Histogram_of_Number_of_Total_Violations_by_Hour_of_Day.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import datetime, pytz\n",
    "from datetime import datetime, timedelta\n",
    "from collections import defaultdict\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>address</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>apartment</th>\n",
       "      <th>sensor_id</th>\n",
       "      <th>bbl</th>\n",
       "      <th>temp</th>\n",
       "      <th>created_at</th>\n",
       "      <th>outdoor_temp</th>\n",
       "      <th>violation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>381.0</td>\n",
       "      <td>124 E 176th St</td>\n",
       "      <td>10453.0</td>\n",
       "      <td>6J</td>\n",
       "      <td>feather0090</td>\n",
       "      <td>2.028260e+09</td>\n",
       "      <td>66</td>\n",
       "      <td>2019-01-30 23:58:43</td>\n",
       "      <td>11.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>390.0</td>\n",
       "      <td>1802 Ocean Parkway</td>\n",
       "      <td>11223.0</td>\n",
       "      <td>C4</td>\n",
       "      <td>feather0101</td>\n",
       "      <td>3.066810e+09</td>\n",
       "      <td>69</td>\n",
       "      <td>2019-01-30 23:58:19</td>\n",
       "      <td>14.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>492.0</td>\n",
       "      <td>341 E 19th St</td>\n",
       "      <td>11226.0</td>\n",
       "      <td>3E</td>\n",
       "      <td>feather0118</td>\n",
       "      <td>3.051620e+09</td>\n",
       "      <td>68</td>\n",
       "      <td>2019-01-30 23:54:54</td>\n",
       "      <td>13.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>389.0</td>\n",
       "      <td>4836 41st St</td>\n",
       "      <td>11104.0</td>\n",
       "      <td>2F</td>\n",
       "      <td>feather0024</td>\n",
       "      <td>4.002020e+09</td>\n",
       "      <td>50</td>\n",
       "      <td>2019-01-30 23:50:40</td>\n",
       "      <td>16.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>167.0</td>\n",
       "      <td>150 Court St</td>\n",
       "      <td>11201.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>feather0115</td>\n",
       "      <td>3.002920e+09</td>\n",
       "      <td>69</td>\n",
       "      <td>2019-01-30 23:50:16</td>\n",
       "      <td>14.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id             address  zip_code apartment    sensor_id           bbl  \\\n",
       "0    381.0      124 E 176th St   10453.0        6J  feather0090  2.028260e+09   \n",
       "1    390.0  1802 Ocean Parkway   11223.0        C4  feather0101  3.066810e+09   \n",
       "2    492.0       341 E 19th St   11226.0        3E  feather0118  3.051620e+09   \n",
       "3    389.0        4836 41st St   11104.0        2F  feather0024  4.002020e+09   \n",
       "4    167.0        150 Court St   11201.0       NaN  feather0115  3.002920e+09   \n",
       "\n",
       "   temp           created_at  outdoor_temp  violation  \n",
       "0    66  2019-01-30 23:58:43          11.0       True  \n",
       "1    69  2019-01-30 23:58:19          14.0      False  \n",
       "2    68  2019-01-30 23:54:54          13.0      False  \n",
       "3    50  2019-01-30 23:50:40          16.0       True  \n",
       "4    69  2019-01-30 23:50:16          14.0      False  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_01 = pd.read_csv(\"data/2018-2019 data pt 1_Oct 01 2018 to Jan 31 2019.csv\")\n",
    "temp_02 = pd.read_csv(\"data/2018-2019 data pt 2_ Feb 01 2019 to May 31 2019.csv\")\n",
    "df = pd.concat([temp_01, temp_02])\n",
    "\n",
    "# remove all columns except for \"created_at\" and \"violation\"\n",
    "# TODO: why doesn't this work\n",
    "df.drop(columns=['user_id', 'address', 'zip_code', 'apartment', 'sensor_id', 'bbl', 'temp', 'outdoor_temp'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Modified from Archived Scripts/Consec Violation Hist and Day Time_eda.ipynb\n",
    "\n",
    "def bin_by_time(dataframe, time, day_night):\n",
    "    \n",
    "    \"\"\"\n",
    "    Bins all temperature violations (as defined by NY law) in the csv file by hour\n",
    "    :param input_csv: path to input csv\n",
    "    :type input_csv: str\n",
    "    :param time: the aspect of timestamp to bin by, e.g. month, day, hour.\n",
    "    :type time: str\n",
    "    :param day_night: the time of day (day or night) to look at.\n",
    "    :type day_night: str\n",
