pandas DataFrame Sales Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SALES ANALYSIS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>category</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>296809</td>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>13</td>\n",
       "      <td>44.48</td>\n",
       "      <td>578.24</td>\n",
       "      <td>2014-09-27 07:13:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98022</td>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>19</td>\n",
       "      <td>53.62</td>\n",
       "      <td>1018.78</td>\n",
       "      <td>2014-07-29 02:10:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>24.16</td>\n",
       "      <td>289.92</td>\n",
       "      <td>2014-03-01 10:51:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93356</td>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>5</td>\n",
       "      <td>82.68</td>\n",
       "      <td>413.40</td>\n",
       "      <td>2013-11-17 20:41:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>659366</td>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>18</td>\n",
       "      <td>99.64</td>\n",
       "      <td>1793.52</td>\n",
       "      <td>2014-01-03 08:14:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>17</td>\n",
       "      <td>52.82</td>\n",
       "      <td>897.94</td>\n",
       "      <td>2013-12-04 02:07:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>995267</td>\n",
       "      <td>Cole-Eichmann</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>18</td>\n",
       "      <td>15.28</td>\n",
       "      <td>275.04</td>\n",
       "      <td>2014-04-09 16:15:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>524021</td>\n",
       "      <td>Hegmann and Sons</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>7</td>\n",
       "      <td>78.78</td>\n",
       "      <td>551.46</td>\n",
       "      <td>2014-06-18 19:25:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>929400</td>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>17</td>\n",
       "      <td>38.19</td>\n",
       "      <td>649.23</td>\n",
       "      <td>2014-02-10 05:55:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>26.98</td>\n",
       "      <td>323.76</td>\n",
       "      <td>2014-05-20 00:21:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>995267</td>\n",
       "      <td>Cole-Eichmann</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>19</td>\n",
       "      <td>60.22</td>\n",
       "      <td>1144.18</td>\n",
       "      <td>2014-03-10 06:23:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>524021</td>\n",
       "      <td>Hegmann and Sons</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>6</td>\n",
       "      <td>13.12</td>\n",
       "      <td>78.72</td>\n",
       "      <td>2013-11-03 18:38:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>4</td>\n",
       "      <td>59.69</td>\n",
       "      <td>238.76</td>\n",
       "      <td>2014-01-11 21:48:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>555594</td>\n",
       "      <td>Ernser, Cruickshank and Lind</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>97.25</td>\n",
       "      <td>1167.00</td>\n",
       "      <td>2014-09-19 13:20:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>9</td>\n",
       "      <td>81.44</td>\n",
       "      <td>732.96</td>\n",
       "      <td>2014-08-12 08:05:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>93356</td>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>18</td>\n",
       "      <td>53.33</td>\n",
       "      <td>959.94</td>\n",
       "      <td>2014-07-15 23:21:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>4</td>\n",
       "      <td>35.62</td>\n",
       "      <td>142.48</td>\n",
       "      <td>2014-10-05 23:38:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>17</td>\n",
       "      <td>98.23</td>\n",
       "      <td>1669.91</td>\n",
       "      <td>2014-01-26 01:52:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>WJ-02096</td>\n",
       "      <td>Belt</td>\n",
       "      <td>15</td>\n",
       "      <td>69.52</td>\n",
       "      <td>1042.80</td>\n",
       "      <td>2013-11-13 21:38:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>296809</td>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>80.12</td>\n",
       "      <td>961.44</td>\n",
       "      <td>2014-05-24 16:03:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>750461</td>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>WJ-02096</td>\n",
       "      <td>Belt</td>\n",
       "      <td>13</td>\n",
       "      <td>81.19</td>\n",
       "      <td>1055.47</td>\n",
       "      <td>2014-01-08 02:45:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>929400</td>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>2</td>\n",
       "      <td>48.15</td>\n",
       "      <td>96.30</td>\n",
       "      <td>2014-04-28 07:01:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>1</td>\n",
       "      <td>54.94</td>\n",
       "      <td>54.94</td>\n",
       "      <td>2014-08-09 11:22:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>734922</td>\n",
       "      <td>Berge LLC</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>4</td>\n",
       "      <td>57.75</td>\n",
       "      <td>231.00</td>\n",
       "      <td>2013-11-04 09:48:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>296809</td>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>14</td>\n",
       "      <td>47.68</td>\n",
       "      <td>667.52</td>\n",
       "      <td>2014-01-12 00:28:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>304860</td>\n",
       "      <td>Huel-Haag</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>2</td>\n",
       "      <td>41.40</td>\n",
       "      <td>82.80</td>\n",
       "      <td>2014-09-23 02:36:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>6</td>\n",
       "      <td>58.52</td>\n",
       "      <td>351.12</td>\n",
       "      <td>2014-03-14 02:28:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>750461</td>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>12</td>\n",
