Ona7Y+iko63ef49E2CJIiM9ve2Ix7YqwRZBw3vmJyDs/JpM+/4yZ8+Zyd69eZRFyqYuICCc+Pv/Tx4SERCIiwsusvrskpqRhCwnK244ICSLxeHqhMtfUsrForWO60ObdhzianEpCSjpX14jg1+37OXHyDBlnz7Fy/U4SjqWWZfgXzVKpCjmnUvK2c06lYPhXKVTm3OYfsFSpRqUH36dSr9fJXDUZ8K436iUpFxbK2cT8N15nk5MpH1Y0MRl4XT1u/PRjrn99HBWja+UfsFi48ZNJNPvuW0788isnt3vXm/i/k3g8HVto/uvDFhJI4vF0p143nu5yf+37hYWSkZB/72ckJeMXHnJemRCqxt3K/q/nlfj/RLWL4/CCZS6L05XCw0NISEzO205MPEb4eeegIB8fKx07xbH6p9/+UX1PYrPZiC/Qd02Ij8dWTL83vkC/Jz6333upCA0NIikpNW87OSmV0AK/785ntVpo164x69Y6fs/PmrmSmjVtzP5mJJM/Hcjb42dielkS290Mw3JJfnkjZ9fAmADc4MS+MmMYRpF9l8sLsWjLi7a9pPPjTF1v4Mz1v1TvEaOYq3ghbe/VrTtJSUlUCQlh8uefs2/vXn5dt841wbpIMc27oGt7sfXdpbgIz2/KI91iGDVpHrc/M4Gra0ZwbXQkPhYLV0aF8/AdMTw4/GMqVihHnVqRWK1eNny0+AtXaNOnRgNykg+SMXsERlAEFW8fwukjz0FWRhkF6Up/3/5TO3exttvd5GRkUKVpE+qNHc0vPe5xHMzJ4be+D2H19+e6MS9T8YpozuzbXwZxl43iXsKGYTj1uvF0eu0Xd+8X3qzf/zG2vv1R3oirIv+Fjw+2Fk3ZNqHotGJvUPzf/pLLDxz0GOt/28qGDdv+UX1PcjH93ktFse37i/LPPHs3mzbtZfPmfQDcfMu17Nl9mP8+NYFq1UJ5483HeWDTK5w5k+miiEVc5y8TGIZhNAWaAWGGYTxT4FAgUOJfP8MwHgEeAaheJYzQgKJDnC5WUkICtqqRedvhkTaSk7xvSOA/kZCQQNXI/LZHRkaSlFh4LmxCfDxVq1bN27bZbCQmJVGuXLm/reup+tzXh149HSMGNm3eVEz7Crfj+PHjBAYGYrVasdvtuW31/nskISEBW2R+2yOKaVdCfAK2885PUu75Scp9nRxPSWHRggXUb9jAKxIYve/tQY+7uwGwecs2IiPzP1mx2SJISkouqWoRCQlJF1XfXWwhQSSkpOVtJ6akEV6l8O9X/4p+jHnyTsDReWv16KtERTiGCd/V+ibuan0TAG98voCIkJI/vfFEOadS8PXP/8TQ4h+CefpEoTK+deM499s3AJhpieSkJ2GpUpWcRO9ZrK4k55KTKV9gpFD5sDDOHiu8loH9zJm874+vWctV/fvhExREdlr+fWM/dYrUDRupcsstl1QCwxYSSMKx/HYmpKQTHhxAVrb9b183nu5yf+1nJiVTwZZ/71cIDyMzOaVQmcp1r6bxmMEAlK8chK35zZh2O/HLVwNgu/VmUn/fXeL0Ek90d4+OdOvWHoBt23Zhi8gfcRUREUryeefgT4/8Xy+Cg4N4eeTEvH2JScecru9p4hMSiCzQd7VFRpJYTL83skC/JzK33+vN7uh2G506NwXg9x1/EB5eOe9YWHhlUgr8viuo7wPtqVzZnxcH5z+8oEOHW5j6+SIAjhw5Rnx8CjVrhrNjxx+ua4CIi/zduJFygD+OREdAga904M6SKpmm+YFpmjeZpnmTK5IXANs2baZ6rZpUjYrCx9eXdp07smLREpf8LE+zadMmakVHE1W9Or6+vnTu3JlFixYVKrNo8WK6de8OQKNGjTh58iTJSUlO1fVUn035jA4dOtChQwcWLlxIt+6ON7P57Sv6BnTNmjV06OB4ykz37t1ZuGhhmcbsCls2baJWdC2iqkfh6+tLx86dWXreNVy6eBFdc89PgwLnp0KFClSqVAmAChUqcGuL29i9c1eZt+GfmPr5NLp06UGXLj1YvGgZXe/oDEDDhtdz8uQpkpOdX5RuyZLlF1XfXa6vXY0D8cc4lHicc1nZfPfjZlo2vrZQmfTTGZzLXdtlxuJfualuNP4VHWtCpKQ61n84mpzKwp+30em2BmXbgIuUk7gXS+VIjMAwsFjxuboZ2ft/LVzm5DGsUdcDYFQIwhJcFTPNuzuxf0rf8TsVoqLwi4zE8PEhvHUrUn78qVAZ3yr5U2oCrr0WDAvZaWn4Vg7C6u8PgKVcOYJvupEzBw+Wafyu1rLxtXyzfAOmabJx5x8EVPQjvEqgU68bT3e5v/ZPbNuJf/VqVKxqw/DxIapdLPErVhcqs7BzHxZ2upeFne7lyOKVbBzzdl7yAiCqvfdNH5k+7Tt69niSnj2eZNmytXTq3BKA66+vw6lTpzl27ESROnfc0ZZmzW5k4IBxhUYgrFj+s1P1PdHmYvqui8/r9ywu0O9tWKDf681mz1rFQw+M46EHxrFq1Wbatb8ZgLr1anH6VCYpKUWnwnXs1JSbb76Wl4Z/Wuj6Jyae4Mab6gAQHBxA9RrhHD3qHQkskfP95QgM0zRXACsMw/jENE2P6unY7XZeGfoS70yZjMVqZc70GezbvZvuvR2f0M+c+iUhYaF8PucbKvn7Y5o53PPgA9zZpj2nT51i9NtvcmOTW6gcHMz3a37kvTfH8+30GW5ulXPsdjtDhw5lypQpWK1Wpk+fzu7du+nduzcAU6dOZdnSpcTFxbFi5UoyMjJ4rn//v6zrbZYtXZbbvhW57Xsu79jkTybzwvMvkJSUxNgxY5kwcQLP9n+Wbdu2MX3adADCwsKYM3cO/v7+mDkmDz74IG1at+HUKc9f4M9utzNi6FA+yr2GM6dPZ8/u3fTMvf5fTZ3KiqXLiImLY1Hu+RmUe35CQkN554MPALD6WJn37besWrHCbW35p5YvX0VMbHOWLJ1HRkYmA14Ymnfsw48mMnjQSyQlJXPffffw70f6Ehoawtx5M1ix4kcGD3rpL+t7Mh+rlaEPd+HhEZOx55h0b3UjV9WI4MsFjkeh9Wp3C3sPJ/PC2zOwWAxqR4Uz6vHuefWffHUqqSfP4GO1MuzfXQjyr+CupvwzZg6ZKz6mYpfBYLGQtX0ZOccP43udYzG3rK2LOPfLTPxaP0bFXq+BAWdXT8XMPAmAX7unsVari+EXQKUH3uXcz9PJ2u5Fb2jsdva88RbXv/kahtVCwrz5nNl/gMiujqcJxX8zh7C4WKrecTum3U7O2bPsGPoSAOVCQqgzZBCGxYphMUhesozjq9e4sTEX7pk3vmLd1v2cOHmaFg+P5cmercnOXeOoV7tbiLmxDivW76TNY69Tobwvo59w3PslvW68yeX+2jftOWx6ZQK3vjMWLBYOzvmBk/sOUqt7JwAOzCx53QsAq195wm+5kQ2j3iqDaF3jx1W/0Lz5TcyZ9xGZmWcZPvTNvGMTJg5nxEtvk5x8nEEvPkF8fBKfTnkdgKVLV/PB+1/+ZX1PZ7fbGZbbd7VYrczI7bvek9vv+aJAv3d5br/3+f75j8oe//bbNGnalODgYFavXctbb77J9GnT3NWcf2Ttmu00bVqPL6cNzXuM6p/Gvfp/vDL2S1JS0nm2/90kJp7g3ff7AbByxWY+/eQHPv3kBwYNvpdPPh0ABrz37hzS0k67qzleyTC8bOrdJcxwZn6YYRg3AYOBmhRIepimWf/v6t5Qq/alMwHtAh03s9wdgpt52yzj0lXe3QG4WY6vdw1RLm27v/WOpIgrnFzqXR3D0rb+ywR3h+BWMR8+7e4QxE1m93nX3SG41Qj75f2XPzV1q7tDcKvq1W93dwhutfLHty/pjn/969teku9pN29Z6HXXzdlFPKcCzwFbAD1zR0RERERERETKlLMJjGTTNOe4NBIRERERERERkRI4m8AYZhjGR8AS4OyfO03TnOWSqERERERERERECnA2gfEAcA3gS/4UEhNQAkNEREREREQuWVrE03M4m8BoYJrm9S6NRERERERERESkBBYny601DKOuSyMRERERERERESmBsyMwmgP3G4axH8caGAZgOvMYVRERERERERGRi+VsAqO9S6MQERERERER8UAWw9mJC+JqTiUwTNM8CGAYRjjg59KIRERERERERETO41QqyTCMLoZh7Ab2AyuAA8D3LoxLRERERERERCSPs2NhRgJNgF2maUYDrYCfXBaViIiIiIiIiEgBzq6BkWWaZophGBbDMCymaS4zDOMVl0YmIiIiIiIi4maGYXV3CJLL2QRGqmEY/sBKYKphGElAtuvCEhERERERERHJ5+wUktuBM0A/4AdgL9DZVUGJiIiIiIiIiBT0tyMwDMd4mW9N02wN5ACfujwqEREREREREZEC/jaBYZqm3TCMM4ZhBJmmmVYWQYmIiIiIiIh4Aq2B4TmcXQMjE9hiGMYi4PSfO03TfMolUYmIiIiIiIiIFOBsAuO73C8RERERERERkTLnVALDNM1PDcOoANQwTXOni2MSERERERERESnEqaeQGIbRGdiI4wkkGIbR0DCMOS6MS0REREREREQkj7NTSIYDNwPLAUzT3GgYRrSLYhIRERERERHxCFrE03M4NQIDyC7mCSRmaQcjIiIiIiIiIlIcZ0dgbDUM4x7AahjGVcBTwGrXhSUiIiIiIiIiks/ZERhPAvWAs8AXQBrwtKuCEhEREREREREpyNkRGHVzv3xyv24HugD1XRSXiIiIiIiIiNsZFq2B4SmcTWBMBfoDW4Ec14UjIiIiIiIiIlKUswmMZNM057o0EhERERERERGREjibwBhmGMZHwBIc62AAYJrmLJdEJSJeL8e0uzsEEbc4k+Xsn1aRS8s503B3CCIicolztpf1AHAN4Ev+FBITUAJDRERERERELlkWQ2tgeApnExgNTNO83qWRiIiIiIiIiIiUwNnHqK41DKOuSyMRERERERERESmBsyMwmgP3G4axH8caGAZgmqapx6iKiIiIiIiIiMs5m8Bo79IoRERERERERDyQoTUwPIZTU0hM0zxY3JergxMRERERERERz2IYRhXDMBYZhrE799/gYspUNwxjmWEYOwzD2GYYxtMFjg03DOOIYRgbc786OPNznV0DQ0REREREREQEYACwxDTNq4AludvnywaeNU3zWqAJ8Ph5a2u+aZpmw9yv+c78UCUwRERERERERORC3A58mvv9p0DX8wuYphlvmub63O9PAjuAahfzQ5XAEBEREREREbnMGIbxiGEYvxb4euQCqkeYphkPjkQFEP43P6sW0Aj4ucDuJwzD2GwYxsfFTUEpjrOLeIqIiIiIiIhcdi7VRTxN0/wA+KCk44ZhLAZsxRwafCE/xzAMf2Am8F/TNNNzd78LjATM3H9fBx78u/9LCQwRERERERERKcQ0zdYlHTMMI9EwjEjTNOMNw4gEkkoo54sjeTHVNM1ZBf7vxAJlPgTmOROTppCIiIiIiIiIyIWYA9yf+/39wLfnFzAMwwAmATtM03zjvGORBTbvALY680OVwBARERERERGRCzEWaGMYxm6gTe42hmFUNQzjzyeK3Ar0AVoW87jUcYZhbDEMYzMQB/Rz5odqComIiIiIiIhICQxDb5vPZ5pmCtCqmP1HgQ653/8IGCXU7/NPfq5GYIiIiIiIiIiIx1MCQ0REREREREQ8nhIYIiIiIiIiIuLxNJlHREREREREpAQWw+ruECSXRmCIiIiIiIiIiMdTAkNEREREREREPJ4SGCIiIiIiIiLi8bQGhoiIiIiIiEgJDIvWwPAUGoEhIiIiIiIiIh5PCQwRERERERER8XhKYIiIiIiIiIiIx1MCQ0REREREREQ8nhbxFBERERERESmBYehts6fw6ivRLKYF/Ye+iNVqZfa06Xzy7vuFjte68gqGv/oK19Srxzuvvc5nH07KOzZs3Bhua9mS4ykp3N2uQ1mHftFiYmIYOmwYVquVaV99xbvvvlukzLDhw4mLiyMjI4P+/fuzbetWp+t6g2HDh53Xvm1FykRVj2LihIkEVQ5i29Zt9OvXj6ysLK688kpefe1V6tWrx2uvvcaHH3zohhb8c7fFxDB42FAsViszvprGh8Vcw8HDhxETF0dmRgYD+vdne+75WfLjj5w+fYocew52ezbdO3cp6/BLxdChA4mNvY2MjEyef34w27btKFImKqoa48e/SuXKQWzbtoNnnx1AVlY2gYGBvPLKSGrUqM7Zs2cZMGAIu3btcUMrLtzAiTNZ/uvvhARVYt74/xY5bpomoybNY8X6nfiVL8fYJ7pT78pqAKxcv4tRH88jJyeHu1o35pFuMWUc/cWz1miAX4sHwLCQtX0J5377tnCBchWo0PYpjIAQMKyc2zCX7B3LAfBr9R+stW7AzEjjzBf9yz74UhDatDHXPvsEhsXC4W/ns+/TLwsdr3JDA254fSQZRxMASFy2ij0ffeZUXW/wd/dw2qkMBk2cyR+Jxynv68Pox7txdU0bAJ/O+4kZi37BBO5q3Zi+nW91Qwv+ucv9tW9rdhONnnsMw2Jh3zff8/vkacWWq1L3alpNeZs1A0ZxePEqADp99xlZpzMwc3Iw7XYW9X68LEMvNc+/8H/c2vwmMjPPMmzIm/z++94iZUaN7k/deleRnZ3N1q27GDVyItnZdqfre6oWMTEMGzYMS27f9b0S+r2xuf2egv3eV159lZYtW5KSkkL7tm3LOvRS89TT3WnStC5nM88xZvRUdu06XKTMkKH3Ueea6mRn29mx4w9eG/cVdnsO/gEVGDDwHqpVDeXcuWzGjvmC/fvj3dAKkYvntVNILBYLL4wYzpN9H6J7m/a079KJ6Nq1C5VJS01l3PARfPbhR0Xqz/16Fk/c/2AZRVu6LBYLI0aOpO/999OmdWu6dOlC7auuKlQmNi6O6OhoYmNiGDRwIKNeftnput4gNi42t32xDBo4iFEvjyq23IABA5g0aRJxsXGkpaXRo0cPAFJTUxk+bDgffuhdiQtwXMOhI0fw8P196di6DZ26dOHKqwrf+y3iYqkVHU3bmFiGDBzE8PPOz/09e9G1QwevTV7Ext5GrVo1aNmyA4MHD2fEiCHFlnv++X5MnvwZrVp1JC0tnbvu6g7AY4/9m+3bf6djx2707z+IIUMGlGX4F6Vb3A18NKRvicdXrt/FgfgUFr7zLCMf7crwDxxv8O32HEZ8OIePXuzLd+P/y7xVm9hzKLGMoi4lhoFf7EOcmTOa01P74XP1rViCqxUqUq5+e+zHD3Pmy+fJmDUcv+b3Qe6jz7J2LCdjzmh3RF46LBbqPf80vz49gFV3P0Bk25b4R9csUuzEhi381PsRfur9SF7ywtm6nsyZe/i9mcu5NjqSuW8+xStP3cmoj+cBsOtgAjMW/cKMcY/x7RtPsvy33zlw9Jg7mvGPXc6vfcNi4cYBT7LyiUH80P1haraPI/CKGsWWq//0wySs+a3IsWWP9Gdhz0e9NnnRvPlN1KhRlds7/5uXR0xg0IvFt+P7+cu54/b/467uj+NXvjx33NHugup7ooJ917Z/0e+tFR1NXEwMAwcO5OXcfi/AzBkz6Hv//WUddqlq0qQuUdXDuKfnSF59dRrP9L+72HKLFv7KvfeMou99Yylf3pdOnZsB0KdPW/bsPsIDfV9h1Muf8dTT3coyfJFS5bUJjOsaNuDwwYMcOXSI7KwsFsz9jti2rQuVOZFynO2bt5CdnV2k/vp1v5CWllpG0Zauhg0bcvDAAQ4dOkRWVhZz586lbZs2hcq0bdOGWTNnArBhwwYCAgMJCw93qq43aNumLbNmzgL+bF8AYeFhRco1a9aM+fPnAzBz5kza5mbeU1JS2Lx5M9lZRe8NT1e/YUMOHjjI4dxr+N3cubRqU/gThVZt2vJN7vnZtGEDgSWcH2/VunUcs2fPAWDjxs2O9oWFFinXtOktfP/9QgBmzfqWNm1aAlC79pWsXr0WgH379lOtWjVCQkLKKPqL07heNEEBFUs8vmTddrrGNsIwDBrWqUH66UySjqezec9hakaGUN1WhXK+PnRsXp8l64qOWvFkloja5KQmYKYnQY6d7F2r8bmiceFCponh6+f4vpwfZuYpyMkBwH50h2PbS1Wudw2nDx0h40g8ZnY28YuWEh7TzOV1PYUz9/DeQ0k0qX8lAFdGhXMkKZVjqSfZeySZBlfXoEL5cvhYrTSuG82in7e7oxn/2OX82q9yXR1OHjrK6SMJ5GRn88eC5VSLLXr/XtXzdg4v+ZGzx1PLPkgXi4lrwry5SwHYsmUnAQGVCA0NLlLuxx9/zft+69ZdhEeEXlB9T9SgmL5rm/P6rm0K9Hs3bthAYG6/F2DdunWkpqaWddilqvlt17Pgh3UAbN92AH//CoSEBBYpt3Zt/u+1HdsPEhYeBECtWjZ++20XAH/8kYQtMoTg4IAyiFyk9DmVwDAMY4kz+8pSWEQECUfzhz4lxScQHhHhxojKToTNxtH4/LbHx8cTYbMVLXP0aN52QkICtogIp+p6gwhbRDHtK9yO4OBg0tPTsdsdQycdbfX+eyTCFkFCfH7bE4tpV4QtgoTzzk9E3vkxmfT5Z8ycN5e7e/Uqi5BLXUREBEdzh8gDJCQkYjvvHAQHV+bkyZN5199RxtGZ2bFjJ+3aORKe9etfR7VqkURGev+9AZB4PB1baFDeti0kkMTj6SSmpGELyd8fERJE4vF0d4T4j1kqVSHnVEreds6pFAz/KoXKnNv8A5Yq1aj04PtU6vU6masmA2YZR+oafmGhZCYm5W1nJh7DL6xoYrLy9XW5deqH3DR+DP5X1Lqgup7MmXv4mlo2Fq11TJfbvPsQR5NTSUhJ5+oaEfy6fT8nTp4h4+w5Vq7fScKx1LIM3+Uu5dd+hfBQMhKT87bPJB6jwnlJ6wphIVRr2Zy9X88rUt80TWL/N5Y2U9/him7eN20YIDw8hIQC5yAx8Rjh4SUn3n18rHTsFMfqn377R/U9ic1mI75A3zUhPh5bMf3e+AL9nvjcfu+lIjQ0iKSk1Lzt5KRUQgu83s9ntVpo164x69Y6kpV79hyhRYsGAFx7bQ0iIoIJC6/sypAvOYZhvSS/vNFfroFhGIYfUBEINQwjGDByDwUCVV0c218yDKPIPtO8NDqpf6doy4u2vaTz40xdb+DM9b9U7xGjmKt4IW3v1a07SUlJVAkJYfLnn7Nv715+XbfONcG6yMVe//ff/4ghQwYwd+7X7Ny5m+3bf8+bI+ztirvFDcMo9i18cb8PPFox1/T8BvvUaEBO8kEyZo/ACIqg4u1DOH3kOcjKKKMgXciJ+z59526Wd+mFPSOTsGa3cMOrI1jZ/T6n6no6Z+7hR7rFMGrSPG5/ZgJX14zg2uhIfCwWrowK5+E7Ynhw+MdUrFCOOrUisVq9s+NWkkv6tV9876XQVqPnHmPz+I8wc0dcFbTkgX5kJqdQPrgyse+N5eSBQySv3+KiWF2j+L/9JZcfOOgx1v+2lQ0btv2j+p7kYvq9l4pi2/cX5Z959m42bdrL5s37AJj6+WKeerobkyY/z7698ezefTjvAx4Rb/N3i3j+H/BfHMmK38j/HZIOvFNSJcMwHgEeAaheJYzQgKJDnC5WUkICtqqRedvhkTaSk5L+osalIyEhgaqR+W2PjIwkKbHwfNaE+HiqVs3PMdlsNhKTkihXrtzf1vVUfe7rQ6+ejhEDmzZvKqZ9hdtx/PhxAgMDsVqt2O323LZ6/z2SkJCALTK/7RHFtCshPgHbeecnKff8JOW+To6npLBowQLqN2zgFQmMe+/tSY8edwKwZctWqla18VvuNGebLYLE887B8eMnCAgIyLv+jjKOT59OnTrNCy/kr5uxYsUCDh8uuhiWN7KFBJJwLC1vOyElnfDgALKy7SSk5O9PTEkjvErp/252pZxTKfj6539iaPEPwTx9olAZ37pxnPvtGwDMtERy0pOwVKlKTqL3LFZXksykZPwiwvO2/SJCOXus8DoO2afP5H2fvPpn6r7wNL5BgU7V9XS2kKC/vYf9K/ox5knH7wnTNGn16KtERTiGyd/V+ibuan0TAG98voCIkJI/vfRGl/JrPyMpmQoR+SOGKkaEkpGcUqhMcN2raDp2EADlKgcR2bwxZradI8tXk5lb9uyJVA4v/Ykq9ep4RQLj7h4d6datPQDbtu3CVuAcRESEknzeOfjTI//Xi+DgIF4eOTFvX2LSMafre5r4hAQiC/RdbZGRJBbT740s0O+JzO33erM7ut1Gp85NAfh9xx+EFxgxERZemZQCr/eC+j7QnsqV/XlxcP7DC86cyWTsmC/ytqfNGEb80eOuCVzExf5yColpmuNN04wG+pumeYVpmtG5Xw1M05z4F/U+ME3zJtM0b3JF8gJg26bNVK9Vk6pRUfj4+tKuc0dWLHLrrJYys2nTJmpFRxNVvTq+vr507tyZRYsWFSqzaPFiunV3LFjYqFEjTp48SXJSklN1PdVnUz6jQ4cOdOjQgYULF9Ktu2MBovz2JReps2bNGjp0cAwX7d69OwsXLSzTmF1hy6ZN1IquRVT1KHx9fenYuTNLz7uGSxcvomvu+WlQ4PxUqFCBSpUqAVChQgVubXEbu3fuKvM2/BOff/4VnTvfSefOd7Jw4VLuuMOxAGnDhvU5efIUyclF34ytXbuOf/3LsT5It263s3ixY/5vQEAAvr6O/G2PHt355ZffOHXqdBm1xLVaNr6Wb5ZvwDRNNu78g4CKfoRXCeT62tU4EH+MQ4nHOZeVzXc/bqZl42vdHe4FyUnci6VyJEZgGFis+FzdjOz9vxYuc/IY1qjrATAqBGEJroqZ5t2d2D+lbf+dSjWqUaGqDcPHh8g2LUlauaZQmXIh+XPag+peg2ExyEpLd6qup3PmHk4/ncG53LWNZiz+lZvqRuNf0bEmSkqqY/2To8mpLPx5G51ua1C2DXCxS/m1f3zbTgJqVKNSVRsWHx9qtIvlyPLC9+93ne5jXsc+zOvYh8OLV/HbmAkcWb4aq58fPhUrAGD188PW9EbS9h5wQysu3PRp39Gzx5P07PEky5atpVNnxzpO119fh1OnTnPs2Ikide64oy3Nmt3IwAHjCo1AWLH8Z6fqe6LNxfRdF5/X71lcoN/bsEC/15vNnrWKhx4Yx0MPjGPVqs20a38zAHXr1eL0qUxSUopOBevYqSk333wtLw3/tND19/evgI+PY9RZp85N2bRpL2fOZJZNQ0RKmbOPUf2fYRhdgFoF65im+YYrgnKG3W7nlaEv8c6UyVisVuZMn8G+3bvp3tvxCf3MqV8SEhbK53O+oZK/P6aZwz0PPsCdbdpz+tQpRr/9Jjc2uYXKwcF8v+ZH3ntzPN9On+Gu5lwQu93O0KFDmTJlClarlenTp7N792569+4NwNSpU1m2dClxcXGsWLmSjIwMnuvf/y/reptlS5fltm9Fbvueyzs2+ZPJvPD8CyQlJTF2zFgmTJzAs/2fZdu2bUyfNh2AsLAw5sydg7+/P2aOyYMPPkib1m04dcrzF/iz2+2MGDqUj3Kv4czp09mzezc9c6//V1OnsmLpMmLi4liUe34G5Z6fkNBQ3vngAwCsPlbmffstq1ascFtb/qnly1cSG3sbS5d+T2ZmRqHRFJMm/Y+BA4eRlJTMuHFvMn78qzzzzJNs27aDGTMcC5vWrn0Fr702Grvdzp49+xgwYKi7mnLBnnnjK9Zt3c+Jk6dp8fBYnuzZmuzcYaC92t1CzI11WLF+J20ee50K5X0Z/YSjQ+djtTL04S48PGIy9hyT7q1u5KoaXjY/2Mwhc8XHVOwyGCwWsrYvI+f4YXyvcyzmlrV1Eed+mYlf68eo2Os1MODs6qmYmScB8Gv3NNZqdTH8Aqj0wLuc+3k6WduXubNFF8S057B93AQav/0KhtXK4Tnfc2rfAap36wzAoVlzsbWMocadXTCz7eScPcvGwS//ZV1vUtI9/OWCnwHH/b/3cDIvvD0Di8WgdlQ4ox7vnlf/yVenknryDD5WK8P+3YUg/wruaso/cjm/9k17DutfmUjM/8Y4HqP67QLS9x3kyjs7ARS77sWf/EIq0/yN4QAYVisHv19GwupfSyzvqX5c9QvNm9/EnHkfkZl5luFD38w7NmHicEa89DbJyccZ9OITxMcn8emU1wFYunQ1H7z/5V/W93R2u51huX1Xi9XKjNy+6z25/Z4vCvR7l+f2e5/vn/+o7PFvv02Tpk0JDg5m9dq1vPXmm0yfVvxjeD3V2jXbadq0Hl9OG5r3GNU/jXv1/3hl7JekpKTzbP+7SUw8wbvv9wNg5YrNfPrJD9SsGcHgF+/FnmNy8EACY8d+UdKPkhIYhrNvm8XVDGfmhxmGMR/IBLYAeZMLTdN86e/q3lCr9qUzAe0CHTez3B2Cm3nfLNvSVN7dAbhZto+/u0Nwq71z/vbX4yXr5FLv6hiWth+neNfUjNL2r0+85/GMUrqm3fueu0Nwq7E55dwdglulpm51dwhuVb367e4Owa1W/vj2Jd3xj23x3CX5nnb5yle97ro5m0qKMk2zvksjEREREREREREpgVOPUQW+NwyjrUsjEREREREREREpgbMjMNYCsw3DsABZOOYGmKZpetcy1iIiIiIiIiIXwGJcWo/e9mbOJjBeB5oCW8xL6aHKIiIiIiIiIuIVnJ1CshvYquSFiIiIiIiIiLiDsyMw4oHlhmF8D5z9c6c7H6MqIiIiIiIiIpcPZxMY+3O/yuV+iYiIiIiIiIiUGacSGKZpvuTqQEREREREREQ8jWFx9nN/cTWnroRhGGHA80A9wO/P/aZptnRRXCIiIiIiIiIieZxdxHMq8DsQDbwEHAB+cVFMIiIiIiIiIiKFOJvACDFNcxKQZZrmCtM0HwSauDAuEREREREREZE8zk7mycr9N94wjI7AUSDKNSGJiIiIiIiIeAbD0BoYnsLZK/GyYRhBwLPABCAQ+K+rghIRERERERERKcjZBMYJ0zTTgDQgDsAwjFtdFpWIiIiIiIiISAHOroExwcl9IiIiIiIiIiKl7i9HYBiG0RRoBoQZhvFMgUOBgNWVgYmIiIiIiIi4m2Hora+n+LspJOUA/9xyAQX2pwN3uiooEREREREREZGC/jKBYZrmCmCFYRifmKZ5sIxiEhEREREREREpxNlFPM8YhvEqUA/w+3OnaZotXRKViIiIiIiIiEgBziYwpgLTgE7Ao8D9QLKrghIRERERERHxBIbh7NtmcTVnn0ISYprmJCDLNM0Vpmk+CDRxYVwiIiIiIiIiInmcTSVl5f4bbxhGR+AoEOWakERERERERERECnM2gfGyYRhBwLPABByPUf2vq4ISERERERERESnI2SkkdwGGaZpbTdOMA9oAd7guLBERERERERGRfM6OwKhvmmbqnxumaR43DKORa0ISERERERER8QyGRYt4egpnR2BYDMMI/nPDMIwqOJ/8EBERERERERG5KM4mIV4HVhuG8TVgAncDo1wWlYiIiIiIiIhIAU4lMEzTnGIYxq9AS8AAupmmud2ZumdN+0WEJ97N2QE+l6byhrsjcC/Dp5K7Q3CrTf1edXcIbrPvmL+7Q3Crq2yn3R2CW83u8667Q3Crc+bl+8u/x+ePujsEtxpx13h3h+BWHQIu7wcUbnF3ACKXCaengeQmLJxKWoiIiIiIiIhcCgxDqyd4isv7I3IRERERERER8QpKYIiIiIiIiIiIx1MCQ0REREREREQ8nibziIiIiIiIiJREa2B4DI3AEBERERERERGPpwSGiIiIiIiIiHg8JTBERERERERExONpMo+IiIiIiIhICQyL3jZ7Co3AEBERERERERGPpwSGiIiIiIiIiHg8JTBERERERERExOMpgSEiIiIiIiIiHk+rkYiIiIiIiIiUwDD0ttlTaASGiIiIiIiIiHg8JTBERERERERExOMpgSEiIiIiIiIiHk+TeURERERERERKYtHbZk+hERgiIiIiIiIi4vGUwBARERERERERj6cEhoiIiIiIiIh4PE3mERERERERESmJYXV3BJJLIzBERERERERExOMpgSEiIiIiIiIiHk8JDBERERERERHxeFoDQ0RERERERKQEhkVvmz2FRmCIiIiIiIiIiMfz6lRS85gWDBg2DKvVwsyvpvHRu+8VKTNw+DBaxMWSkZHJ4P792bF1G7WuuILXJ07IKxNVozoT33iTzz6eXIbRX7xhw4cTFxdHRkYG/fv3Z9vWrUXKRFWvzsQJEwiqXJltW7fSr18/srKynK7vyYYNH0pcnOPa9u//HNu2bitSJqp6FBMnvF2g/c+SlZXF7V1v59FH/w+AM2dO8+LgIezY8XvZNuAi3BrTgheGDsVitTBr2nQ+Lubef2HYUG6LiyUzI5Mh/Z9jxzbH+en9QF+69+wBhsGsr6bxuZfd938aPPgZWsQ0IzMzk4EDRrJ9+84iZXr3vpP77u9JzZrVadKkLakn0godv+76a5k2bRLP9HuRBQuWllXoFyXgpiZU/U8/DIuF4z/MIWnaZ4WOV6p/A9EvjeNcwlEA0n5cTuLUjwEI7daTkPZdMDHJ3L+XQ6+9jJl1rszbcDHCmzWmfv/HMKwWDs7+nl2ffFVsucp16xD76dusG/AyR5eswr9mFI3Hvph3vFK1SHa89yl7v5hVVqGXCv8bmxD5f8+AxcKJBXM4NmNKkTKVrr8B2yP9MHx8sKensv+F/zhd19Ndztff1uwmGj33GIbFwr5vvuf3ydOKLVel7tW0mvI2awaM4vDiVQB0+u4zsk5nYObkYNrtLOr9eFmGXioGTpzJ8l9/JySoEvPG/7fIcdM0GTVpHivW78SvfDnGPtGdeldWA2Dl+l2M+ngeOTk53NW6MY90iynj6EvHwEFP0aJFEzIyzjJ40Bh27NhVpMw993Sjz313UqNGFLc260xqav7fvcaNGzJg4JP4+Phw4kQafe9/qizDvyh1b72FOwf8F4vVwk8z57Jo0ueFjjfu2JY2D/UG4OyZDL4a+RpHdu4BIPbeu7i1excMw+Cnr+ew7PPpZR5/aXjq6e40aVqXs5nnGDN6Krt2HS5SZsjQ+6hzTXWys+3s2PEHr437Crs9B/+ACgwYeA/VqoZy7lw2Y8d8wf798W5ohcjF89oRGBaLhcEjR/Do/X3p0rotHbp04cqrahcqc1tcLDWja/GvmDiGDxzI0JdfBuDAvn1079CR7h06clenzmRmZLJ4wUI3tOKfi42LIzo6mtiYGAYNHMio3Ladb8CAAUyaNIm42FjS0tLo0aPHBdX3VLFxsURH1yI2piWDBg5i1Msjiy03YMALTJr0MXGxLUlLS6dHj7sBOHToED3u7sm/2ndgwtsTGTNmdBlGf3EsFguDRrzEf/o+QNc27fhXl85cUbvwvd881nHvd4ptyYhBg3hxlOP81L76arr37ME9t9/BXf/qSIuWLalRq5YbWnFxWrRoRs1a1WnX9k6GDhnLsOHPF1tu/frNPPjAkxw5fLTIMYvFQv/+T/Djjz+7OtzSY7FQ7Yn+7B/cj53/7kXl2LaUr1GrSLHTWzay6z/3ses/9+UlL3xCwgjteje7nniAXY/0xrBYqBzbpowbcJEsFhq88CSrnxzE4u4PEdU+joDoGsWWu+7ph0lc82verlMHD7Os16OOr96PYc88y9FlP5Zh8KXAYqHqY89xYOh/2fNoT4Ji2lK+enThIpX8iXz8ef4Y0Z89/+nFH6MHOV3X413G19+wWLhxwJOsfGIQP3R/mJrt4wi8omjbDYuF+k8/TMKa34ocW/ZIfxb2fNQrkxcA3eJu4KMhfUs8vnL9Lg7Ep7DwnWcZ+WhXhn/wLQB2ew4jPpzDRy/25bvx/2Xeqk3sOZRYRlGXnttaNKFmzSj+1f4ehg97laHDnim23PoNW3jowWc4cqTwm9OAAH+GDH2GJx4fyO1d7ueZfkPLIuxSYVgs3P3is7zzn2cZ2aU3N3Voje2KWoXKHDtylDf7PsHobvfz/XufcM8wR78gsnY0t3bvwrheDzO6+/1cF9OMsBpRbmjFxWnSpC5R1cO4p+dIXn11Gs/0v7vYcosW/sq994yi731jKV/el06dmwHQp09b9uw+wgN9X2HUy5/x1NPdyjJ8kVLltQmM6xs24NCBgxw+dIisrCzmz51LXJvCnfGWbdowZ6bj05XNGzYSEBhIaHhYoTJNbr2VQ38cJP7IkTKLvTS0bdOGWTNnArBhwwYCAgMJCw8vUq5Zs2bMnz8fgJkzZ9K2bdsLqu+p2rZpzayZswHYkHttw867tgDNmjVl/vzvgT/b77hH1v+2nvT0dMf36zdgi7SVUeQX77qGDfjj4EGOHDpEdlYWP8ydR1zbwvd+XNvWzJ3lOD+bN2wkICCQ0LAwomtfyeYNG8nMzMRut/Przz/Tql1bdzTjorRq1YJvv3Fc102bthIYGEBYWEiRcjt27CrSifvTvX3uZuGCZRxPOe7SWEtTxTp1OXf0MOcSjmJmZ5O6YhFBzVo4Xd+wWrGULw8WK5byfmQdT3ZhtKWvynV1OH34KGeOxGNmZ3N4wXIiY28tUu7Knl05smQVZ4+nFvv/hN/ciNOHj5IRn+TiiEtXhavrcvboYbJyr3/aykUENC18/SvHtiN99TKykh1v0OxpJ5yu6+ku5+tf5bo6nDx0lNNHEsjJzuaPBcupFtusSLmret7O4SU/lth2b9a4XjRBARVLPL5k3Xa6xjbCMAwa1qlB+ulMko6ns3nPYWpGhlDdVoVyvj50bF6fJet2lGHkpaNly+bM+XYBAJs3bycgwJ/Q0KJ/937fsZujRxOK7O/YsTWLF60kPve+P+5F90it668l+Y/DpBw+ij07m9++X0L9lrcVKrN/41Yy0k86vt+8jcoRjj6t7Ypa7N+8jazMs+TY7ez+dSMNWnnX7z6A5rddz4If1gGwfdsB/P0rEBISWKTc2rXb877fsf0gYeFBANSqZeO33xwjdv74IwlbZAjBwQFlELlI6XMqgWEYxl3O7CtLETYb8fH5b0wS4xOIsBV+ExpuiyDhaIEyCfFERBQu868unZg/Z65rg3WBCJuNo0fzP1VOSEjAFhFRqExwcDDp6enY7XYA4uPj886RM/U9mSP+/GvriL/wtS3a/gQibEXb2KPn3SxfvsK1AZeiiAgbiQXv6/h4ws+7duERtvPu/QTCbTb27NzFDTffTFDlyvj5+XFbXCwRkZFlFXqpiYgIIz4h/xO0hIQkIiKKJrBKEh4eRpvWMXz1lfcMHwfwDQ3jXHL+m66s5CR8Q4q2u2Ld67n63c+IHvUm5Ws6PmXPTkkmecZUrv38G+p9NQ/7mdOc+m1dmcVeGvzCQslIyG9/RlIyfuEh55UJoWrcrez/el6J/09UuzgOL1jmsjhdxTcknKxj+fd99rGi179ctRpY/QOJHvs/rhz/KZVb/svpup7ucr7+FcJDyUjMTzieSTxGhbDQwmXCQqjWsjl7i2m7aZrE/m8sbaa+wxXdOrg8XndIPJ6OLTQob9sWEkji8XQSU9KwheTvjwgJIvF4ujtCvCjh4aEkFLj/ExOTiYgI/YsahdWqVZ3AwAAmfzKe6TM+pEuXdq4I0yUqh4dxokDbUxOTqFzMh1Z/atatE9t+XAvA0T37qH1jAyoFBeLrV556tzUluJi+oKcLDQ0iKSk1bzs5KZXQAvf7+axWC+3aNWbdWkeybs+eI7Ro0QCAa6+tQUREMGHhlV0Z8qXH8Lk0v7yQs1EPBGY4sQ8AwzAeAR4BiKwSQrC/KzJ8RpE9pmmeH8dflvH19SWudWveeuXV0g/Pxf