    "    :return: dictionary of lists where keys are time slices, values are lists of records where a violation occured\n",
    "    :rtype: dict(list)\n",
    "    \"\"\"\n",
    "    \n",
    "    # keys are values of time parameter, values are lists of rows\n",
    "    violations = defaultdict(list)\n",
    "    for row in df.itertuples(index=False):\n",
    "        created_at = getattr(row, \"created_at\")\n",
    "        if getattr(row, \"violation\") == True:\n",
    "            created = datetime.strptime(created_at, \"%Y-%m-%d %H:%M:%S\")\n",
    "            # datetime formatting to convert UTC to EST or EDT as appropriate\n",
    "            # for EDA only! stick to UTC for actual automation.\n",
    "            # hardcoding timezone since our domain is very constrained.\n",
    "            created = created.replace(tzinfo=pytz.utc)\n",
    "            created = created.astimezone(pytz.timezone('US/Eastern'))\n",
    "            if day_night == \"day\":\n",
    "                if created.hour >= 6 and created.hour <= 21:\n",
    "                    violations[getattr(created, time)].append(row)\n",
    "                    # looking only at day time hours\n",
    "            elif day_night == \"night\":\n",
    "                if created.hour >= 22 or created.hour <= 5:\n",
    "                    violations[getattr(created, time)].append(row)\n",
    "                    # looking only at night time hours\n",
    "            else:\n",
    "                violations[getattr(created, time)].append(row)\n",
    "            # modified the code from Daniel to output only Day time hour data, Night time hour data, or AlL\n",
    "    return violations\n",
    "\n",
    "\n",
    "def plot_time_bins(title, time_bins):\n",
    "    \"\"\"\n",
    "    Make a bar graph of total violations across all users with a bin for each time\n",
    "    :param time_bins: a dictionary of lists keyed by time, value is list of violations occurring during that time\n",
    "    :type time_bins: dict[list]\n",
    "    :param label: the label for the x axis of the plot (what type of time slice this is)\n",
    "    :type label: str\n",
    "    \"\"\"\n",
    "    \n",
    "    violations_per_time = []\n",
    "    tick_labels = []\n",
    "    # get tick labels in order\n",
    "    for time_slice, records in sorted(time_bins.items(), key=lambda x: x[0]):\n",
    "        violations_per_time.append(len(records))\n",
    "        tick_labels.append(time_slice)\n",
    "        print(str(time_slice) + ': ' + str(len(records)))\n",
    "    \n",
    "    plt.bar(range(len(violations_per_time)), violations_per_time, tick_label=tick_labels)\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Hour of the Day (US/Eastern)')\n",
    "    plt.ylabel('Total Violations')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6: 865\n",
      "7: 715\n",
      "8: 581\n",
      "9: 547\n",
      "10: 524\n",
      "11: 483\n",
      "12: 459\n",
      "13: 449\n",
      "14: 448\n",
      "15: 452\n",
      "16: 481\n",
      "17: 494\n",
      "18: 522\n",
      "19: 489\n",
      "20: 476\n",
      "21: 479\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_bins = bin_by_time(df, 'hour', 'day')\n",
    "plot_time_bins('Number of Total Violations By Hour of Day - During Daytime Hours', time_bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0: 176\n",
      "1: 185\n",
      "2: 197\n",
      "3: 196\n",
      "4: 202\n",
      "5: 205\n",
      "22: 175\n",
      "23: 177\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_bins = bin_by_time(df, 'hour', 'night')\n",
    "plot_time_bins('Number of Total Violations By Hour of Day - During Nighttime Hours', time_bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0: 176\n",
      "1: 185\n",
      "2: 197\n",
      "3: 196\n",
      "4: 202\n",
      "5: 205\n",
      "6: 865\n",
      "7: 715\n",
      "8: 581\n",
      "9: 547\n",
      "10: 524\n",
      "11: 483\n",
      "12: 459\n",
      "13: 449\n",
      "14: 448\n",
      "15: 452\n",
      "16: 481\n",
      "17: 494\n",
      "18: 522\n",
      "19: 489\n",
      "20: 476\n",
      "21: 479\n",
      "22: 175\n",
      "23: 177\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_bins = bin_by_time(df, 'hour', 'all')\n",
    "plot_time_bins('Number of Total Violations By Hour of Day - During All Hours', time_bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}