       "      <td>96.62</td>\n",
       "      <td>1159.44</td>\n",
       "      <td>2013-12-13 03:19:19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>93.67</td>\n",
       "      <td>1124.04</td>\n",
       "      <td>2014-02-19 06:03:09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>115138</td>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>72.63</td>\n",
       "      <td>871.56</td>\n",
       "      <td>2014-02-07 03:30:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>711951</td>\n",
       "      <td>Kilback-Gerlach</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>2</td>\n",
       "      <td>90.80</td>\n",
       "      <td>181.60</td>\n",
       "      <td>2014-03-26 20:56:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>676847</td>\n",
       "      <td>Hamill-Hackett</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>6</td>\n",
       "      <td>42.96</td>\n",
       "      <td>257.76</td>\n",
       "      <td>2013-11-14 22:16:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>711951</td>\n",
       "      <td>Kilback-Gerlach</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>1</td>\n",
       "      <td>71.50</td>\n",
       "      <td>71.50</td>\n",
       "      <td>2014-04-14 16:58:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>305803</td>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>1</td>\n",
       "      <td>74.43</td>\n",
       "      <td>74.43</td>\n",
       "      <td>2014-09-20 09:49:19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>8</td>\n",
       "      <td>35.38</td>\n",
       "      <td>283.04</td>\n",
       "      <td>2013-12-12 02:37:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>115138</td>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>16</td>\n",
       "      <td>24.87</td>\n",
       "      <td>397.92</td>\n",
       "      <td>2014-02-20 07:42:49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>296809</td>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>WJ-02096</td>\n",
       "      <td>Belt</td>\n",
       "      <td>14</td>\n",
       "      <td>15.33</td>\n",
       "      <td>214.62</td>\n",
       "      <td>2013-12-03 01:25:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>93356</td>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>94.34</td>\n",
       "      <td>1132.08</td>\n",
       "      <td>2014-09-04 13:39:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>18</td>\n",
       "      <td>12.78</td>\n",
       "      <td>230.04</td>\n",
       "      <td>2014-02-20 13:18:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>676847</td>\n",
       "      <td>Hamill-Hackett</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>3</td>\n",
       "      <td>28.71</td>\n",
       "      <td>86.13</td>\n",
       "      <td>2014-01-02 12:49:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>115138</td>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>11</td>\n",
       "      <td>11.21</td>\n",
       "      <td>123.31</td>\n",
       "      <td>2013-12-10 20:13:01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>4</td>\n",
       "      <td>29.79</td>\n",
       "      <td>119.16</td>\n",
       "      <td>2013-11-07 17:43:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>11</td>\n",
       "      <td>35.82</td>\n",
       "      <td>394.02</td>\n",
       "      <td>2014-06-21 19:49:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>676847</td>\n",
       "      <td>Hamill-Hackett</td>\n",
       "      <td>WJ-02096</td>\n",
       "      <td>Belt</td>\n",
       "      <td>6</td>\n",
       "      <td>55.43</td>\n",
       "      <td>332.58</td>\n",
       "      <td>2014-08-08 13:50:43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>304860</td>\n",
       "      <td>Huel-Haag</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>4</td>\n",
       "      <td>95.75</td>\n",
       "      <td>383.00</td>\n",
       "      <td>2014-03-15 12:50:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>304860</td>\n",
       "      <td>Huel-Haag</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>10</td>\n",
       "      <td>12.63</td>\n",
       "      <td>126.30</td>\n",
       "      <td>2014-06-05 22:34:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>10</td>\n",
       "      <td>26.21</td>\n",
       "      <td>262.10</td>\n",
       "      <td>2014-04-21 02:14:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>11</td>\n",
       "      <td>92.10</td>\n",
       "      <td>1013.10</td>\n",
       "      <td>2014-03-21 14:26:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>750461</td>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>10</td>\n",
       "      <td>98.27</td>\n",
       "      <td>982.70</td>\n",
       "      <td>2014-10-02 04:41:10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>555594</td>\n",
       "      <td>Ernser, Cruickshank and Lind</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>6</td>\n",
       "      <td>65.40</td>\n",
       "      <td>392.40</td>\n",
       "      <td>2014-09-17 19:15:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>995267</td>\n",
       "      <td>Cole-Eichmann</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>10</td>\n",
       "      <td>23.79</td>\n",
       "      <td>237.90</td>\n",
       "      <td>2013-11-17 23:56:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>7</td>\n",
       "      <td>52.01</td>\n",
       "      <td>364.07</td>\n",
       "      <td>2014-05-23 17:49:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>11</td>\n",
       "      <td>13.06</td>\n",
       "      <td>143.66</td>\n",
       "      <td>2014-03-01 08:58:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>14</td>\n",
       "      <td>92.43</td>\n",
       "      <td>1294.02</td>\n",
       "      <td>2014-08-03 21:22:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>14</td>\n",
       "      <td>57.69</td>\n",
       "      <td>807.66</td>\n",
       "      <td>2014-05-26 16:29:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>555594</td>\n",