6ubX9Xxpn6nuyft7/wdtOmTejR427u7F78UDyPVLRZTl/7/Xv3Mvm99/ng8ymcOX2GnTt+z0vweBUnru1fGTS4H6+99g45OTmlGFRZKO7iF97M2PM7O+7tSk5mBgGNmxI9fBy/P3AXVv8AApu1YMd93bCfOkmtIaOp3Ko9qUt+KJvQS0Mx1/389tfv/xhb3/4ISri2ho8PthZN2TbhIxcE6GLFNP/8G9+wWqlQ+xr2D3wcS/nyXPH6JM7s3OpUXY93WV//Yi9goa1Gzz3G5vEfYRbT9iUP9CMzOYXywZWJfW8sJw8cInn9FhfF6h7F3c6GYZx/izj2uzya0nex/Tar1Urdelfz0IP9KF++PF98+S6bNm3j4MGi6yh4nAto+1WNb6BZt0680cex9k/ivoMs+ngqT3z4FufOZHBk1x5yvLDfU+z1/4vyzzx7N5s27WXz5n0ATP18MU893Y1Jk59n3954du8+7J39PxH+JoFhGMa/gA5ANcMw3i5wKBDILqmeaZofAB8A1KsZ7ZIeUmJCPJEFPjmOiLSRlFh4TmNifAK2qgXK2CJJSsov0zw2lu1bt5Fy7JgrQix1fe67j149ewKwafNmqlatmnfMZrORmFR4OOzx48cJDAzEarVit9uJjIzMO0cJ8fF/W9/T9LmvD716OtbwcLQ//9o64i98/Yu2v/A9cs011zD2lTH0vf9BUlNTy6QNpSExIYGIgvd1ZCTJ5127xIT48+59G8m5bZ89fTqzpzsWsHrquf4kxhcdauqJ7rnnTu66+3YAtmzZTmSBT1BstnCSkpyfDnHdddfyxhuOdUEqB1emRUwzsrOzWbJkZekGXcqyjiVRLix/qpdvWHiRaSA5Z87kfX/ylzUYVh+sgUH4N7iRcwlHsaelAo7FPSvVvd6rEhiZSclUsOW3v0J4GJnJKYXKVK57NY3HDAagfOUgbM1vxrTbiV++GgDbrTeT+vturxxin3UsCd/Q/PveJzScrOPHipSxp6dins3EfjaTM1s34Bd9lVN1Pd3lfP0zkpKpUGCUWcWIUDLOa3tw3atoOtax5km5ykFENm+MmW3nyPLVeefp7IlUDi/9iSr16lxyCQxbSCAJx/IXrExISSc8OICsbDsJKfn7E1PSCK9SdOi9J+rV6w7uvKsTAFu3/I6twP0fERFGUlJKSVWLSExM5kRqGhkZmWRkZPLrr5uoc01tr0hgpCYmEVyg7ZUjwklLLvr7q+rVV9J7xAD+9+iznE7LH2WzZtY81sxyjEzq8vT/FRrN4cnu6HYbnTo3BeD3HX8QXmDERFh4ZVIK3O8F9X2gPZUr+/Pi4El5+86cyWTsmC/ytqfNGEb8Ue+ZQitS0N9NITkK/ApkAr8V+JoDuHXs2dZNm6kRXYtq1aPw9fWlQ+fOLFu0uFCZZYsX06W7Y5Ga+o0acurkSY4VeJPToUtn5s+ZU6ZxX4zPpkyhQ4cOdOjQgYULF9Kte3cAGjVqxMmTJ4u8iQVYs2YNHTo4hot2796dhYsWAbBo8WKn6nuSz6Z8RocOnejQoRMLFy6iW/c7AGjUqGFu/EXfwK5Zs5YOHRxDqB3td9wjVatW5b33/0e/fs+yf//+smtEKdi2aTM1a9WiWlQUPr6+tO/cieXn3fvLFy2hczfH+amfe36OJTvOT5UQx5BrW9WqtGrfzmteA1988TV3dO3DHV37sGTxSm7v6riuDRpcx8mTp0hOdr4j17rVHbTK/Vq4YCkjXnrV45MXAGd27qBcteqUs0Vi+PhQOaYNaWtWFSrjE1wl7/sKdeqCxcCenkZWciKVrrkOo3x5APwb3cTZPw6UZfgX7cS2nfhXr0bFqjYMHx+i2sUSv2J1oTILO/dhYad7WdjpXo4sXsnGMW/nvXkFiGrvfdMH/pSxawflq1bHN8Jx/YNatOHk2sL37cm1K6lYryFYrBjly1OhTj3OHjrgVF1Pdzlf/+PbdhJQoxqVqtqw+PhQo10sR5avKVTmu073Ma9jH+Z17MPhxav4bcwEjixfjdXPD5+KFQCw+vlha3ojaXsPuKEVrtWy8bV8s3wDpmmycecfBFT0I7xKINfXrsaB+GMcSjzOuaxsvvtxMy0bX+vucJ3y5Zez6d7tIbp3e4glS1bR5XZH17t+/bqcOnmaY8ec/7u3dOmP3HhjfaxWK35+5alf/1r27T3oqtBL1cGtvxNeI4qQapFYfXy48V+t2HLeIrzBtggeeWs0nw4cQdLBQ4WO+VepnFemQasYfv2+cJ/JU82etYqHHhjHQw+MY9WqzbRrfzMAdevV4vSpTFJSik6F6tipKTfffC0vDf+00CgVf/8K+PhYAejUuSmbNu3lzJnMsmmISCn7yxEYpmluAjYZhvGFaZpZZRSTU+x2O6OGDuODKVOwWC3Mnj6Dvbt3c3fvewCYPvULVi5dRou4OL5fuZzMjAxe7J//pAI/Pz+a3daclwYNdlcTLsqypUuJi4tjxcqVZGRk8Fz//nnHJn/yCS88/zxJSUmMHTOGCRMn8mz//mzbto3p06b9bX1vsGzpMuLiYlmxchkZGZk8V+DaTv7kY154fkBu+19hwsS3ebb/M2zbtp3p03JHHjz9JMHBwbw8cgQA2XY7XTrf7oaWXDi73c7oocN5d8qnWK0Wvsm99+/KvfdnTP2CVcuWcVtcLN+tWOZ4jOpz+efnjXf/R1BwZbKzsxk9ZBgn071vLvCKFT/RIqYZCxfNJDMjk0GD8p9C8/4HbzLkxVEkJR2jT5+7eejhPoSGVmHOnKmsWLGaIS96zxNnisixc2Tia1wxejxYLBxfMI+zB/cT0tGRrEr5bjZBt7UktFM3TLudnHNnOTh6CABnft9G6qqlXP2/TzHtdjL27CJl/jdubMyFM+05bHplAre+MxYsFg7O+YGT+w5Sq7vjE8oDM0te9wDA6lee8FtuZMOot8ogWhfIsXP03deo9fLbGBYLJxbO5ewf+wnu4Lj+J+bP5uyhA5z6bS21/zcVcnI4sWAOZw86hhAXV9ebXM7X37TnsP6VicT8b4zjMarfLiB930GuvNPR9uLWvfiTX0hlmr8xHHBMMTr4/TISVv9aYnlP9cwbX7Fu635OnDxNi4fH8mTP1mTnDoHv1e4WYm6sw4r1O2nz2OtUKO/L6CccH9L4WK0MfbgLD4+YjD3HpHurG7mqhvetgbBy5VpatGjK9z98SWbmWV4cPCbv2LvvjWPokFdITk6h973defDBXoSGVmH2N5NZuXItw4aOY9++g/z448/M/mYyOTk5zPz6O/bs8Y7fATl2O9NHv8nj77+BxWplzex5xO/dT/O7uwLw4/Rv+Nd/HqBSUCA9X3T0Z+12O+N6PATAv98cTaXKgdizs5k+6vW8xT69ydo122natB5fThua9xjVP4179f94ZeyXpKSk82z/u0lMPMG77/cDYOWKzXz6yQ/UrBnB4BfvxZ5jcvBAAmPHflHSj5ISmBbvXC/iUmQ4M3/OMIxOwEigJo6khwGYpmn+7Rg8V00h8Qan8bb59aXN6u4A3CrQGyfZlqJz5b1rgcDSNq3m5XsD7Dvm7+4Q3Ooqm/d1jkvT7oTLe2X7c+bl+9rv8fmj7g7BrerdNd7dIbhVrOXyXlNhS+Ub3R2CW6388e1L+pdfh+6zLsn3tPNndvO66+ZsKuktoBuwxfSmlR5FRERERERE5JLg1GNUgUPAViUvRERERERERMQdnB2B8Tww3zCMFcDZP3eapvmGS6ISERERERER8QSWy3tqvCdxNoExCjgF+AHlXBeOiIiIiIiIiEhRziYwqpim2dalkYiIiIiIiIiIlMDZNTAWG4ahBIaIiIiIiIiIuIWzIzAeB543DOMskMUFPEZVRERERERExGtpDQyP4VQCwzTNy/uh7iIiIiIiIiLiVs6OwMAwjGDgKhwLeQJgmuZKVwQlIiIiIiIiIlKQUwkMwzAeBp4GooCNQBNgDdDSZZGJiIiIiIiIiORydhHPp4HGwEHTNOOARkCyy6ISERERERERESnA2SkkmaZpZhqGgWEY5U3T/N0wjDoujUxERERERETEzUwt4ukxnE1gHDYMozLwDbDIMIwTwFFXBSUiIiIiIiIiUpCzTyG5I/fb4YZhLAOCgO9dFpWIiIiIiIiISAFOrYFhGMZnf35vmuYK0zTnAB+7LCoRERERERERkQKcnUJSr+CGYRhW4MbSD0dERERERETEc2gNDM/xlyMwDMMYaBjGSaC+YRjpuV8ngSTg2zKJUEREREREREQue3+ZwDBNc4xpmgHAq6ZpBuZ+BZimGWKa5sAyilFERERERERELnNOrYEBzDMMoxKAYRj3GobxhmEYNV0Yl4iIiIiIiIhIHmfXwHgXaGAYRgPgeWASMAWIcVVgIiIiIiIiIm6nNTA8hrMjMLJN0zSB24HxpmmOBwJcF5aIiIiIiIiISD5nR2CcNAxjIHAv0CL3KSS+rgtLRERERERERCSfsyMwegBngYdM00wAqgGvuiwqEREREREREZECnBqBkZu0eKPA9h841sAQERERERERuWSZFmc/9xdXcyqBYRjGScDM3SyHY/rIKdM0g1wVmIiIiIiIiIjIn5wdgVFowU7DMLoCN7siIBERERERERGR8/2jsTCmaX4DtCzdUEREREREREREiufsFJJuBTYtwE3kTyn5S+WNy/eZuafNHHeH8P/t3Xd8FNX6x/HPk4AgEFoISZRubwhXUUEkCU1EQASVpoLY27WhgtIE9SoqFvCiIHYsKEWaSAe94g+VEgiKoIIIaQQIvYXz+2M3jSSwSDa7Id/365VXdmfO7D5nZ+bM7DNnzgZYRqADCKjdPu0hJ6+hp1YMdAgBdfGr9wQ6hIDpfuPrgQ4hoMql1Al0CAF1KGNXoEOQABlSwvf9hC8eCnQIAVW/69uBDiGg9iZ/G+gQREoEX39GtX2Ox4eA9UCHQo9GREREREREJIi4kJJ7UT7Y+JrACAEecs5tBzCzKsArQG8/xSUiIiIiIiIiksXXMTDqZyYvAJxz24CGfolIREREREREROQIviYwQry9LgAws6r43ntDREREREREROSE+JqEeAX43sy+xDN4503Ac36LSkRERERERCQIHA79Rz/eKX7gUwLDOfehmf2E56dTDejknFvt18hERERERERERLx8vg3Em7BQ0kJEREREREREipz6woiIiIiIiIhI0NNAnCIiIiIiIiIFcCG67h8stCZEREREREREJOgpgSEiIiIiIiIiQU8JDBEREREREREJehoDQ0RERERERKQAGgMjeGhNiIiIiIiIiIjPzKyqmc02s7Xe/1UKKLfezFaa2XIz++l4lz+SEhgiIiIiIiIicjz6AnOdc2cBc73PCxLnnGvgnLv0Hy6fRQkMERERERERETke1wEfeB9/AHQsiuU1BoaIiIiIiIhIAQ6fpGNgmNldwF05Jo12zo32cfFI51wigHMu0cyqF1DOAbPMzAFv53h9X5fPRQkMERERERERkRLGm0woMGFhZnOAqHxmPX0cb3Olc26zN0Ex28x+dc4tOs5QsyiBISIiIiIiIiK5OOdaFjTPzJLNLNrbeyIaSCngNTZ7/6eY2STgMmAR4NPyRzo5+8KIiIiIiIiIiL9MAXp6H/cEvjqygJmVN7OwzMdAa2CVr8vnRwkMERERERERETkeLwCtzGwt0Mr7HDM7zcxmeMtEAt+Z2QpgCTDdOTfzaMsfi24hERERERERESmAC9V1/yM559KAFvlM3wy09T7+A7j4eJY/Fq0JEREREREREQl6SmCIiIiIiIiISNBTAkNEREREREREgp7GwBAREREREREpgAuxQIcgXuqBISIiIiIiIiJBr1gnMJrENGPi3Fl8tWAuve69O8/8OmfU4/2JX/DDmtXccuftueYNGvYf5vz0f4z/Zkae5YqLQYMHs2DhQr6eOZMLLrww3zI1atZk8uTJzF+wgJEjR1K6dGkAzjjjDCZOmsSa337jzrvuKsqwC82J1N/X5YNVs5gYZs+bx7yFC7n73nvz1KsZewAAV21JREFULTNw8GDmLVzI9Bz1O6VMGSZ+9RXTvv6ar2fP5qFHHinKsAtNdJNLaTf5XdpPeZ/zb+tSYLmqF5xN159nUrPlVVnTOsz4iLZfjOaaz9/i6nFvFkW4harfyAk07vUc7R56Ld/5zjmefWcqre57mfaPvEHC75uy5i1a+htXPzCcVve9zOiJC4so4sLX76l/8/XMT5g46T3OO+/sfMt0796Jr2d+QsLqRVSuXCnXvEaNGjBh4li+mvIB73/wRlGEXKge69OLiZNe55NPh3HOOXXzLTN06IN8OeFVPvv8ZQYMvIfQ0FAAmsVcyiefDmPcuBf54MPnufjic4oy9ELxxJN389XUMXz+xUjOPfeMfMs893wfJn31Nl9MeJNBzzxEqVKhx7V8MCvJ9S/J+77afniy731Mm/4eX054i/POOzPfMl27dWDa9PeIXzmLypUrZk2vUKEcI0YM4YsvRzFx0miu69i6qMIuNAMGPMGcOV8xdernnH/+ufmWufnmLsyZ8xVr1y6jSpXKWdPr1avD+PEfkJDwf9x++y1FFLGIfxTbBEZISAhPDhnMg71up3OrNrTp0I66Z+ZuzNK3b2fY4CF8NOadPMtP/XIiD/TsXUTRFr7YuDjq1q1LbEwMT/Xrx3PPPptvub59+zJ27FjiYmNJT0+nSxfPl73t27czeNAgxowZU5RhF5oTrb+vywejkJAQBg8dSu+ePbm6ZUvad+jAmWedlatMbFwcderWpXlMDE/368cQb/0O7N/Pzd260e6aa2h/zTU0i4mhQcOGgajGP2YhIVza70Hm3/8U0zvdQe02cVSsVyvfcg0euoOkxT/nmTf3zj583eUevulxf1GEXKg6xf2Ldwb0KnD+oqW/sT4xjVlvPsbQezoyePRXAGRkHGbImCm8078X019/mGnfrmDdxuQiirrwXNXsCmrXrsE1bbozeNBLDBz0aL7lli5bye29H2XTpsRc08PCKjBg4KM8cH8/ruvQk0cfGVgUYReaJlc2oFbNKDpd/xDPPzeGvv1uz7fc1zO/5YbOj9C1Sx/KlDmFjh2bA/DjkpV07/YEPXo8ydAhb9F/QN7kfzBr2vRSatU6jeva38mzQ0bwVP/89+GvZyzg+uvu5sbO91O2TBmuv/7q41o+WJXk+pf0fb+kt/1Nr2pE7dqn0+7a2xjyzGv07//vfMstX5bAXXf2ZdOmpFzTu3btwO9/bODGG+7l9t6P06fPXZQqVXzupI+JaUrt2rVo2fI6Bgx4liFDnsq33NKly+nZ8x7+/ntzrunbt6czdOiLvPPOh0URrohfFdsExoUNLubvDRvYtHEjhw4e5Jup04lt3TJXmW1pW1kdv5JDhw7lWX7pkh9JT99eRNEWvtatWjFxwgQAli1bRljFikRUr56nXJMmTZgxw9PLZMKECbRu7ck4p6WlER8fz6GDB4su6EJ0ovX3dflgdHGDBmxYv56NGzdy8OBBpk2dSstWrXKVadmqFZO89Vu+bBkVc9Rvz549AJQqVYpSpUvjnCvaCpyg8AvPYdfGzezelMThQ4fY8M0CasQ2yVPu7G7XsXHud+zbur3og/SjRhfUpVJYuQLnz12ymo6xDTEzGpxTix2795GydQfx6/6mdnQ4NaOqckrpUlzbtD5zl/xShJEXjubNmzLlq28AiI9fTVhYBapVC89T7tdf1rJ5c1Ke6dde25I5sxeRmJgCwNZitn3ExDRi+oxFAKxatZawsPKEh1fOU+77/y3PepyQsI7qkVUB2Lt3f9b0U08tQzHb/YmJu4JpU+cBsHLlGsLCylOtWpU85b777qesx6tW/Ub1yGrHtXywKsn1L+n7fklv++PimjB1ymwA4uN/9W67VfOU+/XX39m8OW+CxjkoX87z+ZUrdyrp6TvJyMjwb9CFqGXLGCZPngbA8uUrCQsLIyKiWp5yq1evyZO8A9i6dRsrV67O9zuR+OZwqJ2Uf8WRTwkMM5vry7SiFBEZSdLm7B00JTGJ6pGRAYyoaEVGRbF5c3Z2NSkpiagj6l+lShV27NiR1UAnJiYSGRVVpHH6y4nW35flg1VkVBSJidnbflI+6/Vo9QsJCWHqjBksWbqU/337LSuWLy+SuAvLqdWrsTspNev5nuQtlKte7Ygy4dSIa8q6L6blfQHniBv1Am0+eZMzOrf1d7hFLnnrDqKqZXebjgqvSPLWHSSnpRMVnj09MrwSyVt3BCLEE1K9ejWSklKynicnpxIZmfckriB16tSkYsUw3nv/dcZ/MYYOHa72R5h+ExFRheSktKznKclpVK+e9yQ+U2hoKG3bNmPx9yuypsXGNuKLL4fz6mt9GTpklF/jLWzVq4eTlJy9/ycnb6F69bxfYjOVKhXKte3i+P5/P/+j5YNNSa5/Sd/3j+Xkb/vDSUr659vup59+Rd16NZk771MmTHybF18YVawu4ERGVicxMTsxl5SUTGRk8bjwJlLYjtp3yszKAuWAamZWBchM01QETjvKcncBdwHUrBpBtbCKBRX9x8zyZoyKU0N0onyp/8n8GZ1o/YvzZ5NvrvQ46n748GHat21LWMWKvDV6NGeffTa//fabHyL1Ex/W3SWP38fy19/BHT6cp+zsXo+wNzWNMlUq0/ytF9jx50ZSl670W7hFLb/N2MzIb+sujnn3E913Q0NDOf+Cs7m99yOUKVOGTz4dxYoVCWzY8Hdhhuk3x1v/vn1vZ9nSX1i+/NesaQsW/MiCBT/SsOF53HNPF+6/v/jcQmf5bLVHW/39nrqPpT+vYtmyhH+0fLApyfUv6fv+sZTItv84lr/yyktZs+YP7rj9CWrWPI3Ro1/ghhvuYffuPYUXpB8V5/NWkcJ2rJu/7gYexpOs+JnsNm8HUODod8650cBogH/VOdMve1dKUhJRp0VnPa8eHUVqSspRlij+brn1Vrp17QrAivh4TjstO4cUFRVF8hH137p1KxUrViQ0NJSMjAyio6NJSS5+9z1mKsz6JyUmHnP5YJWUlER0dPa2HxUdTfIR6zWzfpmjP+RXv507dvDD4sU0i40tVgmMvcmplI+KyHpeLrIae1PTcpWpev5ZXPmi5/7QMpUrcVrTRriMDP6e/31W2f3btvP3/P8RfuE5J1UCIyq8Iklb0rOeJ6XtoHqVMA4eyiApLXt6clo61asWfnLZH7p1u54bbmwHwKqVvxIVlX3VKTIygpSUtIIWzSM5OZVt29PZu3cfe/fu46efVnDOuWcG9ZeYG29sTceOLQBYvfp3IqPCwduhonpkOKmp2/Jd7o47b6BylYo8//wr+c5ftuwXTq8RSaVKYaSn7/RL7IXhpi7X0qlTGwASEn4jKjJ7/4+MrEZqav7r/667u1GlSiWeHToya1pyyhaflw8WJbn+JX3fPx4nY9vfpWt7Ont7SiasWkNU1BHb7nGs/+s6tubdsZ8DsHHjZjZtSqJu3ZqsWrWmcIMuRD163ESXLp0AiI9PIDo6u7dtVFQkKSmpBS0qclI76i0kzrnXnXN1gT7OuXrOubrev4udcyOPtqy/JayIp2ad2pxWowalSpfm6vbXsnB2QO9q8buPPvyQtm3b0rZtW2bNmkWnzp0BaNiwITt37sw3gbN48WLatvU0/p07d2bW7NlFGnNhKsz6z54zx6flg1H8ihXUqVuXGjVrUrp0adq1b8/cI9brnDlzuN5bvwY56le1alXCKnpOXMqUKcOVTZvy+7p1RV6HE5GWsIawWqdT/rQoQkqVovbVsWxauDhXmSnX3sqUtrcwpe0tbJzzLT8+P4K/539PaNmylCp3KgChZcsS1fgS0tetD0At/Kd5o/OYvGAZzjmWr/mLsHJlqV61IhedeTrrE7ewMXkrBw4eYvp38TRvdF6gw/XJp59OonOn2+nc6Xbmzv2WDtd5un7Xr38+u3buZssW309i5837jksuqU9oaChly5ahfv3z+OP3Df4KvVB88cUsevR4kh49nmTBgh+5tm0zAC688Cx27dpDWtr2PMtcd11zGl9Rn/5Pv57rKl2NGtm3yp1zTl1Kly4V1MkLgPGfT6drlwfp2uVB5s//gXbtPQOSXnTROezatZstW/ImcK6/vjVNmlxCv77DctV/4YL/82n5YFKS61/S9/3jcTK2/Z9/NpWbbryXm268l3nzvqd9B894X/Xrn8vOXbvZsmWrz6+VlJjC5Zd7Bi2vGl6Z2nVq8PffeceKCCbjxo2nQ4eudOjQlTlz5tOxoyeZ16DBRezcuYvU1C0BjrBkcSF2Uv4VR+Zr9yMzuxA4HyibOc05d8yhbP3VAwPgytgY+gzsT0hoKFPGf8HYN0fRuUc3ACaM+5TwiGp8PGUy5StUwLnD7Nm9hxtatWH3rl08/8arXHLF5VSuUoWtW9J469XX+Wr8F4Ua31bn3wEyhwwdSkxMDHv37uXxPn1YudJzFfm999/nySeeICUlhZo1azJi5EgqV65MQkICjzz8MAcOHCAiIoIpU6dSoUIF3OHD7N6zh1YtW7Jr1y6/xlyYTqT+R1u+sIQeu8g/FhsXR/+BAwkJDeXL8eP578iRdOvRA4BPx40DYPDQoTSLiWHf3r086a3fOeeey0vDhxMaEkJISAjTp01j5Bv++Sm5oVXy/4m7wnBa08v41+P3YiEh/PHVNyS88wln3uA5sK/7Mve4F1cMeZxNi35g45xvKX96FM2GDwbASoWy4ev5JLzziV9i7D7uHr+87qPDP2PJqj/ZtnM34ZUq8GDXlhzyjvPS7erLcc4xZMwUvl22llPLlOb5Bzpz0Zk1AFj48xqef3caGYcdnVtcwr03xPklxgtufN0vr5upf/9HuLLpZezbt5/+T/+HhATPFbRRbw1j4IAXSU1No8fNnenduxvVqlVl69btLFr0A4MGDgPgtt5duf76thw+fJgJX07no48Kt+0vVy762IVOwBNP9KZxk4vZt+8AQ54ZxS+//AHAa6/35dmhb7NlyzYW//AJSUmp7Nm9D4D585fwzjsTuLVnB65t24xDhzLYt/8Ab7z+MStWFO4VyEMH/Xsc6dvvXppceQn79u1n8MBXWb3ak4QdMXIwQ555g9TUrfz48xQSE1PYs3svAPPmfc/otz896vLFRTDX/8BB/ybDgn3fT/jioUJ9vZyKQ9tfv+vbfnndTE89/QBXXnkp+/btZ0D/l1m9ei0Ab/73WQYPGk5q6la6d+/Ibb1vJDzcs/6/+3YJgwe/SkREVYY++zgREVUxjLHvfs70aYV74XPvPv/2iBg0qC/NmjVh79599O07mFWrVgMwZswInn56CCkpqdx6azfuvLMn1aqFk5a2jYULv+Ppp4dQrVo4kyaNo0KF8hw+7NizZw/XXNOZXbt2F1p8a9cuK57fhn10ZZ9lJ+U9O/97uWGxW28+JTDMbBAQiyeBMQO4BvjOOXfDsZb1ZwIj2Pk7gSHBzZ8JjOLAnwmM4sBfCYziwN8JjGDn7wRGsPN3AkOCl78TGMHOnwmM4sDfCYxg5+8ERrBTAqN4Ko4JDF9/RvUGoAWQ5Jy7DbgYKOO3qEREREREREREcvA1gbHXOXcYOGRmFYEUoJ7/whIRERERERERyXasXyHJ9JOZVQbG4Pk1kl3AEn8FJSIiIiIiIhIMiuuAlycjnxIYzrn7vA/fMrOZQEXnXLz/whIRERERERERyebTLSRmdr2ZVQJwzq0H/jKzjn6MS0REREREREQki69jYAxyzqVnPnHObQcG+SUiEREREREREZEj+DoGRn6JDl+XFRERERERESmWXGigI5BMvvbA+MnMhpvZGWZWz8xexTOYp4iIiIiIiIiI3/mawHgQOAB8DowH9gL3+ysoEREREREREZGcjnkbiJmFAl8551oWQTwiIiIiIiIiInkcM4HhnMswsz1mVinnQJ4iIiIiIiIiJzsXYoEOQbx8HYhzH7DSzGYDuzMnOuf+7ZeoRERERERERERy8DWBMd37JyIiIiIiIiJS5HxKYDjnPjCzU4Fazrk1fo5JRERERERERCQXn36FxMzaA8uBmd7nDcxsih/jEhEREREREQm8kJP0rxjyNezBwGXAdgDn3HKgrl8iEhERERERERE5gq8JjEP5/AKJK+xgRERERERERETy4+sgnqvMrDsQamZnAf8GvvdfWCIiIiIiIiIi2XztgfEgcAGwH/gESAce8ldQIiIiIiIiIiI5+doD43zvXynv33VAB6C+n+ISERERERERCbzQQAcgmXxNYIwD+gCrgMP+C0dEREREREREJC9fExipzrmpfo1ERERERERERKQAviYwBpnZO8BcPONgAOCcm+iXqEREREREREREcvA1gXEbcC5QmuxbSBygBIaIiIiIiIicvHz96QvxO18TGBc75y7yayQiIiIiIiIiIgXwNZf0g5md79dIREREREREREQK4GsPjKZATzP7E88YGAY455x+RlVERERERERE/M7XBEabf/oGh3H/dNFiz9cP92R1CAt0CAFVOtABBNiAHZsCHUJAdQ90AAG0Z/eGQIcQUJ/UOBDoEAKq45rEQIcgAdI2rEagQwio+l3fDnQIARX/2d2BDiGg2jz6V6BDEH/SGBhBw6fv2M65kn02KiIiIiIiIiIBpVySiIiIiIiIiAQ9JTBEREREREREJOiV9GEaRERERERERApkuuwfNLQqRERERERERCToKYEhIiIiIiIiIkFPCQwRERERERERCXpKYIiIiIiIiIhI0NMgniIiIiIiIiIFsBAX6BDESz0wRERERERERCToKYEhIiIiIiIiIkFPCQwRERERERERCXoaA0NERERERESkAKbL/kFDq0JEREREREREgp4SGCIiIiIiIiIS9JTAEBEREREREZGgpzEwRERERERERAoQEhroCCSTemCIiIiIiIiISNBTAkNEREREREREgp4SGCIiIiIiIiIS9DQGhoiIiIiIiEgBQnTZP2hoVYiIiIiIiIhI0FMCQ0RERERERESCnhIYIiIiIiIiIhL0lMAQERERERERkaCnQTxFRERERERECmAhLtAhiJd6YIiIiIiIiIhI0CvWCYwmMc2YPHc2UxbM47Z7784zv84Z9fhg4hcsWbOaW++847iWDXbNYmKYNW8ecxcu5O577823zIDBg5m7cCHTZs7kggsvzDUvJCSEKTNmMPrdd4siXL8YNHgQCxYu4OuZX3PBhRfkW6ZGzRpMnjyZ+QvmM3LkSEqXLg3AGWecwcRJE1nz2xruvOvOogy7UDSNieHreXP5ZuEC7ixg/T89eBDfLFzAVzO/5vwcn09YxYq8Puq/zJg7l+lz59DgX/8qqrAL1cCBTzFv3kymz5jEBRecl2+ZGjVOZ8LEz5g772veeOOVrPVfIawCo8e8ybTpE/l65hQ633B9UYZ+QvqNnEDjXs/R7qHX8p3vnOPZd6bS6r6Xaf/IGyT8vilr3qKlv3H1A8Npdd/LjJ64sIgiLlzNYmKYO28e8xcu5J4Ctv1Bgwczf+FCvj6i7XvxpZf48eefmTlrVlGFW+jCLr2Cc8Z+zrnvfUH1LrfkmV++/r+4cNIczh71IWeP+pDIHr2z5lXr1JVzRn/C2aPHUavfEKz0KUUZeqEoyeu/JNcd4PwrL2fg1E8ZPONzWt1+c575ja5tzVMTP+CpiR/w2Mdvcfo5Z2bNi735Rp6e9BH9J39M3M03FWXYherJvvcxbfp7fDnhLc4778x8y3Tt1oFp098jfuUsKleumDW9QoVyjBgxhC++HMXESaO5rmProgr7hJX0416me++N5d33bmPUqJs588zq+ZZ55JFW/HfUzYwadTNP929H2bKls+bVr1+DN//bg7dH38qwl24sqrBFCl2xTWCEhITQb8hg7u/Vm06trqZNh/bUOzN3Y56+PZ1hg4fw4Zixx71sMAsJCWHw0KHc3rMnbVq2pF2HDpx51lm5ysTExVGnbl1axMTQv18/nnn22Vzze/Xuzbp164oy7EIVGxdL3bp1iY2J5al+T/Hcs8/lW65v376MHTuWuNg40tPT6dKlCwDbt29n8KDBjBkzpgijLhwhISEMHDqEO3v2ol3LVlzboQNnnJV7+20WF0vtunW5OiaWgf2eYlCOz+fpQYP4duFC2rZoQcc21/B7MdwOYmObUadObZo3b8PTTw1iyNBB+ZZ74snHeO/dD2jR/BrSd+zgxps6AXDLLd1Zt+532l3biR7de/LUU09kJTeCXae4f/HOgF4Fzl+09DfWJ6Yx683HGHpPRwaP/gqAjIzDDBkzhXf692L66w8z7dsVrNuYXERRF46QkBCGDB1Kr549ad2yJR3yaftivW1fXEwM/fr149kcbd+EL76gV8+eRR124QkJ4fQH+vDn04+w5s5uVI5tTZladfIU271yOb/deyu/3XsryeM8SepS4RFU63gTvz1wG7/d1QMLCaFybKsirsCJKcnrvyTXHcBCQrip/2O8ee9jDO3Qg0vbtiSqXp1cZbZs2syrvR7g+U49+fqt9+k+6AkAos+sy5WdOzCs2x0837knF8Y0IaJWjQDU4sQ0vaoRtWufTrtrb2PIM6/Rv/+/8y23fFkCd93Zl02bknJN79q1A7//sYEbb7iX23s/Tp8+d1GqVPG4k7wkH/cyNWpUh9NOr0zv297j9dfn8MCDzfMt9/bbC7nv3o+5996PSU3ZQYcODQAoX74M9z/QnMGDpnD3XR/y3LPTijB6kcLlUwLDzK70ZVpRurDBxWzcsIFNGzdy6OBBvpk6jdjWLXOV2ZaWRkL8Sg4dOnjcywazixs0YMP69WzcuJGDBw8yfepUWrbKfSLaslUrJk2YAMDyZcuoWLEiEdU92dqoqChimzdn/GefFXnshaV1q9ZMnDARgGXLlhFWMYyI6hF5yjVp0oQZM2YAMGHCBFq39lxxSEtLIz4+nkMHDxVd0IWkfoMG/LV+A3971/+MqVNp0Sr3lZQWrVrzlffzWbFsGRW9n0/5ChW49PLL+PKzzwE4ePAgO3fsKPI6nKiWLZszaZLnBGX58nhP/SKq5SnXuPHlfP2154rjxAmTadWqBeC5WlO+fHkAypUrR/r2dA4dKh7bQqML6lIprFyB8+cuWU3H2IaYGQ3OqcWO3ftI2bqD+HV/Uzs6nJpRVTmldCmubVqfuUt+KcLIT9yRbd/UqVNpdUTb16pVKyYW0PYtWbKE7du3F3XYhabcOedzYPPfHEjajDt0iO0LZ1OpSTOfl7fQUELKlIGQUELKlOXg1lQ/Rlv4SvL6L8l1B6hz0Xmk/vU3aX9vJuPQIX7+ei71m1+Vq8yfy1exd8dOz+P4BCpHes956tXhz/gEDu7bz+GMDNb+tJyLW/i+3wSLuLgmTJ0yG4D4+F8JCytPtWpV85T79dff2bw575d056B8Oc+xo1y5U0lP30lGRoZ/gy4kJfm4l6lx4zOYO8cT+6+/JlGhfBmqVi2fp9yePQeyHp9SphQOz7gNcXHn8P3/1pGa6tlH0tP3FkHUJ5eQkJPzrzjyNewRPk4rMtUjI0nanJj1PDkxieqRkX5fNhhERkWRmJgdf1JiIpFRUXnLbN6cXSYpiUhvHfsPGsSLzz+PO3y4aAL2g8ioSDYfUb+oyNyfQZUqVdixY0fWAToxMZHIqOKzngsSGRVJYmKOuudTr8ioyHzWfxQ1a9Via1oa/3n5ZSbOmM7QF1/g1FNPLbLYC0tkVHU2J2ZfXUpKSibqiM+gSpXK7NyRfYKWlJRMlHcf+OjDcZx5Rj0W/7CQGV9/xZChz+PcyTE4U/LWHURVq5T1PCq8Islbd5Cclk5UePb0yPBKJG8tXsmrqHzavqhjtH2JSUlZ6724K10tggOpKVnPD6amUDo8b+K23PkXcfaoj6j73KuUqV0XgENpqaR+MY7zPp7MBZ9NI2PPbnb9vKTIYi8MJXn9l+S6A1SuHsG2pOxtf3tyCpXzuWiRqUmndiR89wMAm9f9wZmXXEz5ShUpXbYMF1zVmCrF8FygevVwkpKyk47JyVuoXj3c5+U//fQr6tarydx5nzJh4tu8+MIoHfeKkfBqFbKSDwCpW3YRHl4h37KPPtaaTz+7i5o1qzLlq+UAnF6jChUqlGHYsBsYMbI7LVrmf+utSHFw1ASGmTU2s8eACDN7NMffYCD0KMvdZWY/mdlPaTv901CYWZ5pvrbDJ7JsMMgbPXkOQvnX0RHXvDlpaWkkrFrlp+iKRkH1O94yxZMP9Sqg7qVCQzn/wgv59OOP6dT2Wvbu2cud9+V/L3Uw+8fr33sl4qpmTVn9y680viKG9u06MXhwfypUyHslozjKbxM3M/Lb8vNrS4LZibR9J4d8PoEjqrZ33a/8cnNHfrv3FrZMHk/dwcMACK0QRsUmzfjl1k4kdGtHSNmyVG7RpghiLjwlef2X5LoDBR7T8nNWo3/RpFM7vhr+XwCS/9jA7HfH8cCY13jgreFs+m0dh4tJz4Oc8j+m+e7KKy9lzZo/aNG8GzfecC9PPfUA5csX3KuhODmZj3uZfGkDMg1/ZRY9uo/hr7+20izmbABCQ0M486xIBgyYzNNPTaR798s5/fTK/gtYxI+OdfPbKUAFb7mwHNN3ADcUtJBzbjQwGqBBnTP8cvRMTkoi6rTorOeR0VGkpvh2X9uJLBsMkpKSiI7Ojj8qOpqU5NzxJyUmEn3aadlloqJISUnhmrZtadGyJTGxsZQpU4YKYWG88tprPPbww0UV/j92y6230K1rNwBWxK/gtCPql3zEOty6dSsVK1YkNDSUjIwMoqOjSUlOobhLTkoiOjpH3fOpV3JiUj7rPxnnPPPily8H4JsZM4pNAuPmW7rRpYtn0KmV8Ss5LTqKn73zoqIiST7iM9i6dRthFcOy1n/OMjfccD1vvfUOABs2/MXfG/+mXr16xMevLLL6+EtUeEWStqRnPU9K20H1KmEcPJRBUlr29OS0dKpXrZjfSwStxHzavuRjtH3RUVEkpxT//R7g4JYUTonIHritdET1PLeBHN6zJ+vxzh8XY6GlCK1YiQoXX8KBpM1kpG8HIP27BZQ//yK2z51ZJLEXhpK8/kty3cHT46JKVPa2XzmyOumpW/KUO+3sM+gxpC//vecxdqdnX0BbPHEaiyd67vnv8NDduXpzBLMuXdvTuXNbABJWrSEqKrvXSWRkNVJT0nx+res6tubdsZ7bRzdu3MymTUnUrVuTVavWFG7QAXCyHvfat7+YNtd4BuP97bdkIiKyv4pFVKvA1q27C1z28GHHooVruOHGS5k9azVbUnexI30v+/cfYv/+Q6xauYl69SLYtGm7v6shUuiO2gPDObfQOfcMcIVz7pkcf8Odc2uLKMZ8JayIp1adOpxWowalSpfm6vbtWDh7rt+XDQbxK1ZQu25datSsSenSpbm2fXvmzp6dq8zcOXO4vnNnABo0bMjOnTtJTUnh5WHDaHrFFcQ2bcrDDz7I4u+/LxbJC4CPPvyItm3b0rZtW2bNmkWnzp4BGRtm1S/v/dyLFy+mbVvPwb9z587Mml18R2DPtHLFCmrXrcPpNWtQunRp2rZvz7wj1v+8ObO5zvv5XJzj89mSmkpi4mbq1qsHQOMrr+T3tQHdlX328Uef0r5dJ9q368Ss2XO5/vrrAGjQoL6nfvmczP7wwxKuucYzPkinzh2ZM2ceAJs3J9KkyRUAhFcLp269umzcuLGIauJfzRudx+QFy3DOsXzNX4SVK0v1qhW56MzTWZ+4hY3JWzlw8BDTv4uneaPi1YU0fsUK6uRo+9q3b8+cI7b9OXPm0Cmftu9ksGfNL5xyek1OiYrGSpWickwr0hd/m6tMqSrZ98Sfes75EGJk7EjnYGoy5c+9ECtTBoAKDS9l/1/rizL8E1aS139JrjvAhlW/Ur1WDcJPjya0VCkuuaYFK+d/l6tMlahI7nrteT7oN4SUDbnb8wpVK2eVubhFDD99PaeoQj8hn382lZtuvJebbryXefO+p30Hz7gn9eufy85du9myZavPr5WUmMLllzcEoGp4ZWrXqcHffyceY6ni4WQ97k2duoL77xvH/feNY/H3v2fd9nHuuVHs3nMg3wRG9GnZt8xcfkU9Nm70bCOLF//OBReeTkiIUaZMKc45N4q//vJ9+5HAj1WhMTCy+Tr88B4zewm4ACibOdE5l/8QuEUgIyODFwY+w6gP3yckNISvxn/J72vXckMPzxX6L8d9SnhENT6ZMpnyFSrgnKNH7150atWG3bt25btscZGRkcEzAwfy3ocfEhoayhfjx7N27Vq69egBwKfjxrFg3jxi4+KYt2gRe/fu5ck+fQIcdeGaP28+cXFxLFy0kL179/J4n8ez5r33/ns8+cSTpKSk8MJ/XmDEyBE81ucxEhISGP/5eAAiIiKYMnUKFSpUwB129O7dm1YtW7Fr165AVclnGRkZDB04kLEffkhIaCgTxo9n3dq1dPGu/8/HjWPhvPk0i4tj1qKF7Nu7l6dyfD7PDhrMS6+/RunSpdn410aeKobbxoL5i4iNbca8+TPZt28fTz7xdNa8se++Rb++A0hJSWXYi6/w+hsv8+ijD5Gw+he+GO8Z4G7kiFEMe+l5Znw9GcMY9uJwtm3bHqDaHJ9Hh3/GklV/sm3nbprd8QIPdm3JIW936G5XX07MJeewcOkaWt33CqeWKc3zD3i+0JQKDWXgHR24Y8h7ZBx2dG5xCWfVKl73gWdkZDBo4EA+9G77mW1fd++2/8m4ccyfN4+4uDgWeNu+J3Js36+/8QZXNG5MlSpV+P6HH3jt1VcZ//nngarO8TucwaaRL1Pv+dchJISt30xj/4Y/Cb/W8zPAadMnUemq5lRr1wmXkcHhA/vZ8PwAAPb8msD2b+dx9n8/wGVksHfdb6TNmBzAyhy/krz+S3LdAQ5nZDD++Ve5/+3hhISGsnjSNBJ//5OmN3UE4Lvxk7nm3tsoX6kiXft76p2RkcGwLrcDcOerz1O+ckUyDh1i/HOvZA32WZx8++0Srmp2GdNnvM++ffsZ0P/lrHlv/vdZBg8aTmrqVrp378htvW8kPLwqX054m+++XcLgwa/y9tvjGPrs40yY+DaG8dprY9m+vXiMB1GSj3uZliz5k0aN6vDue7exf/8hhr+SfUFuyNCOvPbqbLZt202fPm0oV+4UzOCPP1IZOcJz4Wbjxq38/NN6Rr11C845Zs5cxYYNvvfgEQkm5sv9kWY2C/gc6APcA/QEUp1zTx5rWX/dQlIc7HLF41cN/OVQsb3TsHCUPXaRk9rB0JPj3tp/6vepQwMdQsDUbftooEMIqMnnRB+70Ems45qT46quHL+2YcXv50kL07d2coyl9E/Ff3Z3oEMIqDaP/hXoEAJq5jePnNQn/i3fXHZSfqedc3/DYrfefO04Eu6cGwsc9N5W0hu4wo9xiYiIiIiIiIhk8fUWkoPe/4lmdi2wGSjZaXYRERERERE56RXX8SJORr4mMJ41s0rAY8AIoCLwiN+iEhERERERERHJwacEhnNumvdhOhDnv3BERERERERERPLyqTOMmX1gZpVzPK9iZu/6LSoRERERERERkRx8vZunvnNue+YT59w2oKFfIhIREREREREROYKvY2CEmFkVb+ICM6t6HMuKiIiIiIiIFEsaxDN4+JqEeAX43sy+BBxwE/C836ISEREREREREcnB10E8PzSzn4DmgAGdnHOr/RqZiIiIiIiIiIiXTwkMM/vIOXcLsDqfaSIiIiIiIiIifuXrLSQX5HxiZqHAJYUfjoiIiIiIiEjw0BgYweOoq8LM+pnZTqC+me3w/u0EUoCviiRCERERERERESnxjprAcM79xzkXBrzknKvo/QtzzoU75/oVUYwiIiIiIiIiUsL52hlmmpmVBzCzm81suJnV9mNcIiIiIiIiIiJZfB0DYxRwsZldDDwBjAU+BGL8FZiIiIiIiIhIoIWGuECHIF6+9sA45JxzwHXA686514Ew/4UlIiIiIiIiIpLN1x4YO82sH3Az0Mz7KySl/ReWiIiIiIiIiEg2X3tgdAH2A7c755KA04GX/BaViIiIiIiIiEgOPvXA8CYthud4/heeMTBERERERERETlohvl72F7/zKYFhZjuBzJFLTsFz+8gu51wlfwUmIiIiIiIiIpLJ1x4YuQbsNLOOwGX+CEhERERERERE5Ej/qDOMc24y0LxwQxERERERERERyZ+vt5B0yvE0BLiU7FtKRERERERERET8ytefUW2f4/EhYD3QodCjEREREREREQkiGsQzePiawAgBHnLObQcwsyrAK0BvP8UlIiIiIiIiIpLF11xS/czkBYBzbhvQ0C8RiYiIiIiIiIgcweceGGZWxZu4wMyqHseyJdYhLNAhBFSpEj5MyuESvv4PHz4Y6BAkQKpFXBHoEAKqX6XugQ4hoGrWnBvoECRAVgY6gADbm/xtoEMIqDaP/hXoEAJq5vBagQ5BpETwNQnxCvC9mX2JZ/DOm4Dn/BaViIiIiIiISBAI1RgYQcOnBIZz7kMz+wnPT6ca0Mk5t9qvkYmIiIiIiIiIePl8G4g3YaGkhYiIiIiIiIgUOXWGEREREREREZGgp4E4RURERERERAoQUrLH5g8q6oEhIiIiIiIiIkFPCQwRERERERERCXpKYIiIiIiIiIhI0NMYGCIiIiIiIiIFCNVl/6ChVSEiIiIiIiIiQU8JDBEREREREREJekpgiIiIiIiIiEjQUwJDRERERERERIKeBvEUERERERERKUCILvsHDa0KEREREREREQl6SmCIiIiIiIiISNBTAkNEREREREREgp7GwBAREREREREpQKgu+wcNrQoRERERERERCXpKYIiIiIiIiIhI0FMCQ0RERERERESCnsbAEBERERERESmAxsDIy8yqAp8DdYD1wE3OuW1HlDnHWyZTPWCgc+41MxsM3Amkeuc95Zybcaz31aoQERERERERkePRF5jrnDsLmOt9notzbo1zroFzrgFwCbAHmJSjyKuZ831JXoASGCIiIiIiIiJyfK4DPvA+/gDoeIzyLYDfnXMbTuRNlcAQERERERERkeMR6ZxLBPD+r36M8l2BT4+Y9oCZxZvZu2ZWxZc31RgYIiIiIiIiIgU4WcfAMLO7gLtyTBrtnBudY/4cICqfRZ8+zvc5BegA9MsxeRQwFHDe/68AvY/1WkpgiIiIiIiIiJQw3mTF6KPMb1nQPDNLNrNo51yimUUDKUd5q2uApc655ByvnfXYzMYA03yJuVgnMJrENOOJgQMICQ1l0uef896ot3PNr3NGPZ556UXOu+ACRr48nA/HvOPzssXBoMGDiIuLY+/evfTp04eEVQl5ytSoWYORI0ZSqXIlElYl8Mgjj3Dw4EHOOOMMXnr5JS644AJefvllxoweE4Aa/HPNYmLoP2gQoaGhjP/sM94eNSpPmQGDBxPr/Xye7NOHhFWrOKVMGT4dP55TTjmFUqVKMXPGDF5/9dUA1ODEXBUTw9ODBhIaGsoXn33O6Hzq33/wIGK89e/bpw+rc2wfISEhTJw2leSkJO7ufXtRhl5oBg0aQGxcDPv27qVPnydJSFidp0yNGjUYMfI1KlWqREJCAo8+8jgHDx7k8isuY/Tot/j7778BmDlzFiPeGFnUVfhH+o2cwIKffiW8Unmmvf5wnvnOOZ4bO42FS9dQtswpvPBAZy4443QAFi39jefencbhw4e5sWUj7uoUU8TRF47H+vTiyisbsm/ffp4ZPIo1a/7MU2bo0Ac57/x6HDqUQULCOp5/bgwZGRk0i7mUe+65CXfYcSgjg+GvfMCKFWsCUIt/7u7bLqLRv6qzf38Gw99cxu9/phdY9p7eF9Eqrhadb5kOwBWXRnFL13M57OBwhuPt91ey+tetRRV6ofj3Q525ovH57N93gP88P47ffvs7T5kBA2/lnHNrcuhQBr/88hcvD/uMjIzDlC9flv4DbyUysgqhoSF89uk8vp7xfwGoxT93IvWvEHYqfft15/TTqnHgwCFe+M8n/PlnYgBq8c+U5LoDDBjwBDExV7J37z6efHIQq1f/mqfMzTd3oVev7tSuXYvLLotj27btANSrV4cXXniGCy44l+HDRzJ27EdFHP2Ju/feWBpdVpf9+w7yyiuzWLcu73elRx5pxVlnR2LA35u288rL37Bv30EA6tevwd33xFCqVCjp6Xt54vEvirgG/4yO+xLEpgA9gRe8/786StluHHH7SGbyw/v0emCVL29abDvDhISE0G/IYO7v1ZtOra6mTYf21DvzzFxl0renM2zwED4cM/a4lw12sXGx1K1bl9iYWJ7q9xTPPftcvuX69u3L2LFjiYuNIz09nS5dugCwfft2Bg8azJgxxStxAZ71N3joUG7v2ZM2LVvSrkMHzjzrrFxlYuLiqFO3Li1iYujfrx/PPPssAAf27+eWbt1of801tL/mGq6KiaFBw4aBqMY/FhISwqChQ7izZy/atmxFuw4dOOOs3NtvTFwsderWpVVMLAP6PcUzR2wfPXvfxu/r1hVh1IUrNjaGOnVrExfbkn5PDeDZ54bkW65v38cZO/Y9mse1Ij19Bzd1uTFr3o8//sS1bTtwbdsOxSZ5AdAp7l+8M6BXgfMXLf2N9YlpzHrzMYbe05HBoz3HkoyMwwwZM4V3+vdi+usPM+3bFazbmFzg6wSrJlc2oFbNKDpd/xDPPzeGvv3yT8B9PfNbbuj8CF279KFMmVPo2LE5AD8uWUn3bk/Qo8eTDB3yFv0H3F2U4Z+wSxtW5/To8tzx4FzeeHsFD9x5cYFlz6pXmQrlS+eatnxVKvf3WcCDjy/g1f8u46F7Gvg54sJ1xRXnU6NmBN27DuWllz7n0T435Vtu9qyfuLn7c/S69QXKlClNu/ZNALi+01VsWJ9E714v8u8HR3D/Ax0pVSq0KKtwQk60/rfc0pp1azdxW68Xee7Zj/j3Q52KMvwTUpLrDhAT05TatWvRsuV1DBjwLEOGPJVvuaVLl9Oz5z38/ffmXNO3b09n6NAXeeedD4si3ELXqFEdTju9Mr1ve4/XX5/DAw82z7fc228v5L57P+beez8mNWUHHTo0AKB8+TLc/0BzBg+awt13fchzz/p0oTcolPTjvgS1F4BWZrYWaOV9jpmdZmZZvyhiZuW88ycesfwwM1tpZvFAHPCIL29abBMYFza4mI0bNrBp40YOHTzIN1OnEds6dw+XbWlpJMSv5NChg8e9bLBr3ao1Eyd4toFly5YRVjGMiOoReco1adKEGTM828+ECRNo3bo1AGlpacTHx3Po4KGiC7qQXNygARvWr2fjxo0cPHiQ6VOn0rJVq1xlWrZqxaQJEwBYvmwZFStWJKK6Z1yZPXv2AFCqVClKly6Nc65oK3CC6jdowIb1G46of+tcZVq0as0k7/ax4ojtIzIqitjmzfnis8+KPPbC0qp1SyZOnAzA8mXLqRgWRkRE3u2/cZMr+HrGTAAmTJhI62K2n+en0QV1qRRWrsD5c5espmNsQ8yMBufUYsfufaRs3UH8ur+pHR1OzaiqnFK6FNc2rc/cJb8UYeSFIyamEdNnLAJg1aq1hIWVJzy8cp5y3/9vedbjhIR1VI+sCsDevfuzpp96ahmK2e7PFY2imbtwIwBr1m6jfPnSVKlcJk+5kBDofcv5jP0od8+8ffsysh6XLRta7Orf9KqL+GbmEgBWJ6ynQoVTCQ+vmKfcDz9k98j6ZfUGIqpXAsA5OLWc5/Mqd+op7Nixh4yMw0UQeeE40frXqRPFzz//BsBff6UQFR1OlSphRRD5iSvJdQdo2TKGyZM9X7qXL19JWFgYERHV8pRbvXoNmzbl7Vmydes2Vq5czaFDxe+8D6Bx4zOYO8dzzPr11yQqlC9D1arl85Tbs+dA1uNTypTC4Wnk4uLO4fv/rSM1dScA6el7iyDqwlHSj/sSvJxzac65Fs65s7z/t3qnb3bOtc1Rbo9zLtw5l37E8rc45y5yztV3znXI0RvjqHxKYJjHzWY20Pu8lpld5nv1Cl/1yEiSNmfXMTkxieqRkX5fNlhERkWyeXN2dj0pKYmoyNzjq1SpUoUdO3aQkeE5YU1MTCQyqnjVMz+RUVEkJmavv6TERCKjovKWOeLzifSu45CQEKbMmMH/LV3Kd99+y4rly4sk7sISGRVJUmKOuuWzXiOjIknKUf/kpCQivdvH04MGMuz5/3D4cDH75pJDZGQkiTn24cSkJKKO+Aw82//OrO0/KTF7GwD4178aMOPrKbz3/jucdVbx6oF1NMlbdxBVrVLW86jwiiRv3UFyWjpR4dnTI8Mrkbx1RyBCPCEREVVITkrLep6SnEb16lULLB8aGkrbts1Y/P2KrGmxsY344svhvPpaX4YOyXv7VTCrVrUsqWnZJ95b0vZSreqpecq1b1OP//spiW3b9+eZ1/iyaN5+rTnP9LuC10Yt82u8ha1atUqkpGzPep6asp1qObb3I4WGhnD11Y1Y8oPnpH3ihEXUrh3FpMlDee+Dfrzx+oRilcQ+0fqvW7eJZs08vXbOO68WkZFViKhe2Z8hF5qSXHeAyMjqJCYmZT1PSkomMvJYA/6fPMKrVchKPgCkbtlFeHiFfMs++lhrPv3sLmrWrMqUr5YDcHqNKlSoUIZhw25gxMjutGh5XlGEXSRO9uN+sAgJOTn/iiNfw/4v0BjPvSsAO4E3/RKRj8wszzRfz0FOZNlgkX8d3HGXKY7y1ur46n748GE6tG1L0yuu4OIGDTjr7LP9EabfWD6fgK/1j23enLS0NBJW+XSLWdA60e0/YdVqml4ZS9trOvDB+x/x9uji9SX2aPLbxc2M/Pb8/PalYHe87VrfvrezbOkvLF+efa/4ggU/cuMNj/J4n5e5554ufonTb/JZae6ItVu1SlmaNj6NKV/nHRsEYPGSRO5+eB5Dhy3hli7F6yQ+3/V/lPKPPnYTK1b8Tnz8HwBcdvl5rFv7N9d3HMDtt73II4/cSLlyZf0UbeE70fqP+3gOYWGnMva9J+jUOYa1a//OSvIGu5Jcdzh5z+l85cu5X6bhr8yiR/cx/PXXVprFeM7xQkNDOPOsSAYMmMzTT02ke/fLOf30yv4LuAid7Md9kSP5Oojn5c65f5nZMgDn3DbvT6HkK+fPsdSoWo3wsLxd/E5UclISUadFZz2PjI4iNcW3+7pOZNlAuuXWW+jW1ZNDWhG/gtNOOy1rXlRUFMlH1GHr1q1UrFiR0NBQMjIyiI6OJiX5aIPDFg9JSUlER2evv6joaFKSc9c9KTGR6CM+n5SU3HXfuWMH/7d4Mc1iY1n722/+DboQJSUlERWdo275rNekxCSictQ/MiqKlJRk2rRtS4uWLYmJjaNMmTJUCKvAS6+9yuMP+3TLWUDdcksPunbzfNmMXxFPdI59ODoqiuQjPgPP9h+Wtf1HRWdvA7t27coqt2DBQoY+O5gqVaqwbdu2IqiJf0WFVyRpS3YPvaS0HVSvEsbBQxkkpWVPT05Lp3rVwm+b/eHGG1vTsWMLAFav/p3IqHDwdqioHhlOamr+6+2OO2+gcpWKPP/8K/nOX7bsF06vEUmlSmGkp+/Mt0wwaHd1Xa5uWRuAteu2ERGe3eOiWvippG3dl6v8GXUrER1VnrEjPLdMlTkllHdGtOCOB+fmKrfqlzSio8pRMewUduw8QLC6vtNVtGvfGIBff/mL6jmumkdUr0zalvR8l+t1WxsqV65A/6ezx8Fq2/Zyxn08G4BNm7aQmJhG7drV+eWXv/xXgRNUmPXfs2cfL/znk6znn38xiMTNwTuIa0muO0CPHjfRpYtnrI74+ASio7N7m0ZFRZKSkhqo0IpE+/YX0+aaCwH47bdkIiKyb/mJqFaBrVt3F7js4cOORQvXcMONlzJ71mq2pO5iR/pe9u8/xP79h1i1chP16kWwadN2f1fD707G477I0fjaA+OgmYXiTXabWQRQ4E2jzrnRzrlLnXOX+iN5AZCwIp5adepwWo0alCpdmqvbt2Ph7LnHXvAElw2kjz78iLZt29K2bVtmzZpFp86eg1rDhg3ZuXMnqfkcyBYvXkzbtp5bkDp37sys2bOKNGZ/iF+xgtp161KjZk1Kly7Nte3bM3f27Fxl5s6Zw/WdOwPQIOvzSaFq1aqEVfRsk2XKlKFJ06b8UcwGs1y5YgV16tahRs0aBdZ/3pzZXO/dPi5u2JBd3u3jlWHDaHZFY5o3bcojDz7ID99/XyySFwAffTQua9DNWbPm0KlTRwAaNGzgWb+pebf/Hxb/H9e0bQNA586dmD1rDgDVctw3fPHF9TELOSmSFwDNG53H5AXLcM6xfM1fhJUrS/WqFbnozNNZn7iFjclbOXDwENO/i6d5o+Jx9f2LL2bRo8eT9OjxJAsW/Mi1bZsBcOGFZ7Fr1x7S0rbnWea665rT+Ir69H/69VxX6WrUyL6N6Jxz6lK6dKmgTl4ATPvmTx583DPw5uIfk2gRUxOAc86qwu49B/PcJvLj0mRuvvMbbrt/NrfdP5v9BzKykhfRUdn3jJ9RtxKlSoUEdfICYNLEb7n9tmHcftswvv02nqvbeO5gPf+COuzetY+0tLxdoq9t15jLLjuPZwZ/kGv9Jydv45JLzwGgSpUwataqzubNaXmWDyaFWf8KFU7NGrS0XfvGrFjxO3v27MuzfLAoyXUHGDduPB06dKVDh67MmTOfjh3bAdCgwUXs3LmL1NQtAY7Qv6ZOXcH9943j/vvGsfj737Nu+zj33Ch27zmQbwIj+rTsWyYuv6IeGzd6klSLF//OBReeTkiIUaZMKc45N4q//gruBJavTsbjvsjR+NoD4w1gElDdzJ4DbgD6+y0qH2RkZPDCwGcY9eH7hISG8NX4L/l97Vpu6OHpofDluE8Jj6jGJ1MmU75CBZxz9Ojdi06t2rB71658ly1O5s+bT1xcHAsXLWTv3r083ufxrHnvvf8eTz7xJCkpKbzwnxcYMXIEj/V5jISEBMZ/Ph6AiIgIpkydQoUKFXCHHb1796ZVy1a5rkwHq4yMDJ4ZOJD3PvzQ8zOi48ezdu1auvXoAcCn48axYN48YuPimLdoUdbPqAJEVK/OS8OHExISQkhICDOmTWP+vHmBrM5xy8jIYMjAgYz11v/L8eNZt3YtXb31/2zcOBbMm09MXBxzvNtHvxzbx8lg/vwFxMXFsGDhXPbu3csTj/fNmvfue2Po++TTnu3/hZcYMeJVHnvsEVYnrGb8+C8BaHtNG3rc3J2MjEPs27effz/4cIBqcvweHf4ZS1b9ybadu2l2xws82LUlh7zdoLtdfTkxl5zDwqVraHXfK5xapjTPP+BJ5JUKDWXgHR24Y8h7ZBx2dG5xCWfVKn5j4vzvf8u48sqGTJr8Ovv2HWDIM9m3/7z2el+eHfo2W7Zso2+/O0hKSuXddz2/QDR//hLeeWcCzVtczrVtm3HoUAb79h/gqX6vBagm/8yPS5Np1DCSsSNasv9ABq++mT2GxTP9ruD1t5azdVvBX8quvDyaFjE1OZThOHAggxde/akowi40PyxeTePGF/Dp5wOzfkoz07CX7ubFFz4lLW0Hj/W5ieTkbYx625OgXbQwng/en8kH78/kqadv5v0P+oLBW6OmkJ5e8FXcYHOi9a9dO5Kn+99MxmHHhvVJvPDCJwW9VdApyXUHWLDgO2JimjJ37hT27t1H376Ds+aNGTOCp58eQkpKKrfe2o077+xJtWrhTJ06noULv+Ppp4dQrVo4kyaNo0KF8hw+7OjVqwfXXNOZXbuKx/a/ZMmfNGpUh3ffu439+w8x/JXsC3JDhnbktVdns23bbvr0aUO5cqdgBn/8kcrIEZ5zvI0bt/LzT+sZ9dYtOOeYOXMVGzYEd/IyU0k/7geLUN1/EzTM1/vnzOxcoAWe26fmOud8Gsa2QZ0zSs4NekfY7orPvZX+UOqod6ee/EJK+J2GB630sQudxP6c/kKgQwiYRj3HBzqEgIqo2z3QIQTUrsTg79Eo4g+Jyd8GOoSAOqPerYEOIaBmDq8V6BAC64LOJ/WJ771fLT0pv9iMuu5fxW69+dQDw8yqAinApzmmlXbOHSx4KRERERERERGRwuHrGBhLgVTgN2Ct9/GfZrbUzC7xV3AiIiIiIiIiIuD7GBgzgUnOuW8AzKw10AYYj+cnVi/3T3giIiIiIiIigRPq62V/8TtfV8WlmckLAOfcLKCZc+4HoIxfIhMRERERERER8fK1B8ZWM3sS+Mz7vAuwzfvTqgX+nKqIiIiIiIiISGHwtQdGd6AGMBn4CqjlnRYK3OSXyEREREREREREvHzqgeGc2wI8WMDsdYUXjoiIiIiIiEjw0BgYwcPXn1GNAJ4ALgDKZk53zjX3U1wiIiIiIiIiIll8zSWNA34F6gLPAOuBH/0Uk4iIiIiIiIhILr4mMMKdc2OBg865hc653sAVfoxLRERERERERCSLr79CctD7P9HMrgU24xnUU0RERERERETE73xNYDxrZpWAx4ARQEXgYX8FJSIiIiIiIhIMSoVYoEMQL18TGNucc+lAOhAHYGZX+i0qEREREREREZEcfB0DY4SP00RERERERERECt1Re2CYWWOgCRBhZo/mmFURCPVnYCIiIiIiIiIimY51C8kpQAVvubAc03cAN/grKBEREREREZFgEOrrfQvid0dNYDjnFgILzex959yGIopJRERERERERCQXXwfx3GNmLwEXAGUzJzrnmvslKhERERERERGRHHztDDMO+BWoCzwDrAd+9FNMIiIiIiIiIiK5+NoDI9w5N9bMHspxW8lCfwYmIiIiIiIiEmihFugIJJOvCYyD3v+JZnYtsBmo4Z+QRERERERERERy8zWB8ayZVQIeA0bg+RnVh/0VlIiIiIiIiIhITr6OgXEjYM65Vc65OKAVcL3/whIRERERERERyeZrD4z6zrntmU+cc1vNrKF/QhIREREREREJDqG+XvYXv/N1VYSYWZXMJ2ZWFd+THyIiIiIiIiIiJ8TXJMQrwPdm9iXggJuA5/wWlYiIiIiIiIhIDj4lMJxzH5rZT0BzwIBOzrnVfo1MRERERERERMTL59tAvAkLJS1EREREREREpMj5fRyL5et/N3+/x9GY2V3OudGBjCGQVP+SW/+SXHdQ/QNZ/x9/6hyIt82lJK//wNf9usC9NcFQ/8BS/VX/klr/klx3UP39TYN4Bo+SsCruCnQAAab6l1wlue6g+qv+JVdJrjuo/qp/yVaS61+S6w6qv5QQJSGBISIiIiIiIiLFnBIYIiIiIiIiIhL0/D4GRhAo6feCqf4lV0muO6j+qn/JVZLrDqq/6l+yleT6l+S6g+rvV6EhAR3WUXIw51ygYxAREREREREJSkMWLD8pvzQPjG1Q7DIzuoVERERERERERILeSZXAMLOHzaxcoOMIBDN7KtAxSPAzs/fN7IZAx1GUzGxXIb1OZTO7rzBe6wRiiDWzJoGMoSQws45mdn6g48hkZv82s1/MbFwhv26smU0rzNc8GRSX/ayw4yzO51CFeQ5kZg3MrG1hvV5xUZzXf6YT2Q6Ky36fqbjFK1KYTqoEBvAwUKwb3xNQpAkMMysJ46eUeMVlPRdRnJWBgCYwgFjArycs5nGyHRuOV0cgaBIYeLa7ts65HpkTisu+WdQK6XOJxc/7WSGJpXDjfJjiew5VmOdADYBincD4h/vBwxTf9Z/pRLaDWIrHfp8pluIVb7EXGnJy/hVHxTRsMLPyZjbdzFaY2SozGwScBsw3s/neMq3NbLGZLTWzL8ysgnf6ejN70cyWeP/ODGRdvDHdambx3vp8dOSV8syryGYWbWaLzGy5t95XmdkLwKneaeO85R71zl9lZg97p9Uxs1/N7B3v9HFm1tLM/mdma83sMm+58mb2rpn9aGbLzOw67/Re3s9xKjCriD+ifJnZZDP72cwSzOwu77Tbzew3M1tgZmPMbKR3eoSZTfDW60czuzKw0R+dmQ3wrq/ZZvapmfUxszPMbKa3zt+a2bnesu+b2Rtm9r2Z/ZG57Xi/jI40s9VmNh2onuP1LzGzhd7X+sbMor3TF5jZ82a2EHjIz3U85jbp6/ZoZhXM7D0zW+ndlzrneJ/nvPvWD2YW6Z3W3sz+z/uac3JMH+x9vwXez/Lf3pd5ATjDu5+9VMifw5H7f57YzKwOcA/wiDeGqwrapr3TZ5un7XvbzDaYWTXvvILahl/M7L/AUmCAmb2aI747zWx4Ydb5KJ9Ffvv0LvO02T97P4/LcqyfDt4yZXOs/2VmFued3su8bYD3+TQzi83xurm2DfNc0eoAvOT9nM8oinoXxMzeAuoBU8ws3cxGm9ks4EPvevvWu56XemPP07PCPG1AL+/jNt597jugUwCqlC8/tAVzvZ/JyhzlfHmPOhyxnwXgs/in7cHR2rQPzGyWec5/OpnZMO9nM9PMSpunnct1DhXgOp/oOVCediTzdewobYmZnQIMAbp4X69LEX8Ofj8mmtkoM/vJ+9k8450W0PWfo/6FvR3kej3vNJ/2p6KvfVYdC3v/P9r5wM3m+R603DsvNFD1FjkexXYQT29D3MY5d6f3eSVgBXCpc26Ld+ecCFzjnNttZk8CZZxzQ8xsPTDGOfecmd0K3OScaxegqmBmF3hjvdIbe1VgODDNOfelt8wu51wFM3sMKOuNPRQo55zbmTnfW/YS4H3gCsCA/wNuBrYB64CGQALwI57P7HY8J+y3Oec6mtnzwGrn3MdmVhlY4l3mRuBZoL5zbqv/P5ljM7OqzrmtZnYqnvpcDfwP+BewE5gHrHDOPWBmnwD/dc59Z2a1gG+cc+cFLPijMLNLgXeAxnh+LWgp8DZwDXCPc26tmV0O/Mc519zM3gfKA12Ac4EpzrkzzawTcC/QBogEVgN3AF8BC4HrnHOp3pO0q51zvc1sAZ717/feBt6D8FG3SW/Mx9wezexFPPv4w97XruKc22ZmDujgnJtqZsOAHc65Z82sCrDdOefM7A7gPOfcY2Y2GGgNxAFhwBogCjgdzz55YSF/Bvnt/+4ose1yzr3sXTbfbdo8X9g3Oef+Y2ZtgK+BCKA2BbcNfwBNnHM/mFl5IB441zl30My+B+52zq0szLoX8HkcuU/HAFvw9ED42swm4dnWr8XTS+ID51wDb9t4oXPuNvMk9mYBZwNd8RwXHvC+/jTgZefcgqNsG++To/0NNO8x61LgAaA90NQ5t9c83b0PO+f2mdlZwKfOuUvNk6Dpk3lc824PPwGfAWuB5nj2u8/xHEMCdvzLVMhtQSk89drhPRf4ATgLz/bvyzFwMDn2s6J0gu3B0dq0lnjatPOBxUDnHPvTB865yZnbmXNuSxDU+R+fA3nL52lHnHNp3n3+WG1JL3K0GUWpiI6JmZ9NKDAX+LdzLj5Q6z+TH86F87yet95H208Cst9n8tP+X9D5QAQwDOjkPc7/F/jBOfdhUde7uHhu0ck5iOfTzYrfIJ7FuQvqSuBlbwM9zTn3rVmuz/8KPAek/3mnn4LnoJ3p0xz/XyWwmgNfZh40vA1sQWV/BN41s9LAZOfc8nzKNAUmOed2A5jZROAqYArwZ+aXEDNLAOZ6G7uVQB3v8q2BDmbWx/u8LFDL+3h2sCQvvP5tZtd7H9cEbgEWZsZoZl/g+RIDnhO483N8thXNLMw5t7MoA/ZRU+Ar59xeAPNcUSmLp7vgFznqUCbHMpOdc4eB1ebNvAPN8HypyQA2m9k87/RzgAuB2d7XCgUSc7zW54VfpQIda5usgW/bY0s8X1YBcM5t8z48AGRejf4ZaOV9XAP43Dw9T04B/swR03Tn3H5gv5ml4En++Et++/9FR4ktp3y3aTzbz/Xe15tpZpmfxdHahg3OuR+8y+z2bivtzOwXoHRRJC+8jtynz8KzDmd6p60E9ntPuHK2W02BEd74fzWzDWTv+wUpaNsIZlMy2wWgNDDSzBoAGRy7vufi2d/WApjZx8BdR1+kSBVWW2DA82bWDDiMJ/kY6eN7BNqJtAdHa9O+zrHPhJJ7f6pT+NU4LoV9DgT5tyNp+NaWBJq/j4k3madXSikgGs+5crwf6+Orwt4O8ryed/rR9pNA88f+X9D5QAvgEuBH7+d8KpBS+FUSKXzFNoHhnPvNPD0N2gL/MU+X2pwMT0PeraCXKOBxIFg+MRzCe4uPeVqWUwCcc4u8J2XXAh+Z2Uv5ZEuPlknbn+Px4RzPD5O9PRieqzNrcr2o54r/bp9qVAS8VxlbAo2dc3vM03NgDVBQr4oQb9m9BcwPJvmtwxA82fUGBSyTc93mXD6/7duABOdc4wJeqyjX87G2yQx82x7z248ADjqX1dUsg+ztfAQw3Dk3xbstDS4gppzL+EN+cR8ttpzy3aat4LO+o7UNR67zd/DcT/wr8N5Rlis0BezTZcm9DrO2EefcYcu+17ugumW1pV5lczwuaNsIZjnX0yNAMnAxnjru804/Wp0Dfbw7msJqC3rgubp4iffL6XqyPwNfjoGBdCLtwTHbNO8+c+T+FOh6F+o50FHaEfCtLQk0vx0Tzawu0Ado5O2N8T6524dA8se5cH7tna/7UyD4Y/8/2vnAB865fv883JIltNj1Uzh5FecxME4D9jjnPgZeJvuWgTBvkR+AK807voWZlTOznFenuuT4n7NnRiDMxZMRDwdP10dgPZ7MKMB1eK60YWa1gRTn3BhgLJ56Axz0ZqIBFgEdvXUujyfz+u1xxPMN8GDmlyAza/hPK+ZnlYBt3hOUc/H0uikHxJhZFe/JSOcc5Wfh6YINgPeqZbD6Dmhvnvv6K+A5SO8B/jSzGyFrfIuLj/E6i4CuZhbqzcrHeaevASLMrLH3tUqbp+tiMPJ1ezxy/VY5xutWAjZ5H/f0IY6c7Uthym//Lyi2I2MoaJv+DrjJO601kPlZ+Nw2OOf+D8+Vy+5k91jzt/z2aV8twvPFFW9bXwvPdr4eaGBmIWZWE7jMh9fy17oubJWARG/Pq1vwXFkH2ICnZ04Z89xe2cI7/VegrmWP61FQgj9Y+doWVMJznDxonrFQah/n+wRy/Z9Ie3C8bdqRAlXvwj4HOpF2BIJ//z+RY2JFPEmOdPP01LwmR/lA17uwt4P8Xg98358CwR/7f0HnA3OBG8yseuZ7eT9XkaBXbBMYwEXAEjNbDjyN576/0cDXZjbfOZcK9AI+NbN4PAmNc3MsX8bM/g/PIIWPFGXgR3LOJQDPAQvNbAWee/7G4PkivgTImVWPBZab2TI8X85f904fDcSb2Tjn3FI897kvwXOP+zvOuWXHEdJQPAeJeDNb5X0ejGYCpbzrdyiedbwJeB5PvefguVc03Vv+38Cl5hkcaTWeAZCCknPuRzzd+lfguR/yJzz16AHc7t1OEvAc0I9mEp573lcCo/CMe4Fz7gBwA/Ci97WWE7yjWfu6PT4LVDHPgF4ryE7WFGQwnttxvsUzxsJROefS8NyStsoKcRDPAvb/gmKbClxv2YOMFbRNPwO0NrOleE5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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "{'corr': step customer age gender merchant category \\\n", - " step 1.000000 0.091561 0.081676 0.010605 0.218892 0.057168 \n", - " customer 0.091561 1.000000 0.002931 0.032947 0.006908 0.035071 \n", - " age 0.081676 0.002931 1.000000 0.115579 -0.020316 0.032859 \n", - " gender 0.001423 0.032947 0.115579 1.000000 0.026731 0.003207 \n", - " merchant 0.218892 0.006908 -0.020316 0.026731 1.000000 0.449156 \n", - " category 0.016173 0.035071 0.032859 0.006763 0.449156 1.000000 \n", - " amount 0.099530 -0.000815 -0.011677 0.043971 -0.082459 0.805309 \n", - " fraud 0.067233 0.026313 -0.018114 0.105551 -0.150286 0.870595 \n", - " meramt 0.109209 0.001455 -0.009584 0.053934 -0.101626 0.992498 \n", - " catamt 0.107599 0.000476 -0.009397 0.050372 -0.090733 1.000000 \n", - " custamt 0.071864 -0.001731 -0.024820 0.093464 -0.135225 0.581235 \n", - " mercat 0.106171 -0.006412 -0.003669 0.026906 0.449156 1.000000 \n", - " custcat 0.099459 0.035071 -0.011782 0.060799 -0.082126 1.000000 \n", - " catage 0.098104 -0.012575 0.032859 0.042876 -0.050149 1.000000 \n", - " \n", - " amount fraud meramt catamt custamt mercat \\\n", - " step 0.099530 0.067233 0.109209 0.107599 0.071864 0.106171 \n", - " customer -0.000815 0.026313 0.001455 0.000476 -0.001731 -0.006412 \n", - " age -0.011677 -0.018114 -0.009584 -0.009397 -0.024820 -0.003669 \n", - " gender 0.043971 0.105551 0.053934 0.050372 0.093464 0.026906 \n", - " merchant -0.082459 -0.150286 -0.101626 -0.090733 -0.135225 0.449156 \n", - " category 0.805309 0.870595 0.992498 1.000000 0.581235 1.000000 \n", - " amount 1.000000 0.450215 0.811395 0.805309 0.470454 -0.162678 \n", - " fraud 0.450215 1.000000 0.529481 0.498312 0.600583 -0.231696 \n", - " meramt 0.811395 0.529481 1.000000 0.992498 0.472516 -0.200491 \n", - " catamt 0.805309 0.498312 0.992498 1.000000 0.453809 -0.202007 \n", - " custamt 0.470454 0.600583 0.472516 0.453809 1.000000 -0.157477 \n", - " mercat -0.162678 -0.231696 -0.200491 -0.202007 -0.157477 1.000000 \n", - " custcat 0.010933 0.579601 0.013475 0.013577 