       "      <td>Ernser, Cruickshank and Lind</td>\n",
       "      <td>KV-99194</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>10</td>\n",
       "      <td>83.05</td>\n",
       "      <td>830.50</td>\n",
       "      <td>2014-01-05 10:16:57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>98022</td>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>10</td>\n",
       "      <td>26.49</td>\n",
       "      <td>264.90</td>\n",
       "      <td>2014-02-12 07:27:39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>929400</td>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>15</td>\n",
       "      <td>88.24</td>\n",
       "      <td>1323.60</td>\n",
       "      <td>2014-07-09 19:31:43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>305803</td>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>13</td>\n",
       "      <td>75.38</td>\n",
       "      <td>979.94</td>\n",
       "      <td>2014-03-05 09:26:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>16</td>\n",
       "      <td>66.61</td>\n",
       "      <td>1065.76</td>\n",
       "      <td>2014-07-25 22:56:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    account number                           name       sku category  \\\n",
       "0           296809                    Carroll PLC  QN-82852     Belt   \n",
       "1            98022              Heidenreich-Bosco  MJ-21460    Shoes   \n",
       "2           563905  Kerluke, Reilly and Bechtelar  AS-93055    Shirt   \n",
       "3            93356                  Waters-Walker  AS-93055    Shirt   \n",
       "4           659366                  Waelchi-Fahey  AS-93055    Shirt   \n",
       "5           563905  Kerluke, Reilly and Bechtelar  AS-93055    Shirt   \n",
       "6           995267                  Cole-Eichmann  GS-86623    Shoes   \n",
       "7           524021               Hegmann and Sons  LL-46261    Shoes   \n",
       "8           929400  Senger, Upton and Breitenberg  LW-86841    Shoes   \n",
       "9           563905  Kerluke, Reilly and Bechtelar  KV-99194    Shirt   \n",
       "10          995267                  Cole-Eichmann  KV-99194    Shirt   \n",
       "11          524021               Hegmann and Sons  QN-82852     Belt   \n",
       "12          758133      Kihn, McClure and Denesik  LL-46261    Shoes   \n",
       "13          555594   Ernser, Cruickshank and Lind  FK-71853    Shirt   \n",
       "14          201259                    Koelpin PLC  GS-86623    Shoes   \n",
       "15           93356                  Waters-Walker  LL-46261    Shoes   \n",
       "16          563905  Kerluke, Reilly and Bechtelar  KV-99194    Shirt   \n",
       "17          201259                    Koelpin PLC  KV-99194    Shirt   \n",
       "18          758133      Kihn, McClure and Denesik  WJ-02096     Belt   \n",
       "19          296809                    Carroll PLC  VG-32047    Shirt   \n",
       "20          750461     Volkman, Goyette and Lemke  WJ-02096     Belt   \n",
       "21          929400  Senger, Upton and Breitenberg  LL-46261    Shoes   \n",
       "22          563905  Kerluke, Reilly and Bechtelar  MJ-21460    Shoes   \n",
       "23          734922                      Berge LLC  QN-82852     Belt   \n",
       "24          296809                    Carroll PLC  AS-93055    Shirt   \n",
       "25          304860                      Huel-Haag  QN-82852     Belt   \n",
       "26          563905  Kerluke, Reilly and Bechtelar  VG-32047    Shirt   \n",
       "27          750461     Volkman, Goyette and Lemke  LL-46261    Shoes   \n",
       "28          850140                      Kunze Inc  KV-99194    Shirt   \n",
       "29          115138                  Gorczany-Hahn  VG-32047    Shirt   \n",
       "30          711951                Kilback-Gerlach  AS-93055    Shirt   \n",
       "31          676847                 Hamill-Hackett  AS-93055    Shirt   \n",
       "32          711951                Kilback-Gerlach  AS-93055    Shirt   \n",
       "33          305803     Davis, Kshlerin and Reilly  AS-93055    Shirt   \n",
       "34          201259                    Koelpin PLC  GS-86623    Shoes   \n",
       "35          115138                  Gorczany-Hahn  QN-82852     Belt   \n",
       "36          296809                    Carroll PLC  WJ-02096     Belt   \n",
       "37           93356                  Waters-Walker  AS-93055    Shirt   \n",
       "38          850140                      Kunze Inc  MJ-21460    Shoes   \n",
       "39          676847                 Hamill-Hackett  LL-46261    Shoes   \n",
       "40          115138                  Gorczany-Hahn  VG-32047    Shirt   \n",
       "41          201259                    Koelpin PLC  KV-99194    Shirt   \n",
       "42          201259                    Koelpin PLC  LW-86841    Shoes   \n",
       "43          676847                 Hamill-Hackett  WJ-02096     Belt   \n",
       "44          304860                      Huel-Haag  GS-86623    Shoes   \n",
       "45          304860                      Huel-Haag  MJ-21460    Shoes   \n",
       "46          850140                      Kunze Inc  MJ-21460    Shoes   \n",
       "47          758133      Kihn, McClure and Denesik  LW-86841    Shoes   \n",
       "48          750461     Volkman, Goyette and Lemke  MJ-21460    Shoes   \n",
       "49          555594   Ernser, Cruickshank and Lind  FK-71853    Shirt   \n",
       "50          995267                  Cole-Eichmann  KV-99194    Shirt   \n",
       "51          201259                    Koelpin PLC  MJ-21460    Shoes   \n",
       "52          758133      Kihn, McClure and Denesik  FK-71853    Shirt   \n",
       "53          850140                      Kunze Inc  GS-86623    Shoes   \n",
       "54          201259                    Koelpin PLC  FK-71853    Shirt   \n",
       "55          555594   Ernser, Cruickshank and Lind  KV-99194    Shirt   \n",
       "56           98022              Heidenreich-Bosco  GS-86623    Shoes   \n",
       "57          929400  Senger, Upton and Breitenberg  GS-86623    Shoes   \n",
       "58          305803     Davis, Kshlerin and Reilly  LL-46261    Shoes   \n",
       "59          850140                      Kunze Inc  LW-86841    Shoes   \n",
       "\n",
       "    quantity  unit price  ext price                 date  \n",
       "0         13       44.48     578.24  2014-09-27 07:13:03  \n",
       "1         19       53.62    1018.78  2014-07-29 02:10:44  \n",
       "2         12       24.16     289.92  2014-03-01 10:51:24  \n",
       "3          5       82.68     413.40  2013-11-17 20:41:11  \n",
       "4         18       99.64    1793.52  2014-01-03 08:14:27  \n",
       "5         17       52.82     897.94  2013-12-04 02:07:05  \n",
       "6         18       15.28     275.04  2014-04-09 16:15:03  \n",
       "7          7       78.78     551.46  2014-06-18 19:25:10  \n",
       "8         17       38.19     649.23  2014-02-10 05:55:56  \n",
       "9         12       26.98     323.76  2014-05-20 00:21:28  \n",
       "10        19       60.22    1144.18  2014-03-10 06:23:31  \n",
       "11         6       13.12      78.72  2013-11-03 18:38:16  \n",
       "12         4       59.69     238.76  2014-01-11 21:48:28  \n",
       "13        12       97.25    1167.00  2014-09-19 13:20:00  \n",
       "14         9       81.44     732.96  2014-08-12 08:05:27  \n",
       "15        18       53.33     959.94  2014-07-15 23:21:11  \n",
       "16         4       35.62     142.48  2014-10-05 23:38:16  \n",
       "17        17       98.23    1669.91  2014-01-26 01:52:36  \n",
       "18        15       69.52    1042.80  2013-11-13 21:38:46  \n",
       "19        12       80.12     961.44  2014-05-24 16:03:28  \n",
       "20        13       81.19    1055.47  2014-01-08 02:45:07  \n",
       "21         2       48.15      96.30  2014-04-28 07:01:04  \n",
       "22         1       54.94      54.94  2014-08-09 11:22:15  \n",
       "23         4       57.75     231.00  2013-11-04 09:48:26  \n",
       "24        14       47.68     667.52  2014-01-12 00:28:09  \n",
       "25         2       41.40      82.80  2014-09-23 02:36:55  \n",
       "26         6       58.52     351.12  2014-03-14 02:28:57  \n",
       "27        12       96.62    1159.44  2013-12-13 03:19:19  \n",
       "28        12       93.67    1124.04  2014-02-19 06:03:09  \n",
       "29        12       72.63     871.56  2014-02-07 03:30:14  \n",
       "30         2       90.80     181.60  2014-03-26 20:56:14  \n",
       "31         6       42.96     257.76  2013-11-14 22:16:18  \n",
       "32         1       71.50      71.50  2014-04-14 16:58:07  \n",
       "33         1       74.43      74.43  2014-09-20 09:49:19  \n",
       "34         8       35.38     283.04  2013-12-12 02:37:57  \n",
       "35        16       24.87     397.92  2014-02-20 07:42:49  \n",
       "36        14       15.33     214.62  2013-12-03 01:25:07  \n",
       "37        12       94.34    1132.08  2014-09-04 13:39:04  \n",
       "38        18       12.78     230.04  2014-02-20 13:18:47  \n",
       "39         3       28.71      86.13  2014-01-02 12:49:41  \n",
       "40        11       11.21     123.31  2013-12-10 20:13:01  \n",
       "41         4       29.79     119.16  2013-11-07 17:43:31  \n",
       "42        11       35.82     394.02  2014-06-21 19:49:30  \n",
       "43         6       55.43     332.58  2014-08-08 13:50:43  \n",
       "44         4       95.75     383.00  2014-03-15 12:50:59  \n",
       "45        10       12.63     126.30  2014-06-05 22:34:03  \n",
       "46        10       26.21     262.10  2014-04-21 02:14:10  \n",
       "47        11       92.10    1013.10  2014-03-21 14:26:03  \n",
       "48        10       98.27     982.70  2014-10-02 04:41:10  \n",
       "49         6       65.40     392.40  2014-09-17 19:15:27  \n",
       "50        10       23.79     237.90  2013-11-17 23:56:36  \n",
       "51         7       52.01     364.07  2014-05-23 17:49:08  \n",
       "52        11       13.06     143.66  2014-03-01 08:58:41  \n",
       "53        14       92.43    1294.02  2014-08-03 21:22:07  \n",
       "54        14       57.69     807.66  2014-05-26 16:29:02  \n",
       "55        10       83.05     830.50  2014-01-05 10:16:57  \n",
       "56        10       26.49     264.90  2014-02-12 07:27:39  \n",
       "57        15       88.24    1323.60  2014-07-09 19:31:43  \n",
       "58        13       75.38     979.94  2014-03-05 09:26:56  \n",
       "59        16       66.61    1065.76  2014-07-25 22:56:12  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import csv\n",
    "data=pd.read_csv(\"sell.csv\")\n",
    "data.head(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "account number      int64\n",
       "name               object\n",
       "sku                object\n",
       "category           object\n",
       "quantity            int64\n",
       "unit price        float64\n",
       "ext price         float64\n",
       "date               object\n",
       "dtype: object"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "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>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>category</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>296809</td>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Belt</td>\n",
       "      <td>13</td>\n",
       "      <td>44.48</td>\n",
       "      <td>578.24</td>\n",
       "      <td>2014-09-27 07:13:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98022</td>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>19</td>\n",
       "      <td>53.62</td>\n",
       "      <td>1018.78</td>\n",
       "      <td>2014-07-29 02:10:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>12</td>\n",
       "      <td>24.16</td>\n",
       "      <td>289.92</td>\n",
       "      <td>2014-03-01 10:51:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93356</td>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>5</td>\n",
       "      <td>82.68</td>\n",
       "      <td>413.40</td>\n",
       "      <td>2013-11-17 20:41:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>659366</td>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>18</td>\n",
       "      <td>99.64</td>\n",
       "      <td>1793.52</td>\n",
       "      <td>2014-01-03 08:14:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>AS-93055</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>17</td>\n",
       "      <td>52.82</td>\n",
       "      <td>897.94</td>\n",
       "      <td>2013-12-04 02:07:05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account number                           name       sku category  quantity  \\\n",
       "0          296809                    Carroll PLC  QN-82852     Belt        13   \n",
       "1           98022              Heidenreich-Bosco  MJ-21460    Shoes        19   \n",
       "2          563905  Kerluke, Reilly and Bechtelar  AS-93055    Shirt        12   \n",
       "3           93356                  Waters-Walker  AS-93055    Shirt         5   \n",
       "4          659366                  Waelchi-Fahey  AS-93055    Shirt        18   \n",
       "5          563905  Kerluke, Reilly and Bechtelar  AS-93055    Shirt        17   \n",
       "\n",
       "   unit price  ext price                date  \n",
       "0       44.48     578.24 2014-09-27 07:13:03  \n",
       "1       53.62    1018.78 2014-07-29 02:10:44  \n",
       "2       24.16     289.92 2014-03-01 10:51:24  \n",
       "3       82.68     413.40 2013-11-17 20:41:11  \n",
       "4       99.64    1793.52 2014-01-03 08:14:27  \n",
       "5       52.82     897.94 2013-12-04 02:07:05  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv(\"sell.csv\",parse_dates=['date'])#aet date has higher priority\n",
    "data.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "account number             int64\n",
       "name                      object\n",
       "sku                       object\n",
       "category                  object\n",
       "quantity                   int64\n",
       "unit price               float64\n",
       "ext price                float64\n",
       "date              datetime64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes#date has different data type:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 8 columns):\n",
      " #   Column          Non-Null Count  Dtype         \n",
      "---  ------          --------------  -----         \n",
      " 0   account number  1000 non-null   int64         \n",
      " 1   name            1000 non-null   object        \n",
      " 2   sku             1000 non-null   object        \n",
      " 3   category        1000 non-null   object        \n",
      " 4   quantity        1000 non-null   int64         \n",
      " 5   unit price      1000 non-null   float64       \n",
      " 6   ext price       1000 non-null   float64       \n",
      " 7   date            1000 non-null   datetime64[ns]\n",
      "dtypes: datetime64[ns](1), float64(2), int64(2), object(3)\n",
      "memory usage: 62.6+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "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>account number</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>535208.897000</td>\n",
       "      <td>10.328000</td>\n",
       "      <td>56.179630</td>\n",
       "      <td>579.84390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>277589.746014</td>\n",
       "      <td>5.687597</td>\n",
       "      <td>25.331939</td>\n",
       "      <td>435.30381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>93356.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.060000</td>\n",
       "      <td>10.38000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>299771.000000</td>\n",
       "      <td>5.750000</td>\n",
       "      <td>35.995000</td>\n",
       "      <td>232.60500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>563905.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>56.765000</td>\n",
       "      <td>471.72000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>750461.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>76.802500</td>\n",
       "      <td>878.13750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>995267.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>99.970000</td>\n",
       "      <td>1994.80000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       account number     quantity   unit price   ext price\n",
       "count     1000.000000  1000.000000  1000.000000  1000.00000\n",
       "mean    535208.897000    10.328000    56.179630   579.84390\n",
       "std     277589.746014     5.687597    25.331939   435.30381\n",
       "min      93356.000000     1.000000    10.060000    10.38000\n",
       "25%     299771.000000     5.750000    35.995000   232.60500\n",
       "50%     563905.000000    10.000000    56.765000   471.72000\n",
       "75%     750461.000000    15.000000    76.802500   878.13750\n",
       "max     995267.000000    20.000000    99.970000  1994.80000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "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>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>category</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.00000</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>QN-82852</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-09-11 00:45:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>59</td>\n",
       "      <td>109</td>\n",
       "      <td>404</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>first</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2013-10-22 13:54:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-10-22 11:43:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>535208.897000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.328000</td>\n",
       "      <td>56.179630</td>\n",
       "      <td>579.84390</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>277589.746014</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.687597</td>\n",
       "      <td>25.331939</td>\n",
       "      <td>435.30381</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>93356.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.060000</td>\n",
       "      <td>10.38000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>299771.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.750000</td>\n",