0.291554 -0.182845 \n", - " catage -0.230294 -0.428122 -0.283825 -0.285970 -0.286136 -0.111651 \n", - " \n", - " custcat catage \n", - " step 0.099459 0.098104 \n", - " customer 0.035071 -0.012575 \n", - " age -0.011782 0.032859 \n", - " gender 0.060799 0.042876 \n", - " merchant -0.082126 -0.050149 \n", - " category 1.000000 1.000000 \n", - " amount 0.010933 -0.230294 \n", - " fraud 0.579601 -0.428122 \n", - " meramt 0.013475 -0.283825 \n", - " catamt 0.013577 -0.285970 \n", - " custamt 0.291554 -0.286136 \n", - " mercat -0.182845 -0.111651 \n", - " custcat 1.000000 -0.358553 \n", - " catage -0.358553 1.000000 ,\n", - " 'ax': }" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from dython.nominal import associations\n", - "associations(data, theil_u=True, figsize=(20, 20))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we can see our features have a nice correlation with the target" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "l = ['age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", - "for i in l:\n", - " plt.figure(figsize=(8, 8))\n", - " sns.distplot(data[i])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that except age all the features are skewed, of which catage and mercat are negatively skewed and others are positively skewed" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It can be seen that the data has outliers, however the number of outliers is significant. Thus we wont remove them" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n", - "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", - " warnings.warn(msg, FutureWarning)\n" - ] - }, - { - "data": { - "image/png": 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\n", 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\n", 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ox9fzJNTUSOvWSVu3pq8uAAAAINmiaum5QdIVkjoj2n7OW7RI2rZt16En0e1t1ar01AQAAACkQtpDj5mdLWlNCGHebh43y8zmmtncBsZNTrrEIAa7a+mRuK4HAAAA2S2Klp6jJc00s2WSfifpRDO7o/eDQgizQwjTQwjTq6ur011j7C1ZIpWUSJMm7fwxQ4f6Y7iuBwAAANks7aEnhPDVEMLYEMJESR+W9EQI4SPpriPX1dZ697W8XbwDzPwxtPQAAAAgmzFPT45KhJ7dqanx0BNC6msCAAAAUiHS0BNC+GsI4ewoa8hVfQ091dU+ehsjuAEAACBb0dKTgzo7vfWmL6GnstLXGzaktCQAAAAgZQg9OaihwYer7kvoqary9caNKS0JAAAASBlCTw5KjMbWn9BDSw8AAACyFaEnB/Un9AwZ4mtCDwAAALIVoScH9Sf0FBRIFRV0bwMAAED2IvTkoNpaqbDQR2bri8pKQg8AAACyF6EnB9XW+vw7u5qYtKeqKkIPAAAAshehJwf1dY6ehMpKrukBAABA9iL05KA9CT3NzVJbW8pKAgAAAFKG0JNjQuh/6GGuHgAAAGQzQk+OWbdOamnZs9BDFzcAAABkI0JPjunPcNUJlZW+JvQAAAAgGxF6csxAQg/d2wAAAJCNCD05Zk9CT0mJVFpKSw8AAACyE6Enx9TWSvn50qhR/XseE5QCAAAgWxF6ckxtrTR6tAef/iD0AAAAIFsRenJMba00blz/n1dVRfc2AAAAZCdCT47p7xw9CZWVUmOj1NGR9JIAAACAlCL05JA9mZg0oarKn79pU/LrAgAAAFKJ0JNDNm2Smpv3vKVHoosbAAAAsg+hJ4fsyXDVCVVVvmYwAwAAAGQbQk8OSUbooaUHAAAA2YbQk0MGEnpKS6XCQlp6AAAAkH0IPTmktlYy83l6+svMW3sIPQAAAMg2hJ4cUlsrjRrlLTZ7orKS7m0AAADIPoSeHLKnw1UnEHoAAACQjQg9OWTlSqmmZs+fX1Xlw153diavJgAAACDVCD05pL7eu7ftqcpKqb1d2rw5aSUBAAAAKUfoyRHbtklr1w4s9DBXDwAAALIRoSdHrFnj64G29Ehc1wMAAIDsQujJEatX+3rkyD1/jUTo2bRpwOUAAAAAaUPoyRH19b4eSEtPebmvGxsHXg8AAACQLoSeHJEIPQNp6SkokMrKCD0AAADILoSeHJGM7m2SNGQI3dsAAACQXQg9OaK+XqqokEpLB/Y6hB4AAABkG0JPjli9euCtPJIHJ7q3AQAAIJsQenLEQCcmTUiEnhAG/loAAABAOhB6ckSyQs+QIT7R6datA38tAAAAIB0IPTkiWd3bhgzxNV3cAAAAkC0IPTmgpUXauDF53dskBjMAAABA9iD05IBkDVctdbf0EHoAAACQLQg9OSARepLZ0kP3NgAAAGQLQk8OqK/3dTJCT2mpVFBASw8AAACyB6EnByRCTzK6t5kxVw8AAACyC6EnByS6t40YkZzXGzKElh4AAABkD0JPDqivl6qqpOLi5LweLT0AAADIJoSeHLB6dXKu50kYMoTQAwAAgOxB6MkB9fXJDT0VFVJTk9TRkbzXBAAAAFKF0JMD6uuTM4hBQmKuHlp7AAAAkA0IPTkg2d3bmKsHAAAA2YTQE3ObN/tCSw8AAAByFaEn5hLDVSd7IAOJYasBAACQHQg9MZeK0FNe7mtCDwAAALIBoSfm6ut9nczubYWFUmkp3dsAAACQHQg9MZeKlh7Ju7jR0gMAAIBsQOiJufp6yUyqrk7u61ZU0NIDAACA7EDoibn6emn4cKmgILmvS0sPAAAAsgWhJ+aSPUdPQqKlJ4TkvzYAAACQTISemKuvT+4gBglDhkhtbVJTU/JfGwAAAEgmQk/M1denrqUn8foAAABAJiP0xFgIqevelpiglNADAACATEfoibHGRqmlJXXd2yRCDwAAADIfoSfGUjExaUKie1tdXfJfGwAAAEgmQk+MJQLJ6NHJf+3SUik/n5YeAAAAZD5CT4ylMvTk5XlrDy09AAAAyHSEnhhLZeiR/LqeVatS89oAAABAshB6Yqy+XioulqqqUvP6lZWEHgAAAGQ+Qk+M1dX5cNVmqXn9ykpp5crUvDYAAACQLISeGKurS13XNslDz8aN0pYtqdsGAAAAMFCEnhhLR+iR6OIGAACAzEboibF0hR66uAEAACCTEXpiqqVF2rDBr+lJFUIPAAAAsgGhJ6ZWr/Y13dsAAACQ6wg9MZXqOXokqaREKiujpQcAAACZjdATU+kIPWZSTQ2hBwAAAJmN0BNT6Qg9koceurcBAAAgkxF6YqquTsrLk0aMSO12xoyhpQcAAACZLe2hx8zGmdlfzGyxmb1kZl9Mdw25oK7OA09+fmq3k2jpCSG12wEAAAD2VBQtPe2SvhxC2FfSkZI+b2b7RVBHrNXVpXa46oSaGqmtTVq3LvXbAgAAAPZE2kNPCKEuhDC/6+cmSYsl1aS7jrirr0/99TySd2+T6OIGAACAzBXpNT1mNlHSoZKejbKOOKqrS0/oqemKqwxmAAAAgEwVWegxs8GSfi/pshBC4w5+P8vM5prZ3IaGhvQXmMU6OnxyUlp6AAAAgIhCj5kVygPPb0II9+7oMSGE2SGE6SGE6dXV1ektMMs1NEidnekJPYltEHoAAACQqaIYvc0k/VzS4hDCdenefi5I1xw9klRU5KPE0b0NAAAAmSqKlp6jJX1U0olmtqBrOTOCOmIrnaFHYq4eAAAAZLaCdG8whPC0JEv3dnNJukNPYq4eAAAAIBNFOnobUqO+3tfpmKdH8tBDSw+AWKqvlxYskJqbo64EADAAaW/pQerV1UmVlVJJSXq2N2aMtGaNT1JaVJSebQJAyixdKv32t9Itt0i1tX5fXp60117SQQdJ73qXVFERbY0AgH4h9MRQuuboSUjM1VNfL40fn77tAkDS3Xef9KEP+VmcKVOk886Txo2TFi+WFi6U7rlHevxx6Qtf6B6zHwCQ8Qg9MRRV6Fm5ktADIIvdeaf00Y9Khx8u3X239Mgj3b+bNk065xxp+XLpppukH/1I+vznvfUHAJDxuKYnhtIdepigFEDW+/nPpQsvlI45Rvrzn3d+BmfCBOmKK6TycumGG/x6HwBAxiP0xEwI0bX0MIIbgKx0223Spz8tnXaa9NBDHmh2ZfhwDz41NdLPfia98kp66gQA7DFCT8xs3Ci1tqY39Awb5gMY0NIDIOssXSpdcol00knSnDlSaWnfnjd4sHT55T478223SevXp7RMAMDAEHpiJt3DVUuSGROUAshCnZ3SJz8pFRRIv/ylVFzcv+eXlHgLUVOTdPHF3tQOAMhIhJ6YSffEpAlMUAog6/z0p9KTT0rXXy+NHbtnrzF+vDRzpo/qdvvtya0PAJA0hJ6YiSr00NIDIKu88Yb0H/8hnXGG9IlPDOy1Tj1VOv546dJLpddfT0p5AIDkIvTETJQtPStX0rsDQBbo7JQ+9SmpsFCaPdv76A5EXp70q195N7lPfpIdIQBkIEJPzKxY4QMPpXuy8IkTpeZmae3a9G4XAPrt7ru9W9t///eed2vrbdw46Qc/kP72N+nee5PzmgCApCH0xMzy5T6NxEBPXPbXlCm+fuON9G4XAPqlvV365jelAw4YeLe23j75SWn//b3bXFtbcl8bADAghJ6YSYSedCP0AMgKv/qVtGSJdNVV3i0tmQoKpGuv9R3hTTcl97UBAANC6ImZqELPxIm+Xro0/dsGgD5pbZW+/W3piCN8xLVUOP10H9jgu99l7h4AyCCEnhhpbPTJSaMIPYMG+WAGtPQAyFizZ/uFj1ddldo+wNdeK23a5MEHAJARCD0xsny5r6MIPZJ3cSP0AMhIzc3S1VdLxx0nnXxyard14IF+fc9NNzGENQBkCEJPjEQdeiZPpnsbgAz1k59Iq1d78EnHSC/f+Y5f43PVVanfFgBgtwg9MbJiha+jbOlZtUraujWa7QPADrW0SNdd59faHH10erY5erR08cXSHXfQBA4AGYDQEyPLl0tFRdLIkdFsPzGCG609ADLKnXdKa9ZI//7v6d3uFVd4a8/3v5/e7QIA3oHQEyPLl/v8eMkehbWvJk/2NaEHQMYIQbr+ep+XJ9XX8vQ2erQ0a5Z0++3SsmXp3TYAYDuEnhiJarjqBObqAZBxnnhCWrhQuvzy9M/aLHlrT16edM016d82AOBthJ4YiTr0DBsmlZcTegBkkOuvl0aMkC64IJrtjx0rfepT0i9+Ib31VjQ1AAAIPXHR2irV1UUbesy8tYfubQAywquvSn/8o/TZz0olJdHVceWVvqa1BwAiQ+iJicQJxChDj8RcPQAyyI03+ugun/1stHWMHy9ddJF0661+dgoAkHYFUReA5Ih6jp6EyZOlBx6QOjqk/PxoawGQw9av9wEELrwwuiEte7riCunnP5duuEH6wQ+k2bP79/xZs1JSFgDkClp6YiJTQs+UKVJbm8/XAwCRmT1b2rLFBzDIBHvtJZ13nnTzzdLGjVFXAwA5h9ATE8uX+zU1Y8dGWwcjuAGI3LZt0k9+4kNUH3hg1NV0u/JKqalJ+ulPo64EAHIOoScmVqyQxozx7utRSszVQ+gBEJm775ZWrsycVp6EQw6RTj/du7i1tUVdDQDkFEJPTEQ9XHXC+PE+ATkjuAGIRGIy0mnTPGBkmq9+VWpokP7+96grAYCcQuiJieXLPXBEraDAwxctPQAi8fTT0ty50mWX+aSgmebYY6WjjpIee8xHfAEApEUGfiOgvzo7fcjqTGjpkbyLGy09ACJx/fXS0KHSxz4WdSU7ZuatPevWSf/6V9TVAEDOIPTEQF2dX7ebKaGHuXoARGLpUmnOHOnii6XS0qir2bmzzvKLMP/0Jz9rBQBIOebpiYFMGa46YcoUnyJj40apsjLqaoAMwtwsqfXjH3sf20suibqSXcvLk047TbrtNmnhQungg6OuCABij9ATA5kWehIjuC1dKh12WLS1AIixniFy61bpZz/znc6DD+748ZkUImfMkO6/X3rkEemgg7zbGwAgZejeFgOZFnqmTfP1Sy9FWweAHPL001Jrq8/Nkw3y86VTTvGzQ6+9FnU1ABB7hJ4YWL7cr9sdPDjqSty0ad6dft68qCsBkBM6OqS//EWaOjUzhrHsq6OPlsrLvbUHAJBShJ4YyJQ5ehIKCqRDD/VRYwEg5RYs8NHQsqWVJ6GoSDrxRG8WX7Ei6moAINYIPTHwxhvSpElRV7G96dOl+fOl9vaoKwEQe48/Lg0f7tfGZJvjj5dKSnwkNwBAyhB6stzWrdLrr0sHHBB1JdubMcNrW7w46koAxNqbb/qZn5NOyszJSHentFQ67jjvD1xfH3U1ABBbWfgNgZ4WL/ZpHg48MOpKtjd9uq+Zew9ASj3+uDRokPTud0ddyZ47+WSpsFB66KGoKwGA2CL0ZLlFi3ydaS09U6dKFRVc1wMghdav9xaSY47xLmLZqqLCu7k99xytPQCQIoSeLLdokVRcLO21V9SVbC8vTzr8cEIPgBR64glfn3hitHUkwymn0NoDACnE5KRZbuFCad99fcS0TDN9unTjjVJbmw9SBABJs3699NRTfgHh0KFRVzNwidaexx6TzjxTGjUq6ooA7EzPiZH7IpMmRs5htPRkuUWLMq9rW8KMGR54Fi6MuhIAsfPTn/pkpKedFnUlyUNrDwCkDKEni23cKNXWZm7oSQxmQBc3AEm1ZYv04x/7CC41NVFXkzxc2wMAKUPoyWKJQQwybeS2hIkTpWHDGMENQJLddpvU0CCdfnrUlSRforXngQeirgQAYoXQk8UydeS2BDNv7aGlB0DStLdL117rQ1Rn2gguyVBR4UNYz50rLVsWdTUAEBuEniy2cKF/P44bF3UlOzdjhoezrVujrgRALNx1l4eBK6+MupLUOfVUqbxc+v3vpRCirgYAYoHQk8USgxiYRV3Jzk2fLnV0SAsWRF0JgKzX2Sldc420337SWWdFXU3qDBoknX22tGQJI8EAQJIQerJUCJk9clsCgxkASJp77vEQ8NWv+mRgcXbssdKIEdK99/qZIwDAgMT8WyO+6up8mopMDz01Nb489VTUlQDIau3t0je+Ie2/v3T++VFXk3r5+dK55/rO/h//iLoaAMh6hJ4slekjt/V0zjnSgw9KTU1RVwIga/3qV97d6+qrPRDkgkMPlaZMke6/X9q8OepqACCrEXqyVCL07L9/tHX0xQUXSC0t0pw5UVcCICu1tkrf+pZ0xBHSzJlRV5M+ZtIHPyg1NvrfDwDYY4SeLLVwoTRypFRdHXUlu3fUUT5nz513Rl0JgKx0yy3SW29J3/teZo/ckgqTJ0vHHCPdcAMjwgDAABB6stSiRdnRtU3yY5QPf1h69FGfTxAA+mzzZumqq6QTT5ROOinqaqLx/vf7TM8XX8ygBgCwhwg9WaizU3rppcwfxKCnCy7w7+q77466EgBZ5brr/GzJ1VdHXUl0ysr83+G556Sf/SzqagAgKxF6stDixT7Z50EHRV1J3x14oIc0urgB6LOlS6Xvf1867zzpyCOjriZaF1wgnXyy9LWvSatWRV0NAGQdQk8W+tOffJ1tPT3OP196+mlp+fKoKwGQ8UKQLrlEKiiQrr8+6mqiZybdfLMP6nDJJf7vAwDos4KoC0D/PfKIT0g+fnzUlfTP+edLX/+6dPnl0umn9+05s2altiYAGeree6WHH/ZuXTU1UVeTGfbaS/rud6UrrpBuvVX6zGeirggAsgYtPVmmuVl68sm+h4ZMMmmSL88+69clAcAONTVJX/yidPDB0qWXRl1NZvnyl6VTTvF/n5dfjroaAMgahJ4s89e/Sm1t0hlnRF3JnjnhBO+O/re/RV0JgIz17W9LK1d6d64COiRsJy/PJ2odPNiHxdy6NeqKACAr8G2SZR55RCot9WkbUmGfp2b37wn97H92xBHSM894z5WDDpKqqvq3OQAx989/+pw0n/mMT/KFdxo1Srr9dunMM6WvfEX6yU+irggAMh4tPVnm4Ye9taSkJOpK9oyZdOGFPnz1734XdTUAMsr69dK//Zs0bpz0wx9GXU1mO+MM6Utfkm66iWExAaAPCD1Z5PXXpTfeyN6ubQnV1dJ73+uTi8+fH3U1ADJCCNInPiHV1Ul33SVVVkZdUeb7/velY4+VLrqIPsMAsBuEnizyyCO+zsZBDHo7+WQ/mXvnnT7hOoAcd8MN0v33ewvPjBlRV5MdioqkOXN8hJj3vU969dWoKwKAjEXoySKPPOIjlk6ZEnUlA5efL33sY9KWLdJ//7e0aVPUFQGIzHPPSf/xH37g/sUvRl1Ndhk6VHroIR/w4YwzpNWro64IADISAxlkiZYW6YknpE99KupKkmf8eOkLX/Au6T/6kXTZZdLw4VFXBaTBli1Sba20dq0v69b5h7yjwxdJKi/3Pq1jxkhTp3rrx4gR0dadCkuWSDNn+t95221+4R/6Z/Jk6cEHpeOPl846y2ewHjYs6qoAIKMQerLE3/7mI5Nm+/U8vU2b5mHnf/5HuvZaD0FjxkRdFZBkdXXSn/6kuh/+WhVr31DppnqZgiQpyNRaWqn2olKFvHwFy5cUVLR8tUqef97HqE8YP15617uk007zg9tRo6L5e5Jl+XLv69rZ6U3ZGTac41NP9f2x74l6IuUjjpDuvlv6wAek446THn2UnSkA9EDoyRI33SRVVPh3WdxMnuyDEN14o3TNNT71xFFHccIXWSwEH6XjvvukP/7x7RE7hheVqmn4ZDVMmKGmYRO0tXyEWkuHKuTveFf8nl9/xkc0e+kl6V//8uXvf/eDW8kPdM89V/roR6WamnT9dclRV+eBp6lJ+stfpH32ibqi7HfWWT7E58yZPq/Bn//sO1gAAKEnGzz3nB87fec7UllZ1NWkxrhx0te/Lv3iFz79xOLF0gUXRF0V0A8hSC+84COP3XWXD7WYl+cJ/nvfk848U8/88BnJ+nEppZl3U3rPe3xJbGfhQumBB/zC/69+1T88p58uffKTPjRiUVFq/sZkqauTTjnF13/+s3TIIenZ7ux+zkOWjU44wftCn366B58HH5QOOyzqqoB427bNZ16vrfXuyps2SY2NflInBO+6m5fnB3E1NdLYsb7sv7908MHenRkpR+jJAv/5n36ty2WXRV1JalVVSZdf7icqH3hAWrpUOvTQ7mM9IOOE4K0w//d/HnSWLPFROk480cPIOedsf22FPTvwbZr5zL4HHeRh57XXpF/+0pcPftB3Fh/5iAegAw8c+PaS7R//8Do3bfIP+pFHRl1R/MyY4X2iTzvNQ/d110mf+xzN50CyNDb6aIlLlvi1l/X13k1X8s9Zebk0ZIg0eLCHnYoK//2mTdLLL/sJn56P33tv/9yecIK3gI8fH93fFmOEngz35JPSY4/5CGe5cCIgL897aEyb5idGjjvOB3P63vek0tKoqwPU3XXt3nt9eeUVf+Mef7z05S97d7Pq6vTVM3WqdPXV3hT86KP+wbnpJh8Cevp0Dz/nnx/9vDchSDff7GdvJkzwWg84INqa4my//fx9etFF0iWXeOvPz38e/fsAyEYhSM8/70PE33+/t+pLPlP8Xnt5a824cd56U13t3wk9zep10V97u7cMLVzon9N583yfeMcd/vu99vKLuGfO9AOhwsKU/4m5gNCTwULwE7ljxkif/WzU1aTXXntJ3/ymn8S+8Ua/LOKWW/wEOjJYf7sP9f4iiNrO6u/s9O5qzz/vy/r13UHn0kv94vGRI9Na6jvk5/uX5Bln+Ihwv/mN9xf93Of8orkPfMAD0PHHv/MLOdVWrpS+8hWfmOvss6Vf/zqjD76bWgo1b/lw3fvKUDVvK9LW9kK1tBeqvKhVowY3aXRZkyYM2aBhg7ZGXequVVd7a9r110tXXumtg9deK513Hq0+wO5s2+ajmcyZ49cYvPWW7zuPOcZPbk2b5i0y+fn9f+2CAn/u+PF+plfyg75Fi6THH/ez3f/7vz7K05Ah0plnegA64wy/jT1C6MlgDz/s1yzffLM0aFDU1aRfcbH04x9L73+/9OlPSyedJF14obd6RX18iRywebO34rz8svTii943u6BA2ndfP3A/+GAPEwMQgrR2a6neahyi2qZKrWyqUFtn9xfoY9/w6/sTS5+v6Rs+3JtIv/AFP4v4i19Iv/2tB6GJE6VPfEL6+Me9xSWVmpv9IPuHP/Qzm9/5jp/JSXfo2o3OTumZpSN197zJemxxjRbXVymE7lBQmNeh4oJ2bdlWqM7QXfv4ig06bOQqHT5qpQ5tytDW+Lw8b4E89ljpM5+R/u3f/EDqhhukww+PujogszQ2+kiS99/vZ1s3bvQDsFNP9f3X2Wf7/jUV1weaeZfkAw/0FvHmZg8/99/vJy/uvNNbfI4/3gPQzJl0g+snQk+GeuMNP0E7aZKfnB2Q9nZp2TI/21pX531P16zpvsiusdGHxQ1BByxYIUnqKChSZ0GxOgqK1V40SNtKytVWUqFtJRVqKRum1rKhCnl7cHZjDxx/vLcAX3ONLw8+6K1An/1sboZBpEh9vV66Y74q1i5V5eolGrx+hUxB7YUl2jB6f6096FCtrzlQHYUlUoek+VJ/LzcLQVq5uUILVo/WgtVj9MKa0VqzZfDbvy/Ka1dxQfvbt+d8r7vbd36+j1Z96qm+HHFEH04wmvmB7eGHe/iYM8cD0H/9ly8zZvh1R+ec42EuWWf/33rLu2n85CfeheO886Qf/MB3aBmis1P655sjddfcybpn/iSt3DhYxQXtOmHaKn3o8KU6YlKDWlau1ZDiFhXk+fDi7Z2mNc2DVddcrtfWD9f81WP0pzf31pzX9td3h/uJmfe9z49FRo+O+A/s7YgjugPw17/u//cf/KCH43e/m5Yf5K7ly7sHhvnrX72FZ9iw7n3jKadE07++rKy7ho4O6Z//9Ban++7zHgaXXuoXPs+c6TueQw7hc7wbFkKIuobdmj59epg7d27UZaTNiy/69afbtvkJh+nT+/Ckzk4fNWTJEu8Tlli/9pqPCNDevv3j8/O9ibS83JfiYslMjW+ulYWgvI5tym9vVV57qwratigvdG739GB5aikbqkFHHuJDok6Z4uupU33ZyQ5ioL2fXn3VT14/+qgfVHz9694KVFzcv9dFajz1kf79B7/njgi6t23bJr35prfgvPCCtGCBL8uWSZI68wrUNGyiNozeVxtG7aumYROlnQT83dXf0uKBfe5cv678sTnNWrvVm2uqSrbo4BF1OrC6XhOHbNS4io2qLm1WXo/vrHf9fJbeeMNHM5w/30/6zZ3r4am62r/rzj3Xr3vt12dg2TI/azhnjg8PKfkZw2OP9ZFDjjnGP8d97Ufe0eFF/vOf0u9+59ePhOB90a++Wjr66H4U1w/93KEkgs7d8ybr7nkedIoKOnT6/m/pQ4cv1XsPWq6KQdvefnxf5ulp7zQtahil5Qe9V3Pm+O5W8oB6zjl+Ynj//XdwLBJlV9BNmzyE3nyzn8k+7DC/7uf976frDOKvpcX3VY8/7mEncX3OPvv46JczZ/oAILs6qxR1V+5XX+0OQM884/vbceO89rPO8n14RjY9p56ZzQsh7PDIOZLQY2anS7pRUr6kW0MI1+zq8bkUev7xD3+/lpX5Ac6++/b4ZQjeSpMIMz0Dzhtv+Ac5YdCg7gCSWCZM8MkMR4/2odJ2cEZghwetoVMFbVtU2NKkoq2NKmleq0FNDSrZvFYjRpp/y69du/1zxo3z0Uj23tv7vXat//fRCf1qIdrZfuLJJ6VvfMMPJEeN8mlKLrrIr91FdN5+/3R0aFtbh9rbTXl5QfnqVL4FFeZ39Hi06d23ftK7jOXnd6/7e6YqBG+pbGnxGXw3bPBrbtatk1av9pMBK1f6+vXX/YC/o6sOM4W991brPgdrzcR36cmnTK8X76cN28rV2pGv9s48tXd6d6bCvE4V5HWqKL9DBXkdKszr1AGfP06dnZ6j2tr8WDKxqUSuSpxvGD1a2rfodR0yok6HjFyl8RWbdvun7ihUrVvn+4Y5c6SHHvLG2sGDvcv3uef6uqKiH/9+K1f6Gc4nnvCj/DVr/P6CAj+Zsffe/nkuL/cNlZV517/16315801PZM3N/rzJk6WPfcw/lKmeI6YPBx5b2/L1zNKReuDFCbpn/iTVbugOOucdtlTvPXi5hvQIOj31a3LSO2a9PZhf4hKAxNfW8OHdo44fdpj3Xqm8KwOuf2tu9i6PP/6xF15Y6KNHnXuuD3k9YQJnjpH9Vq/2Oc6ee84PGp55Rmpt7b4+Z+ZMDzt7793314w69PS0Zo13gbnvPv9y2LrVv0sPO8xPPB15pJ89Hz8+Jz7PGRV6zCxf0hJJp0iqlfQvSeeHEF7e2XNyJfQsXtius45o0IHV9frfr7+pEZvf9AOKnkvPYFNY6AclU6f6h7XnesyYPeo3v8dn6hsbPXi9/nr3MI6vvurLpk1vP76joEibqvdS44ipaho2Qc1V49RcNVabq8Zp89Bx2jJktEJ+99nlXe0nQvApPm66ybvetrd7L55TTvGDi3e/m5OW/RKCH8xu3OjBYePGdyyd6zZoa91Gta7eqPZ1fp9taZa1tii/bauK2reqWC0qUMeutrTrMvLypPx8We8wVFDgi+RfWImlrW3Xr2emMGKkWobVaOPQKVpZOlWvaaqe37qPnlp/gF5aVvb28XoyVFb6AD7jxvllP4neZRMnSn/7aHJbwlpbPav84Q/+fbdmjf8TTZ/u33XHHefbHjGijxsMwU+kPPPM9p/jVav8vdHz37qiQho61NPc4Yd796kZM/wkR7q+WHsdeIQgLVtXrhdqh2rBW8P11Guj9I83Rqq1vUBFBR06bb9afejwN3YZdHrqb+jprbbWj0GefNKXrsZESdK4qs2aUt2osVXNGlu1WWMrmzW2qlnjhm7WmCFbNGxwiwrze3w/p/KgKQQ/8z1njr+ZXnvN7x81ys94H3WUN1dNm+Zv5D25cBtIpc5O776/fLnvs15+2ZeFC727reTHRAcf7MH+hBM88OzpgCqZFHp62rLFz57/9a++03n2WT8rJ/nZl0MP9bPp++7rLVtTpvg+PPHdGgOZFnqOkvStEMJpXbe/KkkhhO/v7DkZFXoSp3Xb233dc+l9X2urn4bdvPmd602b/Ahl9Wpfr1njp3B7GzLE+8H3XBItN+PHJ/2NmvTuSSFIDQ1vHzwtuGuJKle/qoo1r2nw+hUqat283cM7LU9bh4zS1sHVaiut0pgDhvqB1dCh3jo1dKifbR40aLtl3dZS3ffoIN33cJGefzFfrR356lCBxozL17iJ+Ro7sUCjx+arvDJfFZV5Kq8w5eX5PtDMlx393HX8/Y7GiN2tE0vi+Tv72azr3yixdHZ2r3f2c3t798F+74P/nrdbW/1Mbte1W2FTo0Jjkzo3NUqbGhUS13M1NcmaGpXftFGWuIBkJ5o0WBtVqQ2q0kZVapOGqCWvTHllg1RQPkjbNrcorzDfg2tBgUJenoKkEEwdwf9fWjoK1dJeoK3bCrStsFTNjR3K62yX/491r8tLO1RZ1q7ysg5VDGrX4NIOlRa1qyA/yIqLZSXFai8oVnt+idrzi7W1s1ib20u0XkNV1zpUSzcO1ctrR2h+3WhtbN6+m1ZpqTdCTJ7sH6nJk/1YrvamOaosblF5catK8tuVn+ctVJLUEUzbOvPV3pGnbZ352taZp0N/dKHy8vz8Q1FRd0PIzqSy+19Hh2eVhx7y77p//av7u6662keHnjrV58UbM8aPZxP19l6Kiro/C9vll7Y2/1ItK+v3EKo7epv3fsv3vK+93U9Y7mjZtMl3l+v+NFermwZpxfrBWr6uXMvWDdbmVp+Y1SzooJp1OmmfVTpxn5U6dq96LfjX7oPOnurL/9WqVd59+cUXpT/f/JrqmwerYctgNWwpU0d450mq0oI2VRS3qryoVRMOH/72rrDnLrH3/11pqa9LSna9j9ppLg3BDxaffNLfUM884ye0EoqK/MMyZowviZ4DFRXeGth7XVLSfcKi58mLnktih4vMtLPjxB3d39f7Evf3PGZqa9v+9ubN3cdNPY+hmpr8uCJxDFVX58Gm50mZ4mIP6fvt5ydjZszwlo9kzfCeqaGnt5YW3+HMm+dNzwsWeCjseaYvP98/y2PH+rVMvXc0Q4d6OCwt9c9zcbGvE0txsX+ZZMiw2pkWej4o6fQQwqe7bn9U0rtCCJfs7DkZE3r++EfvoD1QiYmqRozwZeTId/6cCDhVVQPfXj+k+pqM3vuJwq2bNHhDrcrWv6XBG95S2YZalW2sVcnmdSpuXq/Rxeu7u9G0tvZrW7vSrnwFvfNLti/37enzJClPnTIF5amzx8/p+Qw2abCaVK5GVexw3TPMJJb2skoNGlOlsppKVU0cotHjCjR2rB84J6Yk6NlTck/eP52d3jty1aruZeXK7W+vWuXfbX3ZXeXn+347MRrouHHb/zxxon/EdnSMler3fzqvedqyxU/ev/iij4K6cKE3Fjc07Nnr7ejkQO9lV2EmVSqKWjSibLNGlW3WyLImTarcoL0q12lS5XqVFOx5i2N/DeS90BmkDS2D1LClTA1byrR2S5ka24rV1FaixtZiNbYWSxMmvL0rXL++u4fmnkqceOlL3hga1mlaeEV7h1c1NbyqSZ1LNUp1GhXqNDqs0iC17PoF+mBH++R0394R28H+eUf39eexA31+Mh6bru+dVFmnYWqwEVqTN1JrbKRW2EStyJugt2yCXs/bW8tskjothS2S23bdw+AdCotSU0cfPf20N3JJ8h1yba2PTrpsmbRihS8rV2q7nUxTU983cMstGTMFRaaFnvMkndYr9BwRQri01+NmSUr8C06T9GpaC+2f4ZLW7vZRyDW8L9Ab7wn0xnsCvfGeQG+8J/puQghhhzOER9GJr1bSuB63x0pa1ftBIYTZklIwEHrymdncnaVK5C7eF+iN9wR64z2B3nhPoDfeE8kRxQxx/5I01cwmmVmRpA9Luj+COgAAAADkgLS39IQQ2s3sEkl/kg9Z/YsQwkvprgMAAABAbohkjLoQwkOSHopi2ymSFd3wkHa8L9Ab7wn0xnsCvfGeQG+8J5IgkslJAQAAACBdorimBwAAAADShtAzAGZWYmbPmdkLZvaSmX076pqQGcws38yeN7MHo64F0TOzZWa20MwWmFkGTDqGqJlZpZndY2avmNnirom7kaPMbFrX/iGxNJrZZVHXhWiZ2eVdx5eLzOxOMyuJuqZsRve2ATAzk1QWQthsZoWSnpb0xRDCPyMuDREzsy9Jmi6pIoSQhBltkc3MbJmk6SEE5lmAJMnMbpf0txDCrV0jmZaGEDZGXBYygJnlS1opn7h9edT1IBpmViM/rtwvhLDVzO6S9FAI4ZfRVpa9aOkZgOA2d90s7FpIkTnOzMZKOkvSrVHXAiDzmFmFpPdI+rkkhRDaCDzo4SRJbxB4IB9wbJCZFUgq1Q7mtUTfEXoGqKsb0wJJayQ9FkJ4NuKSEL0bJF0hqTPiOpA5gqRHzWyemc2KuhhEbrKkBkm3dXWDvdXMyqIuChnjw5LujLoIRCuEsFLStZJWSKqTtCmE8Gi0VWU3Qs8AhRA6QgiHSBor6QgzOyDikhAhMztb0poQwryoa0FGOTqEcJikMyR93szeE3VBiFSBpMMk3RxCOFRSs6Qroy0JmaCrq+NMSXdHXQuiZWZVkt4naZKkMZLKzOwj0VaV3Qg9SdLVNeGvkk6PthJE7GhJM7uu4fidpBPN7I5oS0LUQgirutZrJP1B0hHRVoSI1Uqq7dEz4B55CALOkDQ/hLA66kIQuZMlvRlCaAghbJN0r6R3R1xTViP0DICZVZtZZdfPg+Rv0FciLQqRCiF8NYQwNoQwUd5F4YkQAmdmcpiZlZlZeeJnSadKWhRtVYhSCKFe0ltmNq3rrpMkvRxhScgc54uubXA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\n", 