       "      <td>35.995000</td>\n",
       "      <td>232.60500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>563905.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>56.765000</td>\n",
       "      <td>471.72000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>750461.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>76.802500</td>\n",
       "      <td>878.13750</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>995267.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>99.970000</td>\n",
       "      <td>1994.80000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        account number                           name       sku category  \\\n",
       "count      1000.000000                           1000      1000     1000   \n",
       "unique             NaN                             20        10        3   \n",
       "top                NaN  Senger, Upton and Breitenberg  QN-82852    Shirt   \n",
       "freq               NaN                             59       109      404   \n",
       "first              NaN                            NaN       NaN      NaN   \n",
       "last               NaN                            NaN       NaN      NaN   \n",
       "mean     535208.897000                            NaN       NaN      NaN   \n",
       "std      277589.746014                            NaN       NaN      NaN   \n",
       "min       93356.000000                            NaN       NaN      NaN   \n",
       "25%      299771.000000                            NaN       NaN      NaN   \n",
       "50%      563905.000000                            NaN       NaN      NaN   \n",
       "75%      750461.000000                            NaN       NaN      NaN   \n",
       "max      995267.000000                            NaN       NaN      NaN   \n",
       "\n",
       "           quantity   unit price   ext price                 date  \n",
       "count   1000.000000  1000.000000  1000.00000                 1000  \n",
       "unique          NaN          NaN         NaN                 1000  \n",
       "top             NaN          NaN         NaN  2014-09-11 00:45:37  \n",
       "freq            NaN          NaN         NaN                    1  \n",
       "first           NaN          NaN         NaN  2013-10-22 13:54:50  \n",
       "last            NaN          NaN         NaN  2014-10-22 11:43:28  \n",
       "mean      10.328000    56.179630   579.84390                  NaN  \n",
       "std        5.687597    25.331939   435.30381                  NaN  \n",
       "min        1.000000    10.060000    10.38000                  NaN  \n",
       "25%        5.750000    35.995000   232.60500                  NaN  \n",
       "50%       10.000000    56.765000   471.72000                  NaN  \n",
       "75%       15.000000    76.802500   878.13750                  NaN  \n",
       "max       20.000000    99.970000  1994.80000                  NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1000.000000\n",
       "mean       56.179630\n",
       "std        25.331939\n",
       "min        10.060000\n",
       "25%        35.995000\n",
       "50%        56.765000\n",
       "75%        76.802500\n",
       "max        99.970000\n",
       "Name: unit price, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['unit price'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['account number', 'name', 'sku', 'category', 'quantity', 'unit price',\n",
       "       'ext price', 'date'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>13</td>\n",
       "      <td>44.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>2</td>\n",
       "      <td>44.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>13</td>\n",
       "      <td>40.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>12</td>\n",
       "      <td>80.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>11</td>\n",
       "      <td>12.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>Cole-Eichmann</td>\n",
       "      <td>16</td>\n",
       "      <td>88.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>8</td>\n",
       "      <td>28.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>700</th>\n",
       "      <td>Hegmann and Sons</td>\n",
       "      <td>11</td>\n",
       "      <td>54.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>10</td>\n",
       "      <td>88.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>Huel-Haag</td>\n",
       "      <td>5</td>\n",
       "      <td>58.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              name  quantity  unit price\n",
       "0                      Carroll PLC        13       44.48\n",
       "100                  Gorczany-Hahn         2       44.10\n",
       "200                      Kunze Inc        13       40.29\n",
       "300                  Gorczany-Hahn        12       80.25\n",
       "400  Senger, Upton and Breitenberg        11       12.27\n",
       "500                  Cole-Eichmann        16       88.32\n",
       "600                    Carroll PLC         8       28.32\n",
       "700               Hegmann and Sons        11       54.79\n",
       "800                  Waelchi-Fahey        10       88.36\n",
       "900                      Huel-Haag         5       58.12"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer=data[['name','quantity','unit price']]\n",
    "customer[::100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Senger, Upton and Breitenberg', 'Davis, Kshlerin and Reilly', 'Kerluke, Reilly and Bechtelar', 'Kunze Inc', 'Volkman, Goyette and Lemke', 'Kuphal, Zieme and Kub', 'Kilback-Gerlach', 'Kihn, McClure and Denesik', 'Gorczany-Hahn', 'Ernser, Cruickshank and Lind', 'Cole-Eichmann', 'Hamill-Hackett', 'Heidenreich-Bosco', 'Berge LLC', 'Koelpin PLC', 'Waters-Walker', 'Carroll PLC', 'Waelchi-Fahey', 'Huel-Haag', 'Hegmann and Sons'}\n"
     ]
    }
   ],
   "source": [
    "#printing unique name\n",
    "print(set(data['name']))\n",
    "#data['name'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Belt', 'Shoes', 'Shirt'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " data['category'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CONTAINS,STARTSWITH,MATH,FULLMATH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>13</td>\n",