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lkkY0uetwSe8kOTYgLrTJAQAApFOiYcjMhjT553GScivNPSrpZDOrNLPtJY2S9GKSYwPiQmUIAAAgndpY36rjzOweSYdIGmhmyyV9X9IhZraXvAVuiaQzJSmEMNfMZkiaJykjaUoIoT6usQFJYs4QAABAOsUWhkIIpzSz+5ZW7j9V0tS4xgMUSr5La5eUUBkCAABIUiFWkwOKCm1yAAAA6UQYAmJGGAIAAEgnwhAQs3zb5JgzBAAAkCzCEBCzfJfWZs4QAABAsghDQMxokwMAAEgnwhAQM8IQAABAOhGGgJgRhgAAANKJMATEjIuuAgAApBNhCIgZlSEAAIB0IgwBMctVe/JZWpswBAAAkBzCEBAzKkMAAADplFcYMrMHzOyzZkZ4Atqpvl4y8+sItaakhDlDAAAASco33Nwk6YuS3jCzq81sdIxjArqV+vq2q0ISlSEAAICk5RWGQgjPhBC+JGmspCWSnjaz583sa2ZWHucAga4ukyEMAQAApFHebW9mNkDSVyV9XdLLkn4pD0dPxzIyoJugMgQAAJBObaxv5czsQUmjJd0p6egQwrvZm+4zs1lxDQ7oDhoa8gtDJSVSCH7/tuYXAQAAoPPyCkOSfhtCeKLpDjOrDCHUhBDGxTAuoNvIZNpeVltqDEx1dVJlZbxjAgAAQP5tcj9sZt8/ohwI0F21p01OolUOAAAgKa2+X21mgyUNk9TTzPaWZNmb+krqFfPYgG6BMAQAAJBObTXvTJQvmjBc0rVN9q+XdFlMYwK6lfasJpe7PwAAAOLXahgKIdwu6XYzOyGE8EBCYwK6FSpDAAAA6dRWm9yXQwh3SRppZt/Y/PYQwrXNPAxAE4QhAACAdGqrTa53dtsn7oEA3VV9fftXkwMAAED82mqT+012e2UywwG6n3wrQ7lrCzFnCAAAIBl5La1tZj8xs75mVm5mM81slZl9Oe7BAd0BbXIAAADplO91hv4rhLBO0uckLZe0s6RvxTYqoBshDAEAAKRTvmGoPLs9StI9IYQPYhoP0O20d2ltwhAAAEAy8pjWLUl6zMxel7RR0jlmNkjSR/ENC+g+2lsZYs4QAABAMvKqDIUQLpH0SUnjQgh1kqokTYpzYEB3QZscAABAOuVbGZKkXeXXG2r6mDsiHg/Q7bC0NgAAQDrlFYbM7E5JO0p6RVJ9dncQYQhoE5UhAACAdMq3MjRO0pgQQohzMEB3xJwhAACAdMp3Nbk5kgbHORCgu8p3NbncRVepDAEAACQj38rQQEnzzOxFSTW5nSGEY2IZFdCN0CYHAACQTvmGoSviHATQnRGGAAAA0imvMBRC+KuZbSdpVAjhGTPrJSmP0zuguDU0SCEQhgAAANIorzlDZnaGpPsl/Sa7a5ikh2MaE9Bt1GfXXsxnae3cnCEWUAAAAEhGvgsoTJE0XtI6SQohvCFp67gGBXQXuTBEZQgAACB98g1DNSGE2tw/shdeZZltoA2EIQAAgPTKNwz91cwuk9TTzI6Q9HtJj8U3LKB7yLW85dMmRxgCAABIVr5h6BJJKyX9W9KZkp6QdHlcgwK6i45UhpgzBAAAkIx8V5NrMLOHJT0cQlgZ75CA7oM2OQAAgPRqtTJk7gozWyXpdUkLzGylmX0vmeEBXVt7wlBJiWRGGAIAAEhKW21yF8pXkds3hDAghNBf0v6SxpvZRXEPDujq2hOGJKm8nDAEAACQlLbC0FcknRJCWJzbEUJYJOnL2dsAtKK9YaisjDlDAAAASWkrDJWHEFZtvjM7b6g8niEB3QeVIQAAgPRqKwzVdvA2AGrf0toSYQgAACBJbZ2i7Wlm65rZb5J6xDAeoFuhMgQAAJBerYahEEKep3AAmsOcIQAAgPTK96KrADogF2yoDAEAAKQPYQiIEW1yAAAA6ZXntG4AHUEYKkLTprV82+TJyY0DAAC0icoQEKNcGMp3NTnmDAEAACSHMATEiMoQAABAehGGgBgRhgAAANKLMATEqL1tcoQhAACA5BCGgBh1ZGlt5gwBAAAkgzAExKgjF12lMgQAAJAMwhAQI+YMAQAApBdhCIhRLgyV5PmbRhgCAABIDmEIiFF9vVeFzPK7P3OGAAAAkkMYAmKUC0P5Ys4QAABAcghDQIwymfyX1ZZokwMAAEgSYQiIUXsrQ4QhAACA5BCGgBgRhgAAANKLMATEqCNzhlhAAQAAIBmEISBGVIYAAADSizAExIgwBAAAkF6EISBGHQ1DIcQ3JgAAADjCEBCj9i6tnbtvQ0M84wEAAEAjwhAQo45UhiRa5QAAAJJAGAJiRBgCAABIL8IQEKNMhjAEAACQVoQhIEYduc6QxLWGAAAAkhBbGDKzW83sfTOb02RffzN72szeyG63anLbpWa20MwWmNnEuMYFJKmhgcoQAABAWsVZGfqdpCM323eJpJkhhFGSZmb/LTMbI+lkSbtlH3OjmbXjFBJIp/r69q0mRxgCAABITmxhKITwrKQPNts9SdLt2c9vl3Rsk/33hhBqQgiLJS2UtF9cYwOSwpwhAACA9Ep6ztA2IYR3JSm73Tq7f5ikt5rcb3l2H9ClMWcIAAAgvdKygII1sy80e0ezyWY2y8xmrVy5MuZhAZ3D0toAAADp1Y7ZDJFYYWZDQgjvmtkQSe9n9y+XNKLJ/YZLeqe5JwghTJM0TZLGjRvXbGAC0oI2uRhNm9b67ZMnJzMOAADQZSVdGXpU0mnZz0+T9EiT/SebWaWZbS9plKQXEx4bEDkqQwAAAOkVW2XIzO6RdIikgWa2XNL3JV0taYaZnS5pmaQTJSmEMNfMZkiaJykjaUoIoT6usQFJYc4QAABAesUWhkIIp7Rw02Et3H+qpKlxjQcoBJbWBgAASK+0LKAAdDshcNFVAACANCMMATGpzzZ6EoYAAADSiTAExKQjYYg5QwAAAMkhDAExyQUaKkMAAADpRBgCYkKbHAAAQLoRhoCYEIYAAADSjTAExCQXhjqytDZzhgAAAOJHGAJi0pkFFKgMAQAAxI8wBMSkI2GoosK3tbXRjwcAAACbIgwBMcm1urWnTa6y0rc1NdGPBwAAAJsiDAEx6UhlqEcP3370UfTjAQAAwKYIQ0BMOjpnqKSEyhAAAEASCENATDoShsy8VY7KEAAAQPwIQ0BMOhKGJG+VIwwBAADEjzAExKQzYYg2OQAAgPgRhoCYdDQM0SYHAACQDMIQEJOOLK0t0SYHAACQFMIQEBPa5AAAANKNMATEhDY5AACAdCMMATHJtclRGQIAAEgnwhAQEypDAAAA6UYYAmLCdYYAAADSjTAExCQXhjqymhxtcgAAAPEjDAExoU0OAAAg3QhDQExokwMAAEg3whAQk/p6qaREMmvf42iTAwAASAZhCIhJJtP+qpBEmxwAAEBSCENATOrrOxaGcm1yIUQ/JgAAADQiDAEx6UwYCqHxoq0AAACIB2EIiEl9ffuX1Za8TU6iVQ4AACBuhCEgJp2pDEmEIQAAgLgRhoCYdDQM5SpDrCgHAAAQL8IQEJNMpmNtclSGAAAAkkEYAmLS2TY5KkMAAADxIgwBMclddLW9WEABAAAgGYQhICYdXU2ONjkAAIBkEIaAmNAmBwAAkG6EISAmnV1NjsoQAABAvAhDQEy4zhAAAEC6EYaAmHR0aW2uMwQAAJAMwhAQEypDAAAA6UYYAmJSWytVVLT/cYQhAACAZBCGgJjU1DS2vLUHbXIAAADJIAwBMaEyBAAAkG6EISAGIXQ8DFEZAgAASAZhCIjBxo2+7UgYKimRysupDAEAAMSNMATEoLratx0JQ5K3yhGGAAAA4kUYAmJQVeXbjiygIHkYok0OAAAgXoQhIAadrQxVVlIZAgAAiBthCIgBbXIAAADpRxgCYpBrk+tMZYg2OQAAgHgRhoAYUBkCAABIP8IQEIMoFlAgDAEAAMSLMATEIIoFFGiTAwAAiBdhCIhBLgxRGQIAAEgvwhAQg84uoMB1hgAAAOJHGAJiwHWGAAAA0o8wBMSgqkoqLfWPjqBNDgAAIH6EISAG1dUdrwpJtMkBAAAkgTAExKCzYYg2OQAAgPgRhoAYVFV1fCU5iTY5AACAJBCGgBhEURmqq5MaGqIbEwAAADZFGAJiEMWcIYl5QwAAAHEiDAExqKqKJgzRKgcAABAfwhAQgyja5CQqQwAAAHEiDAExiGIBBYnKEAAAQJwIQ0AMopozRBgCAACID2EIiAFtcgAAAOlHGAJiwAIKAAAA6UcYAiKWyUi1tSytDQAAkHaEISBi1dW+7cwCCrnHUhkCAACID2EIiFguDNEmBwAAkG6EISBiUYQhFlAAAACIH2EIiFhVlW+pDAEAAKQbYQiIGG1yAAAAXUNZIb6omS2RtF5SvaRMCGGcmfWXdJ+kkZKWSPpCCGFNIcYHdEauMhTFAgq0yQEAAMSnIGEo69MhhFVN/n2JpJkhhKvN7JLsv79dmKEBHdctK0PTprV82+TJyY0DAAAgQmlqk5sk6fbs57dLOrZwQwE6rluGIQAAgG6oUGEoSHrKzF4ys9zbytuEEN6VpOx26+YeaGaTzWyWmc1auXJlQsMF8hfFAgplZZIZbXIAAABxKlSb3PgQwjtmtrWkp83s9XwfGEKYJmmaJI0bNy7ENUCgo6KoDJl5dYjKEAAAQHwKUhkKIbyT3b4v6SFJ+0laYWZDJCm7fb8QYwM6K4oFFCQPQ1SGAAAA4pN4GDKz3ma2Re5zSf8laY6kRyWdlr3baZIeSXpsQBRylaHy8s49T2UllSEAAIA4FaJNbhtJD5lZ7uvfHUJ40sz+JWmGmZ0uaZmkEwswNqDTqqulnj2lkk6+1UCbHAAAQLwSD0MhhEWS9mxm/2pJhyU9HiBqVVVSr16df57KStrkAAAA4pSmpbWBbqG6OpowRGUIAAAgXoQhIGLV1VLv3p1/HsIQAABAvAhDQMRokwMAAOgaCENAxGiTAwAA6BoIQ0DEqqpokwMAAOgKCENAxKKqDNEmBwAAEC/CEBAxFlAAAADoGghDQMSiWkCBMAQAABAvwhAQMdrkAAAAugbCEBChEFhAAQAAoKsgDAERqq2VGhqirQyF0PnnAgAAwMcRhoAIVVf7NqrKUEODlMl0/rkAAADwcYQhIEJVVb6NagEFiVY5AACAuBCGgAjlKkNRtclJLKIAAAAQF8IQEKFcZSiqNjmJyhAAAEBcCENAhKKsDBGGAAAA4kUYAiIU5QIKtMkBAADEizAERIgFFAAAALoOwhAQIdrkAAAAug7CEBChKBdQoE0OAAAgXoQhIEJUhgAAALqOskIPAN3AtGmt3z55cjLjSAEWUAAAAOg6qAwBEaqqkkpKpIqKzj8XlSEAAIB4EYaACFVXe4ucWeefizAEAAAQL9rkgAhVV0fTIifRJleUWms5LaJ2UwAAkkJlCIhQVVU0iydIVIYAAADiRhgCIhRlZYgwBAAAEC/CEBChKCtDtMkBAADEizlDQIRyCyhEoaREKi+nMtRlLVsmPfec9Prr/p/Zq5fU0CCddprUs2ehRwcAAERlCIhUlG1ykrfKEYa6mNpa6bbbpKlTpX/8Qxo6VBo2TKqrk84+Wxo5UvrDHwo9SgAAICpDQKSibJOTvFWONrkuZPly6ac/9arQUUdJhx/emI5DkHbZRbroIumYY6Rf/lI699zCjhcAgCJHGAIiFGWbnERlqEv54AMPP++/L51zjrTnnpvebiYdcoi3zn3pS9J550kbNkiXXFKQ4aZea8uMSyw1DgCIBG1yQISqqqJtk6My1EXU1EjHHSctXuzVns2DUFN9+kgPPih98YvSpZdKDzyQ3DgBAMAmqAwBEaIyVKTOPlt69lnpnnukdevavn9pqXTLLR6eTj3V5xHts0/swwQAAJuiMgREpKFB2riRBRRitWqVNGOGz7f54x+lRYv8B19I997rCyZ897vSySfn/7gePaSHH5YGDpROOcXLigAAIFFUhoCIbNzoWxZQiMGyZdJVV0m/+93H02GfPtKkSdKECb6EdZKWLpXOOkv65Cel732v/Y/femvpjjukQw+VvvUtaa+9Ih8iAABoGZUhICLV1b6lTS5ijz/uIeHWW6Uvf1l68UWvEF1zjfT1r/vS1dOnS9deK61Zk9y4Ghqkr3zFt3fdJZV18L2lQw7xFeZuukmaMyfSIQIAgNYRhoCI5LqcaJOL0I9+JB19tM+pmTtXuvlmad99pQEDvCK0777SN77hoeStt3xZ6xUrkhnbr3/t84R+8Qtphx0691xTp0pjxniooxQIAEBiCENAROKoDBV1m9z110vf+Y5Xg55/Xtppp+bvZyaNH++hqKbGA9E778Q7tqVLpW9/WzriCOlrX+v88/XoIf3mN7489+OPd/75AABAXghDQERyYSjKylDv3tL69dE9X5cxY4Z0/vk+F+i22zwstGW77XzeTUmJ9KtfSW+/Hc/YQpDOPNO306Z5GIvChAke6p55Jr6xAwCATRCGgIjk2uSirAwNGSK9956fdxeNmTO9GjR+vC9V3Z65OIMH+8VMq6ulo47Kb5nr9rrzTl/J7qqrvH0vSscfL/XsKd19d5H9pwMAUBiEISAiuakqAwdG95xDh3rn1wcfRPecqTZ7tnTssdIuu0iPPurBoL1GjPAV3ubNk046Saqvj258770nXXihB7UpU6J73pw+ffz7X7hQmjUr+ucHAACbIAwBEVmyxLdRFguGDfNtUXRNLVwofeYzvjjCH/8obbVVx59rzBjphhukJ5/0uT1RCEE691yvOt1yS3zLeE+Y4IHugQek2tp4vgYAAJBEGAIis2SJ1L+/1LdvdM85dKhv414PoODee0+aONGrOH/8Y+M33hmTJ3t4ueYavz5RZ911lweUK6/0ylVcSkq8orVmjYc5AAAQG8IQEJElS6KfQlIUlaG1a6Ujj/Q+wyeeiDZo/Pzn0uGH+4IHzz/f8edZvNjb4g46SPrmN6MbX0tGjfJlw596Slq9Ov6vBwBAkSIMARGJIwwNGeLbblsZ+ugjnyMzd65XXfbbL9rnLyuT7rtP2nZb6bjjpGXL2v8cdXW+oENJiS+eUFoa7Rhbcvzxvn3ggWS+HgAARYgwBEQghHjCUGWlL8jQLStDmYyHjL/8xdvYJk6M5+v07y899pgHr6OOklatyv+xIUhnn+1VpV//2pfvTkr//j6H6qWXpAULkvu6AAAUEcIQEIGVK6WNG6MPQ5JPn+l2YSiTkU47zase114rfelL8X690aOlRx6R3nzTL5S6Zk1+j/vxj32xhMsvl04+Od4xNueII3xBiRkz/GcGAAAi1Y4LeABoSRwryeUMG9bN2uTq6qSvftWvpXPVVdJFFyXzdQ85RHr4YemYY6RPf1p68EFphx2av28IPrbvfMdD0A9+kMwYN1dRIZ1wgl/c9eabvUqFeE2b1vrtkycnMw4AQCKoDAERWLrUt3GFoW5TGVqzxlu/ckHokkuS/foTJ/r1i5YulcaO9flEm1+H6P33vVL1ne/49rbbJLNkx9nU2LHSzjt7dapoLjgFAEAyqAwBEchVhtqaUjL62fa/6zx0qJ+f19VJ5eUdG18qvPyyV1kWL5ZuvVX62tcKM46JE/3iriee6OMZOdI/79lTWrTIW9Lq6qQf/cjDWiGDkORf/6STpKlTpe9/X7ruusKOBwCAboTKEBCBJUv8GqFRXmMoZ9gw79p6773onzsR1dVe1dh3X19Ge+bMwgWhnO23l/7xD68MjRwp/exn3gr3yCPSGWdI8+ZJl15a+CCUM3y4dNZZ0k03SXPmFHo0AAB0G4QhIAJxrCSX02UvvLp6tXT11f6DmTrVV46bN8+v1ZMG5eXSF74g/fnPUkODJ85166Trr/cFF9LmBz/wtH3BBT5WAADQaYQhIAJxhqEuc+HVhgbptdekG27wJawHD/bqytix0nPP+fLZ/fsXepRd14ABHoj+9CdfCAIAAHQaYQjopLiuMZST2spQXZ20cKFXfz77WQ86e+4pnXuu9Prr0sUXS6++Kj35pDRhQqFH2z2cdZa0++7SN77ha7kDAIBOYQEFoJNWrfJpMXGFoUGDpLKylFSGMhkPOC+95HNXamp8/+jR3nJ20EH+sd126Zlv052UlUm/+pV06KFeJbrqqkKPCACALo0wVExau34G187osDivMSRJJSXSkCEFrgxt3OjtWX/9qy+C0LevtN9+0m67+Un5oEEFHFyR+fSnfQGKn/7UV8Pbc89CjwgAgC6LMAR0UtxhSCrgtYYyGV/B7PLLpQ0bvEXrK1+RxozxlCYRhArhZz+T/vAH6fTTpX/+0ytGAACg3ZgzBHRSvtcY6oyhQwtQGZo7VzrwQOn88z2NXXaZdN55HohKeOkoqP79/XpDL73kFSIAANAhnNEAnbR0qV9jqF+/+L5GopWhEHx56bFj/QKp994rXXRRvGkP7XfiiT5P63vf8wvaAgCAdiMMAZ0U50pyOcOG+SVwNmyI9+towwbplFO8AnTEEV4dOukkFkNIIzNvYRw0yK/h9NFHhR4RAABdDmEI6KQkwlAiy2u/9ZYvgf373/sqZY8+Km29dYxfEJ3Wv790221+MduLLir0aAAA6HIIQ0An5K4xFHcHWewXXn3xRV8dbvFi6YknpEsuYV5QVzFxovTtb0u//rV0112FHg0AAF0KSxAhfw0N0oIF0r/+5RfbXLLE26refFPq2dMnzQweLO24o7TNNkXRWrV6tVRV1cUrQ7//va8QN3iw9Mwzvlx2G2ozJSotCSotCTEMCO32wx9K//iHdOaZvtT2HnsUekQAAHQJhCG0rrbWT5BnzPC2qTVrfH9JiTR8uF9vZu1aL1msXetLMUvSlltK++wj7b9/wYaehCSW1ZZiqgyFIE2dKn33u75q3MMPt7lM9pJVfXTdn3fXzX8brcNHv60HznpacUTezS+JVV/v+fvll/1ar/36SUdtuZs+NWKxBvaqliQdfHAMA+kqysp8oYuxY6Wjj/bltgcPLvSoAABIPcIQPi6T8QtszpghPfigB6B+/aRjj/ULPu63n7TTTlJ5ud8/d+ba0CCtWOGVotde8wt0zpwpPfus9M1vSscc0+2qRUmFoS22kPr0ibAyVFXlF+78/e998v3NN0s9erR49w+qKnX29Am6f/b2MpP23/59PfTK9rrxL2M05cyIxrSZhgZp0SLphRek2bO9CFleLo0e7RW5Xy0cr+tmHahPDlumKw96WlJDPAPpKoYMkR5/3FPhMcdIf/mL1KtXoUcFAECqEYbg6us9tNx3n/TAA9KqVX4GPmmSL9/7X/8lVVa2/hwlJX5CNmSIT8SvrvbWnRdf9CB1wAF+scjx4xP5lpKQxDWGciJbXnvpUv9//fe//Ro1F1/cZkj91gP768GXt9c3j3hN5356roZvVaXPXX+kLr7/AB18WSe6sjYvAckLVq9N20MPLNhd71VtocrSjMYPX6pD9l6k/Ya+pZ5lXn1csnZLPbV4lKbP3Vu3vLqvDv/0Cx0cRDeyzz7S3XdLxx0nff7z0kMPtf172xWsXu0tusuW+TsCH37o89oyGT92t9zSF/vYaSe/IHDuY9QoLkgLAGgVfyWKWUODV3FmzfJrlaxY4e8kH320L6d85JE+F6ijevWSDjtMmj5duv12b8eaMMFP1K66Stpll+i+lwJZssTPw7bcMv6vFcmFV5991k+Sa2u9ivCZz7T5kH/+U7r176N1yphX9NlBL2rxHGmxpMm7/EX/XPh5HXlkmS69VKqo+PhjJ09u3/Ay9aaz756g387eVXtv87ZO3/NfmjB8iXqVZz5235H9PtTkvf6l9TWVum/+J3TWf5bpUzu/274v2B1NmiT95jf+w//CF7z619x/TtqtXOlvpsyeLb2b/X+trPR3BYYP9zdXysv9dezDD/3164UXvF0wp0cP6ROf8PbBvff27e67t1oFBQAUF8JQsckFoNmz/ePDD/2E4phjPAAddZTUu3e0X7OsTDr9dOnkk6Wf/1z68Y99/tG550pXXJFMkohBCF702mmnZL7esGHSc8918MF1ddKVV3oI3Wkn//nnEUbr66UpU6ShW1bpK7tvemHPrXp8pMsO/LO++afP6v77pS9+sYNjy6quLdXJNx+ux17bTqfuNlun7zkrr67Kc/b5p15aMUxfue0Qvfa9+9WvZ13nBtIdnHGG/59PmSKdcIIHhKh/r+NQXy899pj0q19Jf/6zV3123tnfRBkzxudB5VY5bClpV1VJr7/u18h69VWfaHbPPb7anuSvRzvvLO2wg7T99r4dOdIXfdlmG6mmpntU0wAAeSEMFYO6Op8/MH269MorfvXOsjJfNeyEE/yd0/PPj38cvXtLl1/uJzHf+56f8EyfLv3oR9L/+39SaWn8Y4jQ88/7wnrXX5/M18tVhkJo59Sr55/34Pnyyz5P6Be/8IUv8nDzzZ6Z7/n6P9Vr48dDxr5D3tYRR0hPPy3ttZefr3bEh9UV+syvPqMXlmytG7/4nHaz+Xk/tmdZRpcf+Ced+/QknXfveN3xtb90bBDdzTnneHCYMsXn+j3+eHqvG1VT49Xjn/zE36wZMcIrXAcc4NdSao/evb1dcJ99Gvfl1sCfPbtxFY7Fi/11sbkrGVdU+O/IFls0bnOfDxvmK/YNG9bt5kACQDEiDHVXNTV+hvrAA14F+OAD/wO/xx7eLrLHHoVrFdl6a3+X9swzPYRNnizddJOHowkTCjOmDvjpT6UBAzxf5C0EldVWqzRTo5L6WgUrVUNpmeoq+yiUlrf60GHDPNeuWtXmom9uzhyvBN19tz/4wQe9RTFPq1ZJl13m59EnjXuzxarUpEn+Bvz06dL3v9/+jqxMvekL0w7XS8sG6v7JT+v4sUv07LPte44xA1fq8qNe1pWP76PP7r5MJ+27qH1P0F2ddZbP4TvlFGncOK8QHXhgoUfVaMMGnzd2zTWe9PfdV7r6ap9jeOut0X0dM68Cbb+9vwGUE4LPR1q61Nvs3n/fXy/XrZPWr/eP1as9OK1f7/e/7z5/7FZb+RtJ++wjHXqoL1yxxRbRjRkAkAjCUHeyerVfMPPRR6U//tH/ePfr53OATjhBWr48XXMH9t67cdGGb31LOuggP2m76qpkViTohAUL/Mf83e+2sGBXCOr9wVsauOxlDVw2WwPfellbvTNXfT5YppKGj89/kaTayj7SnBt9PsQOO3gb2+jR/jF0qIYN83eh33mnlTC0Zo23Gd19tx8DvXpJl17qqaZPn7y/vxB8XYX166XrrpPs7y3ft7xcOvVUP5997LFNzzXzcdGMT+rp+cP121P/quPHLmnfg5u4/KjZemreMJ1x18EaN3KlduzwM3UzkyZ5f+WJJ/oJ+w9+4L9v5a2H71itWOEH1o03+jF76KFeGTrssGSrLWbSwIH+kVNb2/x9Gxo8vB1wgK+W+dpr/i7ADTdI117r1fb99pMOP1z63Oc8JHHhYgBIPcJQV5c7K3/sMenvf/c/2EOG+Pyc447zk4tcAGpm5a6CM/OxHn20zyX6yU+k++/3OQ+XXurBIIWuucanFUyZ0mTnu+/6UuLPPCM984y+lF36rcFK9OHg0Vo5cl+tHbSTanv2U315DzWUlkshqKShThUb16mi+kMNHdFXeustX5a8aftOnz46csQuulc7qu6cwdLEAY3/r6tXe0J69VVp/nw/BoYP95Pec87x8lU7XX+9dMcdHvZ2201SK2FIapzW8cwz/ub+ttvm93Vu/MsYXf+X3XXxEa/q9AkL2j3OpspKg+49Y6b2+p8T9IVph+v5bzL14//ss4+3h51xhvSd7/gcmptuSr4S+/rr/stz550eOo49Vvrv//aAkXYlJd4mN2HCpj+3jRt9oYeZM/3jhz/0373Bgz0UHX20BySWOQeAVCIMdTUbN3ro+d//9QD0xhu+f889/STn6KO75juSvXv7CcQZZ/iFQKdN84+TTpIuuMBbfFLSn79ihQeFM7+4Xlv/61lvR3z6aWnePL/DgAHSoYfqb6Wf0qrt9tHq4Z9QfYWfCI1+tvVAOvSu7KTwEDzgLFjgJ5ALFqjXggU6aNnL6v38Cun5dY0Pqqz0id+f+ISvFHfUUZ5IOvjzeuop6cILvaBwxRX5P+744/3N8jvu8Bzb1hSwJ5+Uzr/vQH12j6X68fEvdmism9u2f5V+99W/atKNE/Wtb3nnJbL69fNrhz3yiHTeeV6JPfJIT7yf/GR8v19r1/qKdrffLv3tb96e+7WvSRdd5Cm6q+vZ0ytbhx7qr12rVze+Ps+YIf32t/49H3aYvz5/7nONV1EGABRc6sKQmR0p6ZeSSiX9NoRwdYGHVFjV1T7pN3cB0+ef9/lAFRU+meOCC/wPbL5vxafdiBE+n+jSS6Vf/tJn8E+f7nOcTj3Vz7h3LFAD1EcfSbNn69+XztRTNU/roDv/Id2W8ROdgw+WvvpVfwd4zz2lkhLN60whzsxPmIYN85MsSSapYpU0eg9pmwEZ/fO5OvWoDH4yFtGJ7IIFvhrz7rtLd93Vvkzdu7cX+aZN8/PeU05pvhhZX+/dnH/4g7RDvzWasuuf9Pe/hUjGL0nH7LlUFx72b/3iuj30qU+1v22v25s0yY/TG27wiW/jx/sx+/Wve6Umimrshx/6GwQPPeQfH33kbZ8/+pGvLJnWhRyiMGCAX8j4y1/26tdzzzVW7//wB7/P2LH+un3YYf5GT2cuYQAA6JRUhSEzK5V0g6QjJC2X9C8zezSEMK+wI0tACN5m9Z//eCXgpZd8qbI5c/zsUfITlilT/A/owQe3aw5Il7Pddt6H//3v+5yiW2/1dpr//m9p1109CE6Y4GftO+8cfT/U6tVedZs/3/8fXnxR4dVXZZmMDpVp0ZZjZWd9UzriCJ+QntBiFAMHSrfdJn3mM2W67H/KdO210TxvQ4NPMTr/fM/Zjz7ascNr7Fjps5/1sLNggfSlL3nBKmf1aumWW3zBsAMOkL6/7aPqVR79Utg/Pv4F/X3dHjrxRM+o//M/ybwZn8lIb7y7pea8s5U+qOqhyrJ6VZbVq09lncYMXaPtG1JStO3d23+XzjnHW9ZuvtmrReed58sCTpgg7b+//67ttJNXlZrT0ODXA1q0yCujL7/sLWOvvuqvW1tt5VWg007z+TQpqe62Vwi+4mF9MPWs8uyS1/9jRYW/Xh92mK/iOG+eh6LHHvNK+JVX+tytsWP9dWTcOJ8juMsuXWMpdADoBlIVhiTtJ2lhCGGRJJnZvZImSUp/GArBl/qqrfXKTW1t48fGjb460bp13jKyZo303nseft57T3r7bT/xbjpHZKut/OTh6KN9e8ABzc6aD8Gffv36xi/R0ud1s/ZX3x616tezVn171qpvjzr17VGrvj3r1HeBt8P37eut7fmes4QghQapIZiCpBDM98lkCjKTSrIXiS8p6cC5UL9+vtrc5Mm+4tPDD/tZ+x13+ORryfuxRo3yk4jBg/3nNGiQJ4cePfxkI/dRX+/vUuc+1q71FaTef99P6pYv9/+LNWv+bwgNfbbQe8P31WP9vqUnV++rRcMO1vQnB0i7t/N7iciRR/pK2T//uX/L++3nb+YPGJDfzzcEvxTLqlUeTv70Jy/GLVrkP76HHur4+hVmfsmqT3zCq0M33OALeGUyfnivXevnh6ef7uPu9Ww81wSqKGvQU0/59I3rrvNF1C680N9DGDHCf14tnd+3JgT/XVqzxosfb73l71fkPl5/Xaqt/UKLj+/7E39PY5dd/Ge83XZeJKmp8SJw1d920Ttre2np6i209IM+WrGupzbWlam6tkw1l/lhPXy4f+S+jxEjPOj169e4AnTeayP06SOdfbZ/5E7Un3zSE3fTNeN79PADrGdPXyigttb/Qz/4wP9zc3r39hB12WXSxIn+eVna/sxsqqHBXyfXrvWPd+YO16JVW2jRyr5avNq3i1ZtobUbs2+4XOybvn39ZWeXXRr/P3PF3IEDN33ZKS+XzMwn4O22m3TJJf4L+PzzjR833eSvSTnbbutfYMgQ/8UcMsQPlr59/efcp8+m28pK/+WqqEhJ4gaQdpmMnw9UVTUunrl6deP5Qe7zqio/N+zd2z8GDvTu/MGD/fN+/RqvQlBW1vXe97IQomtP6Swz+7ykI0MIX8/++1RJ+4cQzm3u/uPGjQuzZs1KcogtGzjQj5p8mfkftiFD/GOnnfwv6s47+3bEiGaPpsce82k09fWNH/koLZVKQ0a1DW2fmJg1funmDugQ/ASio3LPnwtHm29bkztcy0KdRof52rVhrnZtmKvRYZ5GNSzQoPC+Bmi1SpT/cd0g0yoN1CobpPdsiN60nfSGdtb8+lH6j3bWGxqloBLttZcvwnXiifmdbDbXItbWnKGDc3OG2lBd7eeZc+Y07israzwH2vzXuum/Q/j4cTNqlHTIIV4UaO7ctbVxv35w82POZPy8eu7cxnO2fv286JDL9W39PNrj4IM325G9KOfixY1rBmwudyy29iH5zyuTafm479/fT4KHDpXGrf+Ttu+3Rlv12Ki6hlLV1pdo590r9O+3++uVvp/SK69ICxf63LOWbNO3Wv3LN2hAz2r1KKtTZWm9NgwfrfXrPYitWeMn7i29fDf9/d38e2ltX05JqNcu4XXtWP8f7RgWalB4X/3DalWqRmWqU60qVKU+WmP99Y4N01u2reZpjJbaSDVY42Sx5saX9776j/+wN7mbNZ7wd+brtKSiJKPBfdZraJ/1GtJnnYb0Wa/ykga9te34/8uCFRVeAV22rO3nLi31142W5tKVh1rtFN7Qzg2va5eG+dq54XVtH97UNuE9DQ7vqodq8hr3r8q+ocsqr8n/GwUQi3xegwp1n9zn+bxu5d5rKS/3c48NGzZ9D6w5ZWX+MX68L6yUFmb2Ughh3Mf2pywMnShp4mZhaL8QwnlN7jNZUu7saxdJuSWoBkpaleBwAYnjDoXBcYdC4dhDIXDcIQrbhRA+1maVtv6F5ZJGNPn3cEnvNL1DCGGapI+9nWxms5pLe0CcOO5QCBx3KBSOPRQCxx3ilLbG4n9JGmVm25tZhaSTJT1a4DEBAAAA6IZSVRkKIWTM7FxJf5QvrX1rCGFugYcFAAAAoBtKVRiSpBDCE5Ke6MBDo5uJDeSP4w6FwHGHQuHYQyFw3CE2qVpAAQAAAACSkrY5QwAAAACQiNSFITMbYWZ/NrP5ZjbXzC7I7u9vZk+b2RvZ7VbNPHYXM3ulycc6M7swe9sVZvZ2k9uOSvhbQ4p15rjL3u+i7OPmmNk9ZtajPY9H8Yrx2OM1Dy2K4Li7IHvMzc39nW3P41GcYjzueL1Dh6UuDEnKSLo4hLCrpAMkTTGzMZIukTQzhDBK0szsvzcRQlgQQtgrhLCXpH0kVUt6qMldfp67PTs3Ccjp8HFnZsMknS9pXAhhd/niHydnb27z8Sh6cR17Eq95aFlnjrvdJZ0haT9Je0r6nJmNyt7Max5aE9dxJ/F6hw5KXRgKIbwbQpid/Xy9pPmShkmaJOn27N1ul3RsG091mKQ3QwhLYxoqupEIjrsyST3NrExSLzVeH6u9xy2KTIzHHtCiTh53u0r6ZwihOoSQkfRXScdlb+M1Dy2K8bgDOix1YagpMxspaW9JL0jaJoTwruS/TJK2buPhJ0u6Z7N955rZa2Z2K6V7tKS9x10I4W1JP5O0TNK7ktaGEJ7K3tze4xZFLOJjT+I1D3nowN/aOZIONrMBZtZL0lFqvGA6r3nIS8THncTrHTootWHIzPpIekDShSGEde18bIWkYyT9vsnumyTtKGkv+UnDNdGMFN1JR4677IvuJEnbSxoqqbeZfTm+UaI7iuHY4zUPberIcRdCmC/px5KelvSkpFfl7U9AXmI47ni9Q4elMgyZWbn8l2R6COHB7O4VZjYke/sQSe+38hSfkTQ7hLAityOEsCKEUB9CaJB0s7znFPg/nTjuDpe0OISwMoRQJ+lBSQe24/EocnEce7zmoS2d+VsbQrglhDA2hHCwpA8kvdGex6N4xXHc8XqHzkhdGDIzk3SLpPkhhGub3PSopNOyn58m6ZFWnuYUbdYil/slyzpOXm4FJHX6uFsm6QAz65V9nsPkfdD5Ph5FLK5jj9c8tKazf2vNbOvsdltJx6vxby6veWhRXMcdr3fojNRddNXMJkh6TtK/JTVkd18m7ymdIWlb+QnAiSGED8xsqKTfhhCOyj6+l6S3JO0QQljb5HnvlJdPg6Qlks7M9acCERx3V0o6SV6yf1nS10MINWY2oLnHJ/edIe1iPPZ4zUOLIjjunpM0QFKdpG+EEGZm9/OahxbFeNzxeocOS10YAgAAAIAkpK5NDgAAAACSQBgCAAAAUJQIQwAAAACKEmEIAAAAQFEiDAEAAAAoSoQhAEC3YWaXdeKxh5jZgW3fEwDQXRCGAADdSYfDkKRDJBGGAKCIEIYAAKlhZl8xs9fM7FUzu9PMfmdmn29y+4bsdoiZPWtmr5jZHDM7yMyultQzu296c8+X3Xe0mb1gZi+b2TNmto2ZjZR0lqSLso8/KPnvHgCQNC66CgBIBTPbTdKDksaHEFaZWX9J10p6PIRwf/Y+G0IIfczsYkk9QghTzaxUUq8Qwvrc7S09X/aq9ltJ+jCEEMzs65J2DSFcbGZXSNoQQvhZ8t89AKAQygo9AAAAsg6VdH8IYZUkZYNLS/f9l6Rbzaxc0sMhhFfyeb7s/uGS7jOzIZIqJC2O7lsAAHQltMkBANLCJG3erpBR9m+VeTKqkKQQwrOSDpb0tqQ7zewreT6fJF0n6foQwh6SzpTUI5LRAwC6HMIQACAtZkr6gpkNkKRsm9wSSftkb58kqTx723aS3g8h3CzpFkljs/epy1aLWno+SeonD1GSdFqTr79e0hYRf08AgBQjDAEAUiGEMFfSVEl/NbNX5fOFbpb0KTN7UdL+kqqydz9E0itm9rKkEyT9Mrt/mqTXzGx6C88nSVdI+r2ZPSdpVZMhPCbpOBZQAIDiwQIKAAAAAIoSlSEAAAAARYkwBAAAAKAoEYYAAAAAFCXCEAAAAICiRBgCAAAAUJQIQwAAAACKEmEIAAAAQFEiDAEAAAAoSv8fexDahTGqG/QAAAAASUVORK5CYII=\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "l = ['amount','age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", - "for i in l:\n", - " plt.figure(figsize=(14, 8))\n", - " sns.distplot(data[df['fraud'] == 0][i],color = 'blue')\n", - " sns.distplot(data[df['fraud'] == 1][i],color = 'red')" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for i in ['gender', 'category']:\n", - " plt.figure(figsize=(20, 10))\n", - " sns.barplot(x = i,\n", - " y = df['fraud'],\n", - " data = data)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the numerical column the values which were fraund and those which were not visibily seperated after a certain value, clearly showing patterns with the exception of age column. The gender column is an interesting one as it tells that the number of females being cheated is significantly higher" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "#adjusting skewness\n", - "import numpy as np\n", - "data['meramt'] = np.log((data['meramt'] + 0.00000001))" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "data['catamt'] = np.log((data['catamt'] + 0.00000001))" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [ - "data['custcat'] = np.log((data['custcat'] + 0.00000001))" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [], - "source": [ - "data['custamt'] = np.log((data['custamt'] + 0.00000001))" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [], - "source": [ - "data['mercat'] = (data['mercat'])**(1/3)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [], - "source": [ - "data['catage'] = (data['catage'])**(1/3)" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['step', 'customer', 'gender', 'merchant', 'category']\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "filtered = data.dtypes[data.dtypes == np.object]\n", - "colname = []\n", - "colname = list(filtered.index)\n", - "print(colname)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [], - "source": [ - "data = data.drop('fraud', axis = 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [], - "source": [ - "data_num = data.drop(colname, axis = 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [], - "source": [ - "data_cat = data[colname]" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SimpleImputer(strategy='median')" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.impute import SimpleImputer\n", - "imputer = SimpleImputer(strategy=\"median\")\n", - "imputer.fit(data_num)" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "data_imp = imputer.transform(data_num)" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [], - "source": [ - "data_tra = pd.DataFrame(data_imp, columns=data_num.columns,\n", - " index=data.index)" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "StandardScaler()" - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.preprocessing import StandardScaler\n", - "scaler = StandardScaler()\n", - "scaler.fit(data_tra)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [], - "source": [ - "scale_train = scaler.transform(data_tra)" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [], - "source": [ - "data_sc = pd.DataFrame(scale_train, columns=data_tra.columns,\n", - " index=data_num.index)" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [], - "source": [ - "data_cat = data_cat.drop(['customer', 'step'], axis = 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [], - "source": [ - "data_cat_encoded = pd.get_dummies(data_cat)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [], - "source": [ - "data_join = pd.concat([data_sc, data_cat_encoded], axis = 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(25200, 74)" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data_join.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Above we have imputed and scaled the features, imputation is not necessary in this case as there is no missing value present, yet I have used it just to show end-to-end data science pipeline as asked in the task.
\n", - "After this we have one-hot encoded the categorical features and dropped customer and step colimns as given in the assignment notebook" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [], - "source": [ - "from sklearn.model_selection import train_test_split\n", - "y = df['fraud']\n", - "X_train, X_test, y_train, y_test = train_test_split(data_join, y, test_size=0.75, random_state=42,stratify=y)" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "RandomForestClassifier(class_weight='balanced', criterion='entropy',\n", - " random_state=42)" - ] - }, - "execution_count": 62, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sklearn.ensemble import RandomForestClassifier\n", - "\n", - "forest_reg = RandomForestClassifier(criterion='entropy', class_weight='balanced', random_state=42)\n", - "forest_reg.fit(X_train, y_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [], - "source": [ - "y_pred = forest_reg.predict(X_test)\n", - "y_prediction = forest_reg.predict_proba(X_test)" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.9971902606310015\n", - "[[13272 228]\n", - " [ 142 5258]]\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 64, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from sklearn.metrics import roc_auc_score\n", - "from sklearn.metrics import confusion_matrix\n", - "\n", - "if df['fraud'].nunique()> 2:\n", - " rules_score = roc_auc_score(y_test, y_prediction[:,1], multi_class = 'ovo')\n", - "else:\n", - " rules_score = roc_auc_score(y_test, y_prediction[:,1])\n", - "\n", - "print(rules_score)\n", - "\n", - "from sklearn.metrics import confusion_matrix\n", - "cf_matrix = confusion_matrix(y_test, y_pred)\n", - "print(cf_matrix)\n", - "\n", - "import seaborn as sns\n", - "sns.heatmap(cf_matrix, annot=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As seen above just with simple feature engineering we reduced 79 false positives and improved roc score. Let's use regularization by cross validation to see what happens" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "metadata": {}, - "outputs": [], - "source": [ - "def display_scores(scores):\n", - " print(\"Scores:\", scores)\n", - " print(\"Mean:\", scores.mean())\n", - " print(\"Standard deviation:\", scores.std())" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Scores: [0.99759259 0.99767215 0.99580316 0.99845885 0.99724417 0.99762346\n", - " 0.99698217 0.99722977 0.99861934 0.99639575]\n", - "Mean: 0.9973621399176956\n", - "Standard deviation: 0.0008087641314100779\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import cross_val_score\n", - "forest_scores = cross_val_score(forest_reg, X_test, y_test,\n", - " scoring=\"roc_auc\", cv=10)\n", - "display_scores(forest_scores)" - ] - }, - { - "cell_type": "code", - "execution_count": 67, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[13288 212]\n", - " [ 130 5270]]\n" - ] - } - ], - "source": [ - "from sklearn.model_selection import cross_val_predict\n", - "from sklearn.metrics import confusion_matrix\n", - "cm_score = cross_val_predict(forest_reg, X_test, y_test, cv=10)\n", - "conf_mat = confusion_matrix(y_test, cm_score)\n", - "print(conf_mat)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As we can see that with 10 fold cross validation we get the roc score with a maximum value of 0.99861934 and reduce the number of false positives to 212" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The hyperparameters for this model were tuned using Random Search, and gave an roc score of 0.99989934 however it worsened the false positive number, which is why we have chosen the base model itself" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} From a31b8286089d187a647d5b7ff9e12e5cf00e389c Mon Sep 17 00:00:00 2001 From: Cheril Shah <79891166+Cheril311@users.noreply.github.com> Date: Fri, 15 Oct 2021 10:15:49 +0530 Subject: [PATCH 3/3] Add files via upload --- datarobot_CherilShah.ipynb | 2185 ++++++++++++++++++++++++++++++++++++ 1 file changed, 2185 insertions(+) create mode 100644 datarobot_CherilShah.ipynb diff --git a/datarobot_CherilShah.ipynb b/datarobot_CherilShah.ipynb new file mode 100644 index 0000000..0fd5cbb --- /dev/null +++ b/datarobot_CherilShah.ipynb @@ -0,0 +1,2185 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DataRobot Internship Task" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Loading the dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "data = pd.read_csv(r'sampled_data2.csv')\n", + "df = data.copy()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Noting the feature names for directly manipulating or analyzing these. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['step' 'customer' 'age' 'gender' 'merchant' 'category' 'amount' 'fraud']\n" + ] + } + ], + "source": [ + "print(data.columns.values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "preview the data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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stepcustomeragegendermerchantcategoryamountfraud
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12021-08-22C48391213126to35FemaleM1198415165Beauty&Wellness608.321
22021-06-03C168158960026to35FemaleM348934600Transportation43.760
32021-07-01C125174929436to45FemaleM1823072687Transportation41.570
42021-03-06C170534621636to45MaleM348934600Transportation42.970
52021-03-27C3467668626to35MaleM348934600Transportation32.610
62021-03-18C76036840536to45MaleM980657600Sports&Toys410.671
72021-07-16C165503714726to35FemaleM480139044Health16.451
82021-05-13C178945787226to35FemaleM3697346Leisure300.621
92021-07-23C47754287426to35FemaleM85975013Groceries47.470
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" + ], + "text/plain": [ + " step customer age gender merchant category \\\n", + "0 2021-07-16 C1326593353 36to45 Male M1823072687 Transportation \n", + "1 2021-08-22 C483912131 26to35 Female M1198415165 Beauty&Wellness \n", + "2 2021-06-03 C1681589600 26to35 Female M348934600 Transportation \n", + "3 2021-07-01 C1251749294 36to45 Female M1823072687 Transportation \n", + "4 2021-03-06 C1705346216 36to45 Male M348934600 Transportation \n", + "5 2021-03-27 C34676686 26to35 Male M348934600 Transportation \n", + "6 2021-03-18 C760368405 36to45 Male M980657600 Sports&Toys \n", + "7 2021-07-16 C1655037147 26to35 Female M480139044 Health \n", + "8 2021-05-13 C1789457872 26to35 Female M3697346 Leisure \n", + "9 2021-07-23 C477542874 26to35 Female M85975013 Groceries \n", + "\n", + " amount fraud \n", + "0 15.78 0 \n", + "1 608.32 1 \n", + "2 43.76 0 \n", + "3 41.57 0 \n", + "4 42.97 0 \n", + "5 32.61 0 \n", + "6 410.67 1 \n", + "7 16.45 1 \n", + "8 300.62 1 \n", + "9 47.47 0 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.head(10)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "get basic information of the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 25200 entries, 0 to 25199\n", + "Data columns (total 8 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 step 25200 non-null object \n", + " 1 customer 25200 non-null object \n", + " 2 age 25200 non-null object \n", + " 3 gender 25200 non-null object \n", + " 4 merchant 25200 non-null object \n", + " 5 category 25200 non-null object \n", + " 6 amount 25200 non-null float64\n", + " 7 fraud 25200 non-null int64 \n", + "dtypes: float64(1), int64(1), object(6)\n", + "memory usage: 1.5+ MB\n" + ] + } + ], + "source": [ + "data.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that we have 8 columns, each column has 25200 non-null rows, this can mean that their is a high probability that the dataset has no null values, but it's better to check. Of the 8 columns/features only 2 are numerical while the rest are categorical." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "checking for null values" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "step 0\n", + "customer 0\n", + "age 0\n", + "gender 0\n", + "merchant 0\n", + "category 0\n", + "amount 0\n", + "fraud 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "this shows that there are no null values in the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " amount fraud\n", + "count 25200.000000 25200.000000\n", + "mean 174.212506 0.285714\n", + "std 501.116240 0.451763\n", + "min 0.000000 0.000000\n", + "25% 17.720000 0.000000\n", + "50% 36.340000 0.000000\n", + "75% 109.180000 1.000000\n", + "max 8329.960000 1.000000" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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stepcustomeragegendermerchantcategory
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" + ], + "text/plain": [ + " step customer age gender merchant category\n", + "count 25200 25200 25200 25200 25200 25200\n", + "unique 180 4061 8 4 48 14\n", + "top 2021-06-18 C1350963410 26to35 Female M1823072687 Transportation\n", + "freq 177 147 7984 14596 9192 15925" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.describe(include = 'O')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It can be noticed that the age column has varied values thus scaling is required. Also the gender column might have an unknown attribute as it has 4 unique values or it might be some human error which needs to be corrected. Also there are many values of the same attribute (female in gender and transportation in category) which might lead to skewed results without techniques for addressing overfitting." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Male' 'Female' 'Enterprise' 'Unknown']\n" + ] + } + ], + "source": [ + "#checking the attributes of gender\n", + "print(data.gender.unique())" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'corr': step customer age gender merchant category \\\n", + " step 1.000000 0.390616 0.014808 0.010605 0.107360 0.057168 \n", + " customer 0.605403 1.000000 1.000000 1.000000 0.508105 0.458672 \n", + " age 0.004728 0.205996 1.000000 0.019601 0.003319 0.001807 \n", + " gender 0.001423 0.086573 0.008237 1.000000 0.002983 0.003207 \n", + " merchant 0.046917 0.143268 0.004542 0.009716 1.000000 1.000000 \n", + " category 0.016173 0.083724 0.001601 0.006763 0.647370 1.000000 \n", + " amount 0.099530 0.470454 0.028884 0.043971 0.811395 0.805309 \n", + " fraud 0.067233 0.796446 0.038085 0.105551 0.944918 0.870595 \n", + " \n", + " amount fraud \n", + " step 0.099530 0.067233 \n", + " customer 0.470454 0.796446 \n", + " age 0.028884 0.038085 \n", + " gender 0.043971 0.105551 \n", + " merchant 0.811395 0.944918 \n", + " category 0.805309 0.870595 \n", + " amount 1.000000 0.450215 \n", + " fraud 0.450215 1.000000 ,\n", + " 'ax': }" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#correlation plot of features using theil's u method to correlate both categorical and numerical features \n", + "from dython.nominal import associations\n", + "associations(data, theil_u=True, figsize=(20, 20))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The correlation plot shows some expected and some weird properties. Both Customer and Merchant are highly correlated with the target column, this might mean that some merchants have repeatedly conned people and some customers have been repeatedly cheated. Also very strangely enough the customer column is 100% corelated with age which seems to be a mistake. Also amount of a purchase is moderately correlated to fraud against my initial thought. And the column age is very weakly correlated to fraud against the common beleif that old people are more likely to cheated" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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categoryfraud
7Leisure1.000000
13Travel0.993127
10Sports&Toys0.971569
6HotelServices0.935154
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5Home0.870317
4Health0.796992
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" + ], + "text/plain": [ + " category fraud\n", + "7 Leisure 1.000000\n", + "13 Travel 0.993127\n", + "10 Sports&Toys 0.971569\n", + "6 HotelServices 0.935154\n", + "8 OtherServices 0.908367\n", + "5 Home 0.870317\n", + "4 Health 0.796992\n", + "11 Technology 0.738318\n", + "0 Beauty&Wellness 0.605907\n", + "9 Restaurants&Bars 0.405405\n", + "2 Fashion 0.362500\n", + "12 Transportation 0.017582\n", + "1 Contents 0.000000\n", + "3 Groceries 0.000000" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[[\"category\", \"fraud\"]].groupby(['category'], as_index=False).mean().sort_values(by='fraud', ascending=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This shows that high spending categories like leisure, travel, sports and toys have been involved in fraud most number of times, with leisure purchases always being fraud. This means that fraud is likely to be nicely correlated to a combination of category and amount" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "sns.distplot(data['amount'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The distanceplot of amount is extremely skewed and the frequency of values starts becoming very less from around 1000" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As seen in the data description, the age column has object values of a particular age band, let us replace that with the upper limit of the groups " + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:670: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " iloc._setitem_with_indexer(indexer, value)\n" + ] + } + ], + "source": [ + "for i in range(0, len(data)):\n", + " if (data['age'].loc[i] == '36to45'):\n", + " data['age'].loc[i] = 45\n", + " if (data['age'].loc[i] == '26to35'):\n", + " data['age'].loc[i] = 35\n", + " if (data['age'].loc[i] == '56to65'):\n", + " data['age'].loc[i] = 65\n", + " if (data['age'].loc[i] == '19to25'):\n", + " data['age'].loc[i] = 25\n", + " if (data['age'].loc[i] == '46to55'):\n", + " data['age'].loc[i] = 55\n", + " if (data['age'].loc[i] == 'gt65'):\n", + " data['age'].loc[i] = 100\n", + " if (data['age'].loc[i] == 'Unknown'):\n", + " data['age'].loc[i] = 0\n", + " if (data['age'].loc[i] == 'lt18'):\n", + " data['age'].loc[i] = 18\n", + "data['age'] = data['age'].astype(int)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Feature Engineering" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "data['meramt'] = data.groupby('merchant')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "data['catamt'] = data.groupby('category')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "data['custamt'] = data.groupby('customer')['amount'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "for i in range(0,len(data)):\n", + " data['customer'].loc[i] = data['customer'].loc[i].replace(\"C\",\"\")\n", + " data['customer'].loc[i] = int(data['customer'].loc[i])\n", + "\n", + "for i in range(0,len(data)):\n", + " data['merchant'].loc[i] = data['merchant'].loc[i].replace(\"M\",\"\")\n", + " data['merchant'].loc[i] = int(data['merchant'].loc[i])" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "data['mercat'] = data.groupby('category')['merchant'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "data['custcat'] = data.groupby('category')['customer'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "data['catage'] = data.groupby('category')['age'].transform(lambda x: x.mean())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first three features are based on previous observations of dependence of amount with the other features. The last three features might seem funny but are based on correlation and might make sense mathematically.
\n", + "Let's revisualize the correlation plot" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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mrFlqdeaZh3VsuBs4eqIuHPCEetz9zwpft9bq8TemKeOO55V57ygtX/NbyWsLF/2kzneOVMYdz2vMpNwgRVy9LmzfXhOz52jy/Gz1v+1v5V5vfuKJemviBH324wpde8tNJfsTk5L02nvvasLcWfpw9kxdPaB/MMOuVkOHDdWC3PmaOWumWvmc276aNmuqjz+erPkLcjR69MuKi4uTJF162aWaOWumZs6aqYmTPtLpp58ezNCrpH1Kiubk5Cg7N1d/q+T8HTxsmLJzczXd59yvUbOmJk6ZomkzZ2rm3Lm6+957gxl2tfL0/QI/+v5jzV8wX6NHjy7p+5NOOkmTJk/Syp9W6pZbbwlm2NUmWsf+fvR/9OY/dNgQLcjN0cxZWYfIfZJ37I8qM/azNHNWliZOmqDTTz8tmKFXi8o+1/lq2qyZt+8XlOp7f48PZ9E89nnvBw6I2AKGw+HQIyMe0x39b9Cl6Z3VtWemTjy5Zak2l6SlqnlyC3VP6aDHBg7So4+PkCQlJCbqmhv66+oel6pXp66KiXGoa2ZmCLI4Mg6HQ8NHjNCA/v2VkZ6unj17quXJJ5dqk5qWpuTkZKWmpGjQwIF64vHH/T42EvRKO0dvDB5Q6esLF/2ktXlbNOeVf2jEbZdp2JgpkiS3u1jDX5+qNx4doBkv3aPpnyzV6vX5QYq6ejgcDj00fJj+PuAmXdmpizr37KHklqXHfuH2bXr+seF69403Su0vKirSi088pSszuuiGXlfoyuuvLXdsJEhNS1VycgulpqSVGt9lPfzww3rzzTeVltpB27dvV58+V0mS1q9frz5X9VHXLl318qiX9dRTTwYx+iPncDg0bMQI3dS/v7qkp6tHBedvSlqaWiQnq2NKih4dOFCPeb83f/7xh67r21eZXbsqs2tXXZKSojZt24YijSrx9H2yUlNSNWjgID3x+BMVtjvQ92nevu8jSdq2bZuGDR2m119/PYhRV59oHfv70f/Rm/+Bsd/Bm/uICts9/PBDevPNt7xjv7DM2L9aXbt008ujRkfg2K/4c11ZB/o+tVTf+3t8uIrmsc97P1DaYRUwjDHHBiqQw3VWm9b6de06bVi/XkX79mnmtOlKy8go1SYtI11TJ06WJC1bvER14uPVKKGxJCk2JkY1a9VSTEyMatWurYL8yPkhtk2bNlq3dq3Wr1+vffv2adq0aepUJvdOGRmaNHGiJGnx4sWqEx+vxgkJfh0bCc5vlay6dY6p9PXsr1bostS2MsaozaknqHDXXhVsLdSy1RvUPKmhmjkbqEZcrLq3O1vZX/0QxMirrlXr1lq/bp1+8479OdNmKCUjvVSb37ds1Ypl36loX1Gp/Vs2bdLK5cslSbt37dLa1WuU4EwMWuzVxTO+J0mSFnvP7cbec9vXRRddqKysmZKkiRMnqlOnTpKkRd8uUmFhoefvixbLmeQMUuRV07rM+Ttj2jSllzl/0zMyNNl77i9ZvFjx3nNfknbv3i1Jio2NVVxcnKy1wU2gGnTK6OTT94tVJ75OJX1/kbKysiSV7vstW7Zo2bJl5c6NSBGtY38/+j968++Uka5J3s90hzf2PdfIyB/7FX+uK6uyvvf3+HAVzWOf936gNL8KGMaYi4wxKyT94N1ubYz5V0AjO4QEp1OuvLyS7fy8PCWW+UEswemUa6NPG5dLCYlOFeTn650xb2ju558q5+svtHPHDn3+yadBi72qEp1ObfTJPS8vT4lOZ/k2GzeWbLtcLjkTE/069miQv7VQzkZ1S7adDeOVv7VQ+Vu2y9nwwP7EhnWVv7UwFCEesQRnovJ9+rDA5TqiIkTS8cfr1DPO0PdLllZneEGR6EzURp9z2+XKkzOx9DiuX7++CgsL5Xa7JUl5ea5y1whJ6nN1Hy1YEBm3EiU6ncrz6XtXJed+XplzPzHRk7fD4dDUrCx9uWiRPv3kEy1dsiQocVcnT9+XvbYdqu/Lvz9Eqmgd+/vR/9Gbv+dzje/Y9yf3ysb+VRE49iv+XOer4r53+n18OIv2sR/t7/3hwG3NUfkVifydgfGipM6StkiStXappPaVNTbG3GqM+cYY883WnYH54bCib3fZiqIxFbSyVvHx8UrrlK4u7VLU8S8Xqnbt2upx+aUBiTMQjjR3a61fxx4NKkrJGKOKMo24U7eSvj0ctY85Rs+++opeGPG4du3cWV2RBU1l4/tw21x44QXq0+cqPf3U09UbYIBU5dyXpOLiYvXs1k3tLrhArdu00cmnnBKIMAOquvo+UkXr2N+P/o/e/I8899LbB8b+M9UaX6BVte8jfVxE9divYF+0vfcDvvx+Com1dn2Zk8N9kLZjJI2RpLOanxiQK0e+yyVnUlLJdmJSkgryC0q3ycuTs4lPG6dTBQX5uqDdxfpt/Qb9vnWrJGnerNlqfe65mj55SiBCrXYul0tNfHJPSkoqdwuMKy9PTZo0Kdl2Op3KLyhQjRo1Dnns0cDZMF6uzdtLtl1bCpVQv472Fbnl2nJgf/6W7UpoEB+KEI9YQZ5LiT59mOB0alOZsX8wMbGxevbVVzRrylTNnz0nECEGxHXXX6e+V18tSVq6bJma+JzbTmeS8gtKj+OtW7cqPj5eMTExcrvdSkpylrpGnHbaaXr6mac1oP8N2rZtW1ByqCqXy6Ukn753VnLuJ5U59wsKSo+PHYWF+vLzz9U+NVWrfvopsEFXA0/f95UkLV22tIJr26H6vvz7QySJ9rFP/0dv/p7cPWsYlB/7/uTuLHWN9Iz9pzSg/40RMvavL3Pul/9c56vivvfkX9nnwnAWzWPfV7S+9wOV8XcGxnpjzEWSrDGmhjHmfnlvJwmV75cuU/PkFjq+WVPFxsWpa2YPLZg7r1Sb+fOy1bP35ZKks9u20c4dO7S5YJPyNm7U2W3bqFatWpKkv158kX5ZvTroORyppUuXqkVyspo2a6a4uDhlZmZq7ty5pdrMnTdPvXr3liS1bdtWO3bs0KaCAr+OPRp0OP90fbxgsay1WrLyV9U5ppYSGsTrrJbHa23eZq3P36o/9xVpxqfL1OH8yFqFf8WyZWrWormaNPWM/U6Z3bVwXrbfxw955in9snq1xr35VgCjrH7/HftfdevWXd26ddecOXPUq3cvSVLbtm2843tTuWM+//wLdevWVZLUu3dvzfGO9SZNmui1f7+qe++9T7/88kvwkqiiZUuXqrnP+ds9M1PZZc7f7HnzdLn33G/jc+43aNBAdeI9xbqaNWvqonbt9HOEXPc8fd9N3bp1K9P3bQ/S95+rW7dukvb3feQU68qK9rFP/0dv/p7ce6hbtx6aM2euenk/0x3e2Pd8NvSM/X/p3nv/EUFjf2yZvi//ua6s8n3vOfcr+1wYzqJ57PuK1vd+oDLGn6lVxphGkl6SlC7PTKY5ku621m451LGBmoEheZ4y8uCQwYqJcWjy+Al6ffS/dGW/ayRJE8a9J0l6ZMRjujilvfbu2atH739QK777TpJ0x733qEuP7ipyF+nH5Ss09KGB2vfnn9Ua347KJ6lUWWpamoYMGaKYmBiNHz9er4werX79+kmSxo0bJ0kaPmKEUlJStGfPHj1w//36zpt7RccGwtqskQH5dyXpvpEf6Kvvf9HvO3apYd3jdNfV6Sry3vPYt/NfZa3V8Nen6pPFq1S7ZpyevLO3zmrZVJKU++1KPfnWdLmLrXp3PFe3X5EWkBjP6/FQQP5dSbo4NUX3DXlUMY4YTZ0wQW+98qp6X+P5LcXE995Xw0aNNHbqxzr2uONkbbF279qtqzp1UcvTTtWbEz7Uqh9/VLH3gdb/eu4F/S8A9wJvLg7c+Jek4SOGKyWlvXd8P1gyvt9+5y099ODDKigoULNmzfTy6JdVr15dLV++Qvfec6/+/PNPPf3M0+ratYt+2+B5vG6Ru0g9M6v3NrJYBeaB4SlpaXrUe/5OGD9er44erb7ec/9977k/bMQItfee+w/df7++/+47nXraaXpu5Eg5HA45HA5lTZ+u0aNGBSTGogDfmOXp+/3Xtgd8+v5tPfTgQ2X6vp6WL19e0veNGzfW1GlTddxxx8kWW+3avUsZ6RnaWa23UgUj//Ad+6rwZr3qE/79H1jhnX9gH243fMRj3rG/9xBjf5TP2L/PO/afKjP23QEY+4F+36v4c93b77yjhx580Cf/0T59f4/+9H6+rez46hPd1/7YAF77IuG9f/W6dRF3V/bhmH9BSuTfj1SBtC9yI67f/CpgVEUgCxjhLpAFjEgQyAJGJAhkASMSBLqAEe4CVcCIBIEuYIS/aM8/at/2EeACRviL7ve9aL/2BbKAEQkoYESmSCxg+LUGhjGmolLddknfWGsjY+EIAAAAAAAQsfwtldeS1EbSKu/X2ZIaSLrJGPPPgEQGAAAAAADg5e9TSFpK6mCtLZIkY8yr8qyDkSGpum+gAwAAAAAgLLhtxN1pcdTydwbG8ZKO9dk+VlITa61b0h/VHhUAAAAAAIAPf2dgPCtpiTFmgTwr9LSX9KQx5lhJ8w52IAAAAAAAQFX5VcCw1r5pjJkp6TpJP8pz+8gGa+0uSQ8EMD4AAAAAAAC/n0Jys6S7JTWVtETSBZI+l9QhYJEBAAAAAAB4+bsGxt2Szpe0zlqbJqmtpE0BiwoAAAAAgDBQbM1R+eUPY0wXY8xKY8xqY8zDFbyeaozZboxZ4v0a4u+xR8LfNTD2Wmv3GmNkjKlprf3RGHNqdQQAAAAAAADCizEmRtIr8jx9dIOkr40xU621K8o0/cRa2+MIjz0s/s7A2GCMqSfpY0lzjTFTJG2syn8MAAAAAADC1l8krbbW/myt/VPSB5IuDcKxlfJ3Ec/LvX8dZoyZL6mupFlV/c8BAAAAAEDwGWNulXSrz64x1toxPtvHS1rvs71B0l8r+KcuNMYslWeSw/3W2uWHcexh8fcWkhLW2tyq/qcAAAAAAEQCt5/rRUQab7FizEGaVJS4LbO9SFJza+1OY0w3ee7aONnPYw+bv7eQAAAAAACA6LFBUjOf7aYqs5SEtbbQWrvT+/csSXHGmEb+HHskKGAAAAAAAICyvpZ0sjEm2RhTQ9LVkqb6NjDGOI0xxvv3v8hTY9jiz7FH4rBvIQEAAAAAAEc3a22RMeZOSbMlxUh6y1q73Bhzm/f11yRdIel2Y0yRpD2SrrbWWkkVHlvVmChgAAAAAABQCXeVV26IXN7bQrLK7HvN5++jJY3299iq4hYSAAAAAAAQ9ihgAAAAAACAsEcBAwAAAAAAhD3WwAAAAAAAoBLF1oQ6BHgxAwMAAAAAAIQ9ChgAAAAAACDsUcAAAAAAAABhjwIGAAAAAAAIeyziCQAAAABAJdws4hk2mIEBAAAAAADCHgUMAAAAAAAQ9gJ+C8kOuQP9X4StaL8/57weD4U6hJD6ZvozoQ4hpE7qdl+oQwipolAHEEI1Qh1AiB1nYkIdQkjtstE8+qNbzSifYb3LhjqC0IoLdQAhVqwoPwGAIIn2n7EBAAAAAKiUO8oLlOGEW0gAAAAAAEDYo4ABAAAAAADCHgUMAAAAAAAQ9lgDAwAAAACASrhZpDVsMAMDAAAAAACEPQoYAAAAAAAg7FHAAAAAAAAAYY81MAAAAAAAqITbhjoC7McMDAAAAAAAEPYoYAAAAAAAgLBHAQMAAAAAAIQ9ChgAAAAAACDssYgnAAAAAACVcIc6AJRgBgYAAAAAAAh7FDAAAAAAAEDYo4ABAAAAAADCHmtgAAAAAABQCdbACB/MwAAAAAAAAGGPAgYAAAAAAAh7FDAAAAAAAEDYYw0MAAAAAAAq4ZYJdQjwYgYGAAAAAAAIexQwAAAAAABA2KOAAQAAAAAAwh5rYAAAAAAAUAm3taEOAV7MwAAAAAAAAGEvogsYKSkpys7J0YLcXN1+++0Vthk6bJgW5OZq5qxZanXmmYd1bDhrn5KiOTk5ys7N1d8qiX/wsGHKzs3VdJ/ca9SsqYlTpmjazJmaOXeu7r733mCGXW0ubN9eE7PnaPL8bPW/7W/lXm9+4ol6a+IEffbjCl17y00l+xOTkvTae+9qwtxZ+nD2TF09oH8ww64WA0dP1IUDnlCPu/9Z4evWWj3+xjRl3PG8Mu8dpeVrfit5beGin9T5zpHKuON5jZmUG6SIq1/7lBTNzclRzkHG/5Bhw5STm6sZZcb/pClTND2Cx380X/ck6ZKUFM3Kydbc3AW6tZIcHh02VHNzF2jqrJk648xWpV5zOBz6OGuG/v3Wm8EIt9pdlNJek7LnaMqCbA24vfy1r8VJJ+qdSRP0xcoVus7n2idJQ599SvO++VLjZ2cFK9xqt7//5+Qu0C2V9P8jw4ZqTgX9n/3pp5o6e5Y+zsrSxGlTgxVytYnm3CXp4pT2mpo9T9MX5OjG22+rsM1DQ4do+oIcfTQzS6e3OpB/vxsGaNLsmZo0Z5auvfGGYIVcraL5fU+S2qWkaGZOtmYfYvzPzl2gKWXGf534eL306r+UlZ2tGdnz1Oacc4IVdrWJ9vc+wFfEFjAcDoeGjxihAf37KyM9XT179lTLk08u1SY1LU3JyclKTUnRoIED9cTjj/t9bDhzOBwaNmKEburfX13S09WjgvhT0tLUIjlZHVNS9OjAgXrMm/uff/yh6/r2VWbXrsrs2lWXpKSoTdu2oUjjiDkcDj00fJj+PuAmXdmpizr37KHkli1LtSncvk3PPzZc777xRqn9RUVFevGJp3RlRhfd0OsKXXn9teWODXe90s7RG4MHVPr6wkU/aW3eFs155R8acdtlGjZmiiTJ7S7W8Nen6o1HB2jGS/do+idLtXp9fpCirj77x/+N/furc3q6Mis591skJ6tDSooeGThQw33G/7V9+6qHd/y3j7DxH83XPcmTw9ARw3VL/wHqlp6hHj176qSTS5+/KWmpapGcrIyUVA0eOEiPPf5Eqdf733iD1qxeHcSoq8/+a99dA25S74wu6lLBtW/7tm16dthw/ff1N8odP+2jSbqz/41Birb6ORwODRkxXDf3H6DulfR/+zRP/3fy9v+wsv1/dV9d1q2bemf2DGLkVRfNuUue/AcNf0y3D7hBl2V0VteemTqxzNhvl5qq5skt1CO1g4YPGqRHnxghSWp5yinqfXUfXXPp5bqya3e179BBJ7RoEYIsjlw0v+9JB8b/Lf0HqEd6hrpXMv6bJyerc0qqhgwcpKE+4/+RoUP1SW6uunXsqMu6dI2494Bof+8DyjpkAcMYE2OMCbtybZs2bbRu7VqtX79e+/bt07Rp09QpI6NUm04ZGZo0caIkafHixaoTH6/GCQl+HRvOWpeJf8a0aUovE396RoYme3Nfsnix4r25S9Lu3bslSbGxsYqLi5ONsHu6WrVurfXr1um39etVtG+f5kyboZSM9FJtft+yVSuWfaeifUWl9m/ZtEkrly+XJO3etUtrV69RgjMxaLFXh/NbJatunWMqfT37qxW6LLWtjDFqc+oJKty1VwVbC7Vs9QY1T2qoZs4GqhEXq+7tzlb2Vz8EMfLqUXb8T6/C+I+NsPEfzdc9STq7TRutW7uuzLWvU6k2HTM6afLESZKkpYsXq058HTVOaCxJSnQ6ldqhgyZ88EHQY68OZ7ZprQ0+177Z02YotVMl176ionLHL/rqa23fvi1I0Va//f2/waf/O1bQ/x/79H+8T/9HsmjOXfKM/V99xv6sadOV1qn09SutU7qmTZosSVq2eInq1IlXo8aNldzyJC1bvER79+6V2+3WN19+qY6dO1X034StaH7fkzzj/1ef8Z9VyfifUsH4P/a443TeX/+ijz74UJK0b98+7SgsDHoOVRHt731AWYcsYFhr3ZIuDUIshyXR6dTGvLyS7by8PCU6neXbbNxYsu1yueRMTPTr2HCW6HQqzyd+VyW555XJPTHR84O6w+HQ1KwsfblokT795BMtXbIkKHFXlwRnovJ98i9wuY6oCJF0/PE69Ywz9P2SpdUZXsjlby2Us1Hdkm1nw3jlby1U/pbtcjY8sD+xYV3lb42sN3HJ//Ff0bkvecb/tKwsfbVokf4XYeM/mq97kpToTJQrzye3vDwlljn3E52Jcvnkn+9yKTHRk+cjQ4fo2SefUnFxZH14369xYqJcG32ufXkuJSRGVgG2Ksr2f74f/e/y6X/J6s13/6uJ06fpqr59gxFytYnm3CUpMdGpfJ+xn5+XV27sJyQ6S50f+S6XEpxOrV75k875y19Ut1491apVS5ekpSoxKSlYoVeLaH7fkzxjO8+Pa3/5z71ONTvhBG3dskVPPf+8JmXN0Ihnnlbt2rWDFnt1iPb3vnDhPkq/IpG/t5D8zxgz2hhziTHmnP1flTU2xtxqjPnGGPPNjp07qynUMv9HBfvKVpSNKd/KWuvXseGsKrlLUnFxsXp266Z2F1yg1m3a6ORTTglEmIFzkNz8VfuYY/Tsq6/ohRGPa1eAxmioVPStMMaoou9QRWMp3FUY82GO/8xu3XSxd/yfEkHjP5qve5JkKsjC3/xTO3TQli1btPz77wMWX6AdbFxHg6r0vyT17dVbvbr30C39B6jf9dfrvL/8JTCBBkA05y6pwoufv/n/smaN3n7t3xrz7li9+p93tPKHH+V2R9bH9mh+3/Pw49pXSf6xMTE648wz9f6776pXt+7as3uPbrkjstaAivb3PqAsfwsYF0lqJWm4pBe8X89X1thaO8Zae5619rw6xx1X9Sgr4HK51MSngp6UlKSC/NL387vy8tSkSZOSbafTqfyCAr+ODWcul0tJPvE7K8k9qUzuBQUFpdrsKCzUl59/rvapqQGNt7oV5LlK/fYkwenUpvyCgxxRWkxsrJ599RXNmjJV82fPCUSIIeVsGC/X5u0l264thUqoX0fOhnXl2nJgf/6W7UpoEB+KEKukovGf7+e572tHYaG+iLDxH83XPcn7G8Ukn9ySklRQ5tx35bnk9Mk/0elUQUG+zj3vPHVMT1fOp5/qxZdf1gUXXaTn/vli0GKvDgUul5xNfK59SU5tKvD/2hfpyvZ/oh/97/T2v6SS98CtW7Zo7uzZOrtN6yBEXT2iOXfJ+9tkn7GfmJRUbuznu/JKnR+JTqc2ea9xk8ePV58ePXVDn6tVuG2bfv1lbVDiri7R/L4nefo/6RDX/vw8VwWfe/PlcrmUn+fSMu+sk9lZWTrDZ3HrSBDt731AWX4VMKy1aRV8dQh0cAezdOlStUhOVtNmzRQXF6fMzEzNnTu3VJu58+apV+/ekqS2bdtqx44d2lRQ4Nex4WzZ0qVq7hN/98xMZZeJP3vePF3uzb2NT+4NGjRQnXjPD601a9bURe3a6ecIW9RnxbJlataiuZo0barYuDh1yuyuhfOy/T5+yDNP6ZfVqzXuzbcCGGXodDj/dH28YLGstVqy8lfVOaaWEhrE66yWx2tt3matz9+qP/cVacany9Th/NNDHe5hW1bm/O1Rwfif5+f4v7hdu4ha1Cqar3uS9N3SpWqR3EJNmzWt9NqXM2+uLu/dS5LUum1b7dyxQ5sKNumFZ59V+wsuVId27XTvXXfpi88+0wP3hN3yTge1fGnpa1/nzO7Knev/tS/SVdT/ORX0/2U+/b/D2/+1a9fWscceK0mqXbu2Lm5/iVat/CnoORypaM5d8oz95i1a6Hjv2O+S2UML5s4r1WbB3Gxl9rpcknR22zbasWOHNm/aJElq0LChJMnZpIk6dumsrKmR9SSWaH7fkzzjv3lyCx3vHf/dKhn/l1Yw/jdv2qS8vI1KPvFESdKFF1+sNatWBT2Hqoj29z6grFh/GhljEiU9KamJtbarMeYMSRdaa0P2LB63260hQ4Zo7NixiomJ0fjx47Vq1Sr169dPkjRu3DjNz8lRWlqachcu1J49e/TA/fcf9NhI4Xa79diQIXrbG/8Eb/x9vbm/P26cFuTkKDUtTTne3B/y5t44IUHPjRwph8Mhh8OhrOnTNT8nJ5TpHDa3263nhj6ml8e+rRhHjKZOmKCfV61S72s89/VOfO99NWz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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'corr': step customer age gender merchant category \\\n", + " step 1.000000 0.091561 0.081676 0.010605 0.218892 0.057168 \n", + " customer 0.091561 1.000000 0.002931 0.032947 0.006908 0.035071 \n", + " age 0.081676 0.002931 1.000000 0.115579 -0.020316 0.032859 \n", + " gender 0.001423 0.032947 0.115579 1.000000 0.026731 0.003207 \n", + " merchant 0.218892 0.006908 -0.020316 0.026731 1.000000 0.449156 \n", + " category 0.016173 0.035071 0.032859 0.006763 0.449156 1.000000 \n", + " amount 0.099530 -0.000815 -0.011677 0.043971 -0.082459 0.805309 \n", + " fraud 0.067233 0.026313 -0.018114 0.105551 -0.150286 0.870595 \n", + " meramt 0.109209 0.001455 -0.009584 0.053934 -0.101626 0.992498 \n", + " catamt 0.107599 0.000476 -0.009397 0.050372 -0.090733 1.000000 \n", + " custamt 0.071864 -0.001731 -0.024820 0.093464 -0.135225 0.581235 \n", + " mercat 0.106171 -0.006412 -0.003669 0.026906 0.449156 1.000000 \n", + " custcat 0.099459 0.035071 -0.011782 0.060799 -0.082126 1.000000 \n", + " catage 0.098104 -0.012575 0.032859 0.042876 -0.050149 1.000000 \n", + " \n", + " amount fraud meramt catamt custamt mercat \\\n", + " step 0.099530 0.067233 0.109209 0.107599 0.071864 0.106171 \n", + " customer -0.000815 0.026313 0.001455 0.000476 -0.001731 -0.006412 \n", + " age -0.011677 -0.018114 -0.009584 -0.009397 -0.024820 -0.003669 \n", + " gender 0.043971 0.105551 0.053934 0.050372 0.093464 0.026906 \n", + " merchant -0.082459 -0.150286 -0.101626 -0.090733 -0.135225 0.449156 \n", + " category 0.805309 0.870595 0.992498 1.000000 0.581235 1.000000 \n", + " amount 1.000000 0.450215 0.811395 0.805309 0.470454 -0.162678 \n", + " fraud 0.450215 1.000000 0.529481 0.498312 0.600583 -0.231696 \n", + " meramt 0.811395 0.529481 1.000000 0.992498 0.472516 -0.200491 \n", + " catamt 0.805309 0.498312 0.992498 1.000000 0.453809 -0.202007 \n", + " custamt 0.470454 0.600583 0.472516 0.453809 1.000000 -0.157477 \n", + " mercat -0.162678 -0.231696 -0.200491 -0.202007 -0.157477 1.000000 \n", + " custcat 0.010933 0.579601 0.013475 0.013577 0.291554 -0.182845 \n", + " catage -0.230294 -0.428122 -0.283825 -0.285970 -0.286136 -0.111651 \n", + " \n", + " custcat catage \n", + " step 0.099459 0.098104 \n", + " customer 0.035071 -0.012575 \n", + " age -0.011782 0.032859 \n", + " gender 0.060799 0.042876 \n", + " merchant -0.082126 -0.050149 \n", + " category 1.000000 1.000000 \n", + " amount 0.010933 -0.230294 \n", + " fraud 0.579601 -0.428122 \n", + " meramt 0.013475 -0.283825 \n", + " catamt 0.013577 -0.285970 \n", + " custamt 0.291554 -0.286136 \n", + " mercat -0.182845 -0.111651 \n", + " custcat 1.000000 -0.358553 \n", + " catage -0.358553 1.000000 ,\n", + " 'ax': }" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from dython.nominal import associations\n", + "associations(data, theil_u=True, figsize=(20, 20))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see our features have a nice correlation with the target" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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rJD8AIGOpBr+ZXWhmj5vZNjO7usl+M7Nr4v0Pm9naMZz722bmZrYozc8wFqNV/NzjBwBkLbXgN7OipE9LWi9pjaRLzWxNw2HrJa2OvzZKujbJuWa2XNI7JT2TVvvHoxIvyTticB9d/QCAnEiz4j9X0jZ33+7ug5JulrSh4ZgNkm70qrskzTezJQnO/QtJv6ucPfBuqOJv2M4CPgCAvEgz+JdK2ln3ele8LckxLc81s4slPevuD4VucKda3uMvMI8fAJAPPSm+d2PhK42s0Fsd03S7mc2U9HFJPzXqLzfbqOrtA61YsWK0w4NodY+/9pLpfACArKVZ8e+StLzu9TJJuxMe02r7GZJWSXrIzHbE2+83s1Maf7m7X+/u69x9XX9/f4cfJZnWo/oZ3AcAyIc0g/9eSavNbJWZ9Um6RNKmhmM2SbosHt1/vqSD7r6n1bnu/gN3X+zuK919pap/IKx19+dS/ByJjT6qv+tNAgDgBKl19bt72cyuknSbpKKkG9x9q5ldEe+/TtJmSRdJ2iZpQNLl7c5Nq62htB7VX/1OxQ8AyFqa9/jl7ptVDff6bdfV/eySrkx6bpNjVnbeynBqXf0jHtIzNJ2P4AcAZIuV+wKqBXurefx09QMAskbwB1RpNY+fp/MBAHKC4A9o9FH93W4RAAAnIvgDYh4/ACDvCP6AWo3qLzKPHwCQEwR/QK1G9Rtd/QCAnEgU/GZ2i5n9tJnxh0IbUctR/dXvTOcDAGQtaZBfK+l9kp4ws0+a2VkptmnCGr7Hf+L22h8CFYIfAJCxRMHv7v/u7r8kaa2kHZJuN7M7zexyM+tNs4ETScsFfHg6HwAgJxJ33ZvZSZI+KOlXJT0g6a9U/UPg9lRaNgHR1Q8AyLtES/aa2T9KOkvSFyX9p/hBOpL092a2Ja3GTTSt1+qPK35KfgBAxpKu1f+5eO38IWY2zd2Pu/u6FNo1IUWjrNVP7gMAspa0q/9/Ndn2/ZANmQwqLbr6jafzAQByom3Fb2anSFoqaYaZvU7Dy9DPlTQz5bZNOKM9nY/gBwBkbbSu/nepOqBvmaRP1W0/LOljKbVpwhptcB9d/QCArLUNfnf/gqQvmNl73P2WLrVpwhq6x9+w3cxkouIHAGRvtK7+97v730laaWa/1bjf3T/V5LQpqxLnemPFL1Xn8pP7AICsjdbVPyv+PjvthkwGrUb1S9XufqbzAQCyNlpX/2fi73/QneZMbK1G9de20dUPAMha0of0/KmZzTWzXjP7ppntM7P3p924iabVqH6pFvxdbhAAAA2SzuP/KXc/JOndknZJeoWk30mtVRNUrSu/WcVvxuA+AED2kgZ/7UE8F0n6sru/lFJ7JrRKi6fzSVKRih8AkANJl+z9JzN7TNIxSR82s35JL6fXrIkpajOqn4ofAJAHSR/Le7WkCyStc/eSpKOSNqTZsIkoinxosZ5G1el8BD8AIFtJK35JeqWq8/nrz7kxcHsmtIq7ii2Sn8F9AIA8SPpY3i9KOkPSg5Iq8WYXwX+CasXfKviHR/0DAJCVpBX/OklrnL7qtipR+4qfywcAyFrSUf2PSDolzYZMBhV3FVtW/HT1AwCyl7TiXyTpUTO7R9Lx2kZ3vziVVk1QUeQqtKz4GdUPAMhe0uD//TQbMVm0G9xnLNkLAMiBRMHv7neY2WmSVrv7v5vZTEnFdJs28USu1tP5TDydDwCQuaRr9f8XSV+V9Jl401JJt6bUpgmr7aj+gg2t7AcAQFaSDu67UtIbJR2SJHd/QtLitBo1UY02qj+KutwgAAAaJA3+4+4+WHsRL+JD+dqg4u3n8TOdDwCQtaTBf4eZfUzSDDN7p6R/kPRP6TVrYopGq/gJfgBAxpIG/9WS9kr6gaRfk7RZ0n9Pq1ETVcXFkr0AgFxLOqo/MrNbJd3q7nvTbdLE1fYhPczjBwDkQNuK36p+38z2SXpM0uNmttfMPtGd5k0sUZt7/MzjBwDkwWhd/b+h6mj+c9z9JHdfKOk8SW80s99Mu3ETTdtR/QW6+gEA2Rst+C+TdKm7P1Xb4O7bJb0/3oc67Sr+glVvBQAAkKXRgr/X3fc1bozv8/em06SJa9Sn83W5PQAANBot+AfHuW9KqrjaP6SHih8AkLHRRvW/1swONdlukqan0J4JLYpcxZaj+hncBwDIXtvgd3cexDMGoy7ZS+4DADKWdAEfJNB+Oh/z+AEA2SP4A2o7qr9AVz8AIHsEf0Btu/oluvoBAJkj+ANqO6q/YDydDwCQOYI/oFFH9UfdbQ8AAI0I/oDaj+pncB8AIHsEf0Dtl+ytrtxH+AMAskTwB9Su4rf4DwJyHwCQJYI/oHYVf+3ePxU/ACBLqQa/mV1oZo+b2TYzu7rJfjOza+L9D5vZ2tHONbM/io990Mz+zcxOTfMzjEXUZlR/reIn+AEAWUot+M2sKOnTktZLWiPpUjNb03DYekmr46+Nkq5NcO6fuftr3P1sSd+Q9Im0PsNYVdqN6o//IGBkPwAgS2lW/OdK2ubu2919UNLNkjY0HLNB0o1edZek+Wa2pN257l7/0KBZUn6edluJvO3T+SQxlx8AkKk0g3+ppJ11r3fF25Ic0/ZcM/tjM9sp6ZfUouI3s41mtsXMtuzdu3fcH2IsIncV24zql6QKwQ8AyFCawd8sARtTr9Uxbc9194+7+3JJN0m6qtkvd/fr3X2du6/r7+9P2OTOjPZ0vmq7utIUAACaSjP4d0laXvd6maTdCY9Jcq4kfUnSezpuaSCRj97Vz+A+AECW0gz+eyWtNrNVZtYn6RJJmxqO2STpsnh0//mSDrr7nnbnmtnquvMvlvRYip9hTCIfDvhGhaFR/V1sEAAADXrSemN3L5vZVZJuk1SUdIO7bzWzK+L910naLOkiSdskDUi6vN258Vt/0sx+TFIk6WlJV6T1GcaqOqq/1UN6qt+p+AEAWUot+CXJ3TerGu71266r+9klXZn03Hh7brr2G0VtRvUPzeOn5AcAZIiV+wKqJBjVzzR+AECWCP6ARns6n0TFDwDIFsEfUPtR/UznAwBkj+APqO3gPtbqBwDkAMEfULuH9DCPHwCQBwR/ILV79y3n8ReYxw8AyB7BH0htDf5WXf1GxQ8AyAGCP5BKreJvUfLX/iCoUPIDADJE8AdSq+RbTefrKVYvdblC8AMAskPwB1Kr5Ft19ffEfxCUI5bwAQBkh+APpJbnrbr6a8FPVz8AIEsEfyDDg/ua7y8OVfwEPwAgOwR/ILV7/C0r/to9foIfAJAhgj+Q4Xn8o9zjr3CPHwCQHYI/kMpoo/q5xw8AyAGCP5DRRvVzjx8AkAcEfyCjjeo3MxULxjx+AECmCP5Ahrv6Wx/TUzDm8QMAMkXwB1IZZXCfVAt+Kn4AQHYI/kDcEwR/saAKXf0AgAwR/IGMNqq/to+ufgBAlgj+QOjqBwBMBAR/ILVCvl3F38OofgBAxgj+QBKN6i8WWMAHAJApgj+QJF393OMHAGSN4A8kSjC4j3v8AICsEfyBRKMs2StVg5+ufgBAlgj+QGr3+G2UefwlBvcBADJE8AeSdFR/hXv8AIAMEfyBJBnVX+QePwAgYwR/IFGSBXyKzOMHAGSL4A+kNmivfVd/