       "      <td>44.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>19</td>\n",
       "      <td>53.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>12</td>\n",
       "      <td>24.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>5</td>\n",
       "      <td>82.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>18</td>\n",
       "      <td>99.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>11</td>\n",
       "      <td>60.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>16</td>\n",
       "      <td>19.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>13</td>\n",
       "      <td>90.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Huel-Haag</td>\n",
       "      <td>9</td>\n",
       "      <td>98.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>14</td>\n",
       "      <td>74.83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              name  quantity  unit price\n",
       "0                      Carroll PLC        13       44.48\n",
       "1                Heidenreich-Bosco        19       53.62\n",
       "2    Kerluke, Reilly and Bechtelar        12       24.16\n",
       "3                    Waters-Walker         5       82.68\n",
       "4                    Waelchi-Fahey        18       99.64\n",
       "..                             ...       ...         ...\n",
       "995      Kihn, McClure and Denesik        11       60.50\n",
       "996                      Kunze Inc        16       19.66\n",
       "997                  Waters-Walker        13       90.95\n",
       "998                      Huel-Haag         9       98.22\n",
       "999              Heidenreich-Bosco        14       74.83\n",
       "\n",
       "[1000 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>12</td>\n",
       "      <td>24.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>14</td>\n",
       "      <td>40.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>17</td>\n",
       "      <td>45.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>4</td>\n",
       "      <td>63.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>17</td>\n",
       "      <td>59.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>13</td>\n",
       "      <td>83.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>12</td>\n",
       "      <td>32.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>525</th>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>6</td>\n",
       "      <td>70.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>626</th>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>3</td>\n",
       "      <td>30.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>733</th>\n",
       "      <td>Volkman, Goyette and Lemke</td>\n",
       "      <td>7</td>\n",
       "      <td>23.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>811</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>8</td>\n",
       "      <td>63.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>892</th>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>15</td>\n",
       "      <td>59.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              name  quantity  unit price\n",
       "2    Kerluke, Reilly and Bechtelar        12       24.16\n",
       "71   Kerluke, Reilly and Bechtelar        14       40.30\n",
       "145     Volkman, Goyette and Lemke        17       45.43\n",
       "217     Davis, Kshlerin and Reilly         4       63.39\n",
       "307     Davis, Kshlerin and Reilly        17       59.12\n",
       "395     Volkman, Goyette and Lemke        13       83.60\n",
       "462                  Waelchi-Fahey        12       32.84\n",
       "525     Volkman, Goyette and Lemke         6       70.64\n",
       "626     Volkman, Goyette and Lemke         3       30.80\n",
       "733     Volkman, Goyette and Lemke         7       23.04\n",
       "811                  Waelchi-Fahey         8       63.37\n",
       "892     Davis, Kshlerin and Reilly        15       59.34"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "customer[customer['name'].str.contains('y')][::20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "237"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(customer[customer['name'].str.contains('y')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>12</td>\n",
       "      <td>24.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>18</td>\n",
       "      <td>99.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>17</td>\n",
       "      <td>52.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>12</td>\n",
       "      <td>26.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>4</td>\n",
       "      <td>35.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>953</th>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>18</td>\n",
       "      <td>20.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>16</td>\n",
       "      <td>90.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>6</td>\n",
       "      <td>49.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>Gorczany-Hahn</td>\n",
       "      <td>20</td>\n",
       "      <td>72.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>10</td>\n",
       "      <td>56.56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>237 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              name  quantity  unit price\n",
       "2    Kerluke, Reilly and Bechtelar        12       24.16\n",
       "4                    Waelchi-Fahey        18       99.64\n",
       "5    Kerluke, Reilly and Bechtelar        17       52.82\n",
       "9    Kerluke, Reilly and Bechtelar        12       26.98\n",
       "16   Kerluke, Reilly and Bechtelar         4       35.62\n",
       "..                             ...       ...         ...\n",
       "953     Davis, Kshlerin and Reilly        18       20.74\n",
       "971  Kerluke, Reilly and Bechtelar        16       90.96\n",
       "978     Davis, Kshlerin and Reilly         6       49.81\n",