gel8AIBMEfyBVJI8pIdR/QCAjBH8gUQJKv5i0RS5CH8AQGYI/kBqWd6+4q9e7sEy3f0AgGwQ/IEkWqs/7g0g+AEAWSH4A0kyqr92G+B4udKVNgEA0IjgDyTJqP7eYi34qfgBANkg+ANJMqq/WLvHXyH4AQDZIPgDSTKqn3v8AICsEfyB1Jbi7UkQ/HT1AwCyQvAHUo6773vaDOuv7aPiBwBkheAPZKjiL44+qp/gBwBkheAPpBQ/fKe30KbirwV/hel8AIBsEPyBDHf1t386n0TFDwDIDsEfSCnB4L4ig/sAABkj+AMpVyIVCyZrM4+/dhuA4AcAZIXgD6QSedtqX6o+nU+iqx8AkB2CP5BSxdXb7gk9YgEfAED2CP5AylHUdmCfNPxYXrr6AQBZIfgDKVV8KNhbYR4/ACBrBH8g5Uo09PS9VooFU8GYxw8AyE6qwW9mF5rZ42a2zcyubrLfzOyaeP/DZrZ2tHPN7M/M7LH4+K+Z2fw0P0NS5chH7eqXquFPxQ8AyEpqwW9mRUmflrRe0hpJl5rZmobD1ktaHX9tlHRtgnNvl/Rqd3+NpB9J+mhan2EsSpWo7ap9NT2FAsEPAMhMmhX/uZK2uft2dx+UdLOkDQ3HbJB0o1fdJWm+mS1pd667/5u7l+Pz75K0LMXPkFi5kqzi7ykYg/sAAJlJM/iXStpZ93pXvC3JMUnOlaT/LOlfmv1yM9toZlvMbMvevXvH2PSxK0fRqIP7pOpcfip+AEBW0gz+ZuWvJzxm1HPN7OOSypJuavbL3f16d1/n7uv6+/sTNLcz1Xn8SSr+go5XCH4AQDZ6UnzvXZKW171eJml3wmP62p1rZr8s6d2S3u7ujX9MZKI6jz/JPX4qfgBAdtKs+O+VtNrMVplZn6RLJG1qOGaTpMvi0f3nSzro7nvanWtmF0r6PUkXu/tAiu0fk+o8/gQVP139AIAMpVbxu3vZzK6SdJukoqQb3H2rmV0R779O0mZJF0naJmlA0uXtzo3f+q8lTZN0e/xAnLvc/Yq0PkdS5UqkmX2jX85iwXS8zDx+AEA20uzql7tvVjXc67ddV/ezS7oy6bnx9jMDNzOIpPP4e5nOBwDIECv3BZJkyV4pXsCHwX0AgIwQ/IEkWbJX4h4/ACBbBH8g1a7+ZBU/C/gAALJC8AdSXbI32Tx+Kn4AQFYI/kDKFR967G47dPUDALJE8AfCAj4AgImA4A+kHCVdstdYshcAkBmCP5By4ul81Xv8OVlpGAAwxRD8gZTGMJ1PEnP5AQCZIPgDSbpyX209f+7zAwCyQPAH4O6qRMm6+gl+AECWCP4ASpXq/fpkg/uql5xFfAAAWSD4AyhH1RBPtHJfkYofAJAdgj+AWsXfk2jlPgb3AQCyQ/AHUI5DvDfRAj7VY6j4AQBZIPgDKEdxxT+G6Xzc4wcAZIHgD6BUq/gTLeBTC/5Kqm0CAKAZgj+AcmUMFT/T+QAAGSL4AxjLqP6+nuoxxwap+AEA3UfwBzA0jz/BqP7Z03okSXuPHE+1TQAANEPwBzDc1T/65Zw1rUfFgun5Qy+n3SwAAEYg+AMoDXX1j17xF8zUP3uanj9ExQ8A6D6CP4DyUFd/ssu5eO40vXCY4AcAdB/BH0BtAZ9ignv8krR4znS9QFc/ACADBH8ApSj5Q3okKn4AQHYI/gBqFX+SwX2SdPKc6Xrp6CBz+QEAXUfwBzC0ZG/Crv6T506TxJQ+AED3EfwBDA3uS1jxL46Dnyl9AIBuI/gDKI9hOp9UHdwnSS8wpQ8A0GUEfwClcUznk6QXDlPxAwC6i+APYHhwX7KK/6RZ01i9DwCQCYI/gNp0vqTBXyyYFs3uo6sfANB1BH8AtYo/aVe/JJ08d7qeZy4/AKDLCP4Ahh/Sk6zil6TFc6axeh8AoOsI/gBqD+lJOp1PkhbPnc7qfQCAriP4Axiq+BMu4COxeh8AIBsEfwBjfUiPNDylj9X7AADdRPAHUIpcvUWT2Rgq/tpcfu7zAwC6iOAPoFyJ1DOGEf3S8Op9ew4S/ACA7iH4AyhVfEwj+iXpzMWz1Vcs6IFn9qfUKgAARiL4AyhH0ZhG9EvS9N6i1p42X3c++WJKrQIAYCSCP4Byxcc0or/mDWcs0qN7Dmn/0cEUWgUAwEgEfwClio+54pekN5xxktylu5+i6gcAdEdP1g2YDMpRNKapfF+6+5mh8/qKBX3+zh166WhJkvS+81ak0kYAACQq/iDK4xjcJ0k9hYJWLpqpJ/ceTaFVAACMRPAHUKpEY3pAT70z+mdr7+HjOnSsFLhVAACMRPAHUI7GV/FL0un9syVJ2/cdCdkkAACaIvgDqAb/+C7lknnTNb23oKf2DQRuFQAAIxH8AZQrkXrHMZ1PkgpmOm3hLO3Yx31+AED6CP4Axju4r2bVolnae+S4jhwvB2wVAAAjEfwBlMaxcl+9lYtmSRJVPwAgdQR/AONdua/m1PnT1Vs0PfUiwQ8ASFeqwW9mF5rZ42a2zcyubrLfzOyaeP/DZrZ2tHPN7BfMbKuZRWa2Ls32J1WqROMe3CdV5/OvWDiTih8AkLrUgt/MipI+LWm9pDWSLjWzNQ2HrZe0Ov7aKOnaBOc+IunnJH03rbaPVTly9XZwj1+q3ud/7uDLOjjAfH4AQHrSrPjPlbTN3be7+6CkmyVtaDhmg6QbveouSfPNbEm7c939h+7+eIrtHrNyJVLPOBfwqVm5aJZc0r07XgrTKAAAmkgz+JdK2ln3ele8LckxSc7NjVKHo/olafmCmSqa6b5n9gdqFQAAI6UZ/M2S0BMek+Tc9r/cbKOZbTGzLXv37h3LqWNWjsa/ZG9Nb7GgJfOn6/6nCX4AQHrSDP5dkpbXvV4maXfCY5Kc25a7X+/u69x9XX9//1hOHbNO5/HXLF84Uw/vOqhyJQrQKgAARkoz+O+VtNrMVplZn6RLJG1qOGaTpMvi0f3nSzro7nsSnpsbpUpn8/hrViyYqWOlih577nCAVgEAMFJqwe/uZUlXSbpN0g8lfcXdt5rZFWZ2RXzYZknbJW2T9FlJH253riSZ2c+a2S5JF0j6ZzO7La3PkFQ56mwef82KhTMlSQ/sPNDxewEA0ExPmm/u7ptVDff6bdfV/eySrkx6brz9a5K+Fralnal29Xf+N9T8mb1aNHuaHnh6vz5w/mkBWgYAwIlYuS+A6pK9nVf8Zqa1K+brfkb2AwBSQvB3qBK53KVigK5+SVp72gLteHFALx0dDPJ+AADUI/g7VIpH4IcY3CdJr1s+X5L0AFU/ACAFBH+HylF1eYEQg/sk6TXL5quvp6DvPbEvyPsBAFCP4O9Qbc59iMF9kjSjr6h3vvJkfePh3cznBwAER/B3qFSpVvwhBvfVbDj7VO07Mqj/2EbVDwAIi+DvUGWoqz/cpXzrjy3WvBm9+vqDY1qsEACAURH8HSoNdfWHq/j7egq66MeX6Latz2lgsBzsfQEAIPg7VBvcF7KrX5J+5uxTNTBY0a0PUPUDAMJJdeW+qWBocF+grv4v3f2MJCly1/IFM/Q/bn1Ej+4+pDWnzpUkve+8FUF+DwBgaqLi71Aag/skqWCmD75hlU6dP11fuudp/XDPoaDvDwCYmgj+DpWjsBV/vRl9RV3+xlVaMm+GvrJlp/YdPh78dwAAphaCv0O1ij/k4L5603uL+qXzVqhYMN10z9MM9gMAdITg71A58JK9zcyf2af3nrNcLxw6rj+77fHUfg8AYPIj+DsUesneVlYvnqO1KxboS3c/o31H6PIHAIwPwd+hUuAle9t50ysWabAS6Qt37kh0/Oe+t10bb9yif354j14uVdJtHABgQmA6X4fKKY3qb2bxnOl615pT9IU7d+jX3nKGZk8b+Y+vNh3w2QPH9Dff3qZiwfRvjz6vJfOm68NvPVMfuOC01NsJAMgvKv4OpTmqv5kPvfUMHXq5rJvuerrlMZXIdesDz2rWtB5dfeFZ+pmzl2rPwZe15emXutJGAEB+EfwdSmsefyuvXT5fb35Fv/7mO0/qwMBg02Pu2v6inj1wTO9+zRLNnNajc1Yu0GkLZ+pbP3yBWQEAMMUR/B0aqvi7cI+/5mMXnaXDL5d0zTe3jdh3YGBQtz/6vH7s5Dn68aXzJElmpgtffYoOHy/rc997qmvtBADkD8HfoaF5/CmP6q931ilz9d5zVujG7+/Q9r1Hhra7u77+4G65XBeffarMhtt02kmztGbJXH3mjieZFQAAUxiD+zpUTnkBn0a1wXsrT5qpQsF06Wfv0qXnrlD/7Gm6/5n9evz5w7rox5dowcy+Eee+61Wn6JpvPaFrvvmE/nDDq7vSXgBAvlDxd6jbg/tq5kzv1S+du0KHXy7rb779pP7i33+kW+5/VssWzNAFp5/U9Jz+OdN0yTnL9aW7n9FT+452tb0AgHwg+Ds0WK4Gf19P9y/l6pPn6NfftlpnLJ6tOdN79XOvW6pf+YlVKra57fCRd6xWX09B/5cVAAFgSqKrv0MHBkoqmDSnyZz6bpg3o1cfOD/53PzFc6brV990uq755hP61Wf263UrFqTYOgBA3lDxd+jAsUHNm9GrQhcH93Vq45tP16LZffo///KY3D3r5gAAuojg79D+gVLTgXR5Nntajz7y9tW656mX9K3HXsi6OQCALiL4O3RwoKR5M3uzbsaYXXLuCq1aNEt/8q+PKYqo+gFgqiD4O7R/YHDCVfxS9THCv/62M/Wj54/ozidfzLo5AIAuIfg7dGCgpPkzJl7FLyme79+rm+5uve4/AGByYVR/hw4eK2n+BKr4awsA1bz61Hm6betzuu47T2rujF6977wVGbUMANANVPwdGCxHOnK8rPkT8B5/zTmrFipy8eQ+AJgiCP4OHDxWkiQtmMDBv2j2NJ3ZP1v3PPXS0GJEAIDJi+DvQO2xuPMmUFd/M289q1+HXy7r6w8+y7x+AJjkCP4OHJgEFb8knb5otn7yrMV6YOcB3fj9p/XDPYdYyx8AJikG93Vg/9FqxT9/xsSu+CXpbWct1o4Xj+p/bto6tO2Db1ipq9efpem9xQxbBgAIieDvQK3in8iD+2oKZnr/eadp4aw+Tesp6O6nXtLn79yhu7a/qFs+9AbNyuhZBACAsPi/eQdq9/gnQ/BL0vTeon7mdUslSet/fInOP32hrvi7+/WVLTt1+RtXZdw6AEAIBH8HDgyU1FMwzZ5E1XDjPP8VC2fq/31rm3qLBb1/DE8BBADkE4P7OrB/oKT5M3tlNnGezDdWbzxzkV46OqjH9hzKuikAgAAI/g4cPDY4oVbtG481S+Zq/sxe/cc21vMHgMmA4O/A/qMTd53+pIoF0wWnn6QdLx7VI88ezLo5AIAOEfwdODDB1ukfr3NWLlRfT0F/+x9PZd0UAECHCP4OHBgYnDQj+tuZ3lvU609boH96aLeeP/Ry1s0BAHSA4O/AgYHShF+1L6k3nH6SKu668fs7sm4KAKADBP84vVyq6FipMiW6+iXppNnT9M5Xnqyb7n5GR4+Xs24OAGCcCP5xOjiJVu1L6tfecoYOHivpt//hIUURD/MBgIlo8qw802UHBuLgnwTr9Cf1+HOHtf5Vp2jzI8/p8s/fqzev7lexYBoYLOvlcqSPvH21ioXJu6YBAEwGBP847Z9ky/Um9cYzF2nvkeO640d7dceP9p6w7xsP79aH3nKGfm7tMv4AAICcIvjHaajin2LBb2a6+LVLdfqi2TpyvKxyJdLMvuq/Ro89f1i/89WH9dX7dukvLzlbS+bNyLi1AIBGBP84DT+gZ+p09dcUC6bXLp8/Yvun3vta3XL/s/rE1x/R+r/6nj66/iy9Z+0y9RQZSgIAeUHwj9PTLw1I0pSZzpeEmennX79Ma1fM12//w0P6vVt+oM98d7vevLpf/XOmace+o3pw5wEdL0ea1lPQupULddkFp+mVS+Zm3XQAmDJSDX4zu1DSX0kqSvqcu3+yYb/F+y+SNCDpg+5+f7tzzWyhpL+XtFLSDkm/6O770/wcjfYfHdTfff9pveOVi4e6uXHik/3es3aZ1iyZq+/8aK++fM8zOl6ONLOvqOULZmrhrD69XKroH7bs1JfveUZL5k3XK5fM1QfOP01L5k/XknkzNHd6z6R++BEAZCW11DKzoqRPS3qnpF2S7jWzTe7+aN1h6yWtjr/Ok3StpPNGOfdqSd9090+a2dXx699L63M0c90dT+rIYFm/866zuvlrJxQz05pT52nNqfMkScfLFfUVCyeE+cBgWfc/c0Bbdx/Utx97Qd967IWhfbP6ilp98hydt2qhzjt9oV5/2kLNa3gugrurVHEVTNxOAICE0ixXz5W0zd23S5KZ3Sxpg6T64N8g6UZ3d0l3mdl8M1uiajXf6twNkt4an/8FSd9RF4N/z8Fj+vydO/Szr1uqHztlTrd+7YQ3rac4YtvMvh79xJmL9BNnLtLA8bL2Hjmug8dKOnispAPHStq9/5g+972n9JnvbpdJOnX+DE3rLahccb10dFBH4oWECiYtmTdDqxbN0quWztWaJXO1bMFMLZ4zTZI0WIl0YGBQ+49W3/fQsZIid1UiV+RS5K4oclW8+roSRTo2GGlgsKyjgxUdGyyrWDBN6ylq4aw+LZrdp/4507Ro9jT1FAuKIlc5qr1f9efpPQXNm9GrufHX9J4T/zCp/QFkkgoFU8Gkgln1qyCZTI0dHs36Pxp7RZofM/p5nahErnIUxd9d7lJPwVSsfZmpkGCWh3v13MiH/7m4S67hNSMs/oS19y5Y2M8CTAVpBv9SSTvrXu9Staof7Zilo5x7srvvkSR332Nmi0M2ejSfuWO7Inf95jte0c1fO+nNnNaj06aN/NexVIn0zEsDemrfUR0YGByq8JctmKHpvUX1FCwO9pKe2ndU33/yRVW8s8WFTFJfT0HTegrq6ymot1iQe/UPiIHBsl4uRR29/0TRLE/He2nNhv8YKJgNhbs3hPx4nPAHBn8DYII6a8lc3fKhN3Tld6UZ/M3+E2z8T7vVMUnObf/LzTZK2hi/PGJmj4/l/NGs+N9tdy+StC/k75tiuH6d4xp2jmvYGa7fGDwqyT48YnMn1/C0VjvSDP5dkpbXvV4maXfCY/ranPu8mS2Jq/0lkl5QE+5+vaTrx9/88TOzLe6+LovfPRlw/TrHNewc17AzXL/OpXUN0xwRda+k1Wa2ysz6JF0iaVPDMZskXWZV50s6GHfjtzt3k6Rfjn/+ZUlfT/EzAAAwqaRW8bt72cyuknSbqlPybnD3rWZ2Rbz/OkmbVZ3Kt03V6XyXtzs3futPSvqKmf2KpGck/UJanwEAgMkm1Uno7r5Z1XCv33Zd3c8u6cqk58bbX5T09rAtDS6TWwyTCNevc1zDznENO8P161wq19C8wxHQAABg4mDVEwAAphCCPyAzu9DMHjezbfGqgoiZ2Q1m9oKZPVK3baGZ3W5mT8TfF9Tt+2h8HR83s3fVbX+9mf0g3neNTZHVW8xsuZl928x+aGZbzewj8XauYUJmNt3M7jGzh+Jr+Afxdq7hGJhZ0cweMLNvxK+5fmNgZjviz/6gmW2Jt3X3GlZXy+Kr0y9VByE+Kel0VacjPiRpTdbtysuXpDdLWivpkbptfyrp6vjnqyX9Sfzzmvj6TZO0Kr6uxXjfPZIuUHWth3+RtD7rz9al67dE0tr45zmSfhRfJ65h8mtokmbHP/dKulvS+VzDMV/H35L0JUnfiF9z/cZ2/XZIWtSwravXkIo/nKElit19UFJtmWFIcvfvSnqpYfMGVZddVvz9Z+q23+zux939KVVnfZwbr9sw192/79V/82+sO2dSc/c9Hj/Ayt0PS/qhqitccg0T8qoj8cve+MvFNUzMzJZJ+mlJn6vbzPXrXFevIcEfTqvlh9HaCcsvS6otv9xuKeddTbZPKWa2UtLrVK1YuYZjEHdTP6jqwl+3uzvXcGz+UtLvSqpft5rrNzYu6d/M7D6rrjArdfka8kzZcDpeZhhDUlvKeaIzs9mSbpH0G+5+qM1tPa5hE+5ekXS2mc2X9DUze3Wbw7mGdczs3ZJecPf7zOytSU5psm3KXr86b3T33VZ9zsztZvZYm2NTuYZU/OEkWaIYJ3o+7rKSnbj8cqtruSv+uXH7lGBmvaqG/k3u/o/xZq7hOLj7AVWf7HmhuIZJvVHSxWa2Q9VbmW8zs78T129M3H13/P0FSV9T9TZxV68hwR9OkiWKcaJWyy9vknSJmU0zs1WSVku6J+4CO2xm58cjWC/TFFmyOf68fyvph+7+qbpdXMOEzKw/rvRlZjMkvUPSY+IaJuLuH3X3Ze6+UtX/v33L3d8vrl9iZjbLzObUfpb0U5IeUbevYdYjHCfTl6rLD/9I1ZGXH8+6PXn6kvRlSXsklVT9a/VXJJ0k6ZuSnoi/L6w7/uPxdXxcdaNVJa2L/0N5UtJfK16EarJ/SfoJVbvyHpb0YPx1EddwTNfwNZIeiK/hI5I+EW/nGo79Wr5Vw6P6uX7Jr9vpqo7Sf0jS1lpOdPsasnIfAABTCF39AABMIQQ/AABTCMEPAMAUQvADADCFEPwAAEwhBD+AoMzsYwHf62wzuyjU+wEg+AGEFyz4JZ2t6noFAAIh+AGcwMwuM7OHrfrc+i+a2efN7Ofr9h+Jvy8xs+/GzxV/xMzeZGaflDQj3nZTfNyt8QNJttY9lERmdsTM/iTe9+9mdq6ZfcfMtpvZxfEKmH8o6b3x+723y5cCmJRYwAfAEDN7laR/VPVBIvvMbKGkT6m6SttX42OOuPtsM/tvkqa7+x+bWVHSTHc/XNtf954L3f2leJnceyW9xd1fNDOXdJG7/4uZfU3SLFUf+bpG0hfc/Wwz+6Ckde5+VRcvAzCp8XQ+APXeJumr7r5PkuLAbnXsvZJuiB8edKu7P9jiuP9qZj8b/7xc1fXGX5Q0KOlf4+0/kHTc3Utm9gNJKzv9IACao6sfQD3TyMd7lhX/vyJ+IEifJLn7dyW9WdKzkr5oZpeNeLPq41vfIekCd3+tqmvlT493l3y4yzGSdDx+30gUJUBqCH4A9b4p6RfN7CSp2k0vaYek18f7N0jqjfedpurz2T+r6pMD18bHlOJeAEmaJ2m/uw+Y2VmSzh9jew5LmjPOzwKgCYIfwBB33yrpjyXdYWYPqXp//7OS3mJm90g6T9LR+PC3SnrQzB6Q9B5JfxVvv17Sw/Hgvn+V1GNmD0v6I0l3jbFJ35a0hsF9QDgM7gMAYAqh4gcAYAoh+AEAmEIIfgAAphCCHwCAKYTgBwBgCiH4AQCYQgh+AACmEIIfAIAp5P8D4P/fCXg2r+4AAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "l = ['age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", + "for i in l:\n", + " plt.figure(figsize=(8, 8))\n", + " sns.distplot(data[i])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can see that except age all the features are skewed, of which catage and mercat are negatively skewed and others are positively skewed" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It can be seen that the data has outliers, however the number of outliers is significant. Thus we wont remove them" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n", + "C:\\Users\\MAYUR Shah\\anaconda3\\lib\\site-packages\\seaborn\\distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", + " warnings.warn(msg, FutureWarning)\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "l = ['amount','age', 'meramt', 'catamt', 'custamt', 'custcat', 'mercat', 'catage']\n", + "for i in l:\n", + " plt.figure(figsize=(14, 8))\n", + " sns.distplot(data[df['fraud'] == 0][i],color = 'blue')\n", + " sns.distplot(data[df['fraud'] == 1][i],color = 'red')" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "for i in ['gender', 'category']:\n", + " plt.figure(figsize=(20, 10))\n", + " sns.barplot(x = i,\n", + " y = df['fraud'],\n", + " data = data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the numerical column the values which were fraund and those which were not visibily seperated after a certain value, clearly showing patterns with the exception of age column. The gender column is an interesting one as it tells that the number of females being cheated is significantly higher" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "#adjusting skewness\n", + "import numpy as np\n", + "data['meramt'] = np.log((data['meramt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "data['catamt'] = np.log((data['catamt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "data['custcat'] = np.log((data['custcat'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [], + "source": [ + "data['custamt'] = np.log((data['custamt'] + 0.00000001))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "data['mercat'] = (data['mercat'])**(1/3)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "data['catage'] = (data['catage'])**(1/3)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['step', 'customer', 'gender', 'merchant', 'category']\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "filtered = data.dtypes[data.dtypes == np.object]\n", + "colname = []\n", + "colname = list(filtered.index)\n", + "print(colname)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "data = data.drop('fraud', axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "data_num = data.drop(colname, axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat = data[colname]" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "SimpleImputer(strategy='median')" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.impute import SimpleImputer\n", + "imputer = SimpleImputer(strategy=\"median\")\n", + "imputer.fit(data_num)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "data_imp = imputer.transform(data_num)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "data_tra = pd.DataFrame(data_imp, columns=data_num.columns,\n", + " index=data.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "StandardScaler()" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "scaler = StandardScaler()\n", + "scaler.fit(data_tra)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "scale_train = scaler.transform(data_tra)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "data_sc = pd.DataFrame(scale_train, columns=data_tra.columns,\n", + " index=data_num.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat = data_cat.drop(['customer', 'step'], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "data_cat_encoded = pd.get_dummies(data_cat)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "data_join = pd.concat([data_sc, data_cat_encoded], axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(25200, 74)" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_join.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Above we have imputed and scaled the features, imputation is not necessary in this case as there is no missing value present, yet I have used it just to show end-to-end data science pipeline as asked in the task.
\n", + "After this we have one-hot encoded the categorical features and dropped customer and step colimns as given in the assignment notebook" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "y = df['fraud']\n", + "X_train, X_test, y_train, y_test = train_test_split(data_join, y, test_size=0.75, random_state=42,stratify=y)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestClassifier(class_weight='balanced', criterion='entropy',\n", + " random_state=42)" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "forest_reg = RandomForestClassifier(criterion='entropy', class_weight='balanced', random_state=42)\n", + "forest_reg.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "y_pred = forest_reg.predict(X_test)\n", + "y_prediction = forest_reg.predict_proba(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.9971902606310015\n", + "[[13272 228]\n", + " [ 142 5258]]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.metrics import roc_auc_score\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "if df['fraud'].nunique()> 2:\n", + " rules_score = roc_auc_score(y_test, y_prediction[:,1], multi_class = 'ovo')\n", + "else:\n", + " rules_score = roc_auc_score(y_test, y_prediction[:,1])\n", + "\n", + "print(rules_score)\n", + "\n", + "from sklearn.metrics import confusion_matrix\n", + "cf_matrix = confusion_matrix(y_test, y_pred)\n", + "print(cf_matrix)\n", + "\n", + "import seaborn as sns\n", + "sns.heatmap(cf_matrix, annot=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As seen above just with simple feature engineering we reduced 79 false positives and improved roc score. Let's use regularization by cross validation to see what happens" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "def display_scores(scores):\n", + " print(\"Scores:\", scores)\n", + " print(\"Mean:\", scores.mean())\n", + " print(\"Standard deviation:\", scores.std())" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scores: [0.99759259 0.99767215 0.99580316 0.99845885 0.99724417 0.99762346\n", + " 0.99698217 0.99722977 0.99861934 0.99639575]\n", + "Mean: 0.9973621399176956\n", + "Standard deviation: 0.0008087641314100779\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import cross_val_score\n", + "forest_scores = cross_val_score(forest_reg, X_test, y_test,\n", + " scoring=\"roc_auc\", cv=10)\n", + "display_scores(forest_scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[13288 212]\n", + " [ 130 5270]]\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import cross_val_predict\n", + "from sklearn.metrics import confusion_matrix\n", + "cm_score = cross_val_predict(forest_reg, X_test, y_test, cv=10)\n", + "conf_mat = confusion_matrix(y_test, cm_score)\n", + "print(conf_mat)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see that with 10 fold cross validation we get the roc score with a maximum value of 0.99861934 and reduce the number of false positives to 212" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The hyperparameters for this model were tuned using Random Search, and gave an roc score of 0.99989934 however it worsened the false positive number, which is why we have chosen the base model itself" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}