       "982                  Gorczany-Hahn        20       72.35\n",
       "993                  Waelchi-Fahey        10       56.56\n",
       "\n",
       "[237 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#use in both upper and lower case as well.\n",
    "customer[customer.name.str.contains('Y',case=False)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Belt', 'Shirt', 'Shoes'}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(data['category'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>category</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>98022</td>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>19</td>\n",
       "      <td>53.62</td>\n",
       "      <td>1018.78</td>\n",
       "      <td>2014-07-29 02:10:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>16</td>\n",
       "      <td>66.61</td>\n",
       "      <td>1065.76</td>\n",
       "      <td>2014-07-25 22:56:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>16</td>\n",
       "      <td>80.82</td>\n",
       "      <td>1293.12</td>\n",
       "      <td>2014-08-19 00:53:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>201259</td>\n",
       "      <td>Koelpin PLC</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>20</td>\n",
       "      <td>45.32</td>\n",
       "      <td>906.40</td>\n",
       "      <td>2014-07-06 22:06:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>524021</td>\n",
       "      <td>Hegmann and Sons</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>10</td>\n",
       "      <td>31.81</td>\n",
       "      <td>318.10</td>\n",
       "      <td>2013-11-18 23:11:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>563905</td>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>17</td>\n",
       "      <td>75.69</td>\n",
       "      <td>1286.73</td>\n",
       "      <td>2013-11-25 02:35:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>305803</td>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>LL-46261</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>13</td>\n",
       "      <td>77.78</td>\n",
       "      <td>1011.14</td>\n",
       "      <td>2013-11-30 17:23:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>93356</td>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>13</td>\n",
       "      <td>45.97</td>\n",
       "      <td>597.61</td>\n",
       "      <td>2014-07-05 08:56:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>15</td>\n",
       "      <td>80.59</td>\n",
       "      <td>1208.85</td>\n",
       "      <td>2014-10-05 18:13:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>561</th>\n",
       "      <td>758133</td>\n",
       "      <td>Kihn, McClure and Denesik</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>12</td>\n",
       "      <td>19.81</td>\n",
       "      <td>237.72</td>\n",
       "      <td>2014-10-12 12:33:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>622</th>\n",
       "      <td>929400</td>\n",
       "      <td>Senger, Upton and Breitenberg</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>17</td>\n",
       "      <td>36.81</td>\n",
       "      <td>625.77</td>\n",
       "      <td>2013-12-05 23:10:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>685</th>\n",
       "      <td>711951</td>\n",
       "      <td>Kilback-Gerlach</td>\n",
       "      <td>MJ-21460</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>14</td>\n",
       "      <td>40.64</td>\n",
       "      <td>568.96</td>\n",
       "      <td>2014-10-21 15:55:43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>299771</td>\n",
       "      <td>Kuphal, Zieme and Kub</td>\n",
       "      <td>VG-32047</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>15</td>\n",
       "      <td>21.39</td>\n",
       "      <td>320.85</td>\n",
       "      <td>2013-12-07 12:59:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>812</th>\n",
       "      <td>524021</td>\n",
       "      <td>Hegmann and Sons</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>9</td>\n",
       "      <td>87.07</td>\n",
       "      <td>783.63</td>\n",
       "      <td>2014-09-10 21:37:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>299771</td>\n",
       "      <td>Kuphal, Zieme and Kub</td>\n",
       "      <td>LW-86841</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>11</td>\n",
       "      <td>87.09</td>\n",
       "      <td>957.99</td>\n",
       "      <td>2013-10-22 16:08:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>935</th>\n",
       "      <td>305803</td>\n",
       "      <td>Davis, Kshlerin and Reilly</td>\n",
       "      <td>FK-71853</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>20</td>\n",
       "      <td>11.96</td>\n",
       "      <td>239.20</td>\n",
       "      <td>2014-09-04 18:27:56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>850140</td>\n",
       "      <td>Kunze Inc</td>\n",
       "      <td>GS-86623</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>16</td>\n",
       "      <td>19.66</td>\n",
       "      <td>314.56</td>\n",
       "      <td>2014-05-03 21:18:15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     account number                           name       sku category  \\\n",
       "1             98022              Heidenreich-Bosco  MJ-21460    Shoes   \n",
       "59           850140                      Kunze Inc  LW-86841    Shoes   \n",
       "120          201259                    Koelpin PLC  LL-46261    Shoes   \n",
       "174          201259                    Koelpin PLC  MJ-21460    Shoes   \n",
       "234          524021               Hegmann and Sons  GS-86623    Shoes   \n",
       "298          563905  Kerluke, Reilly and Bechtelar  FK-71853    Shirt   \n",
       "361          305803     Davis, Kshlerin and Reilly  LL-46261    Shoes   \n",
       "432           93356                  Waters-Walker  VG-32047    Shirt   \n",
       "493          758133      Kihn, McClure and Denesik  VG-32047    Shirt   \n",
       "561          758133      Kihn, McClure and Denesik  GS-86623    Shoes   \n",
       "622          929400  Senger, Upton and Breitenberg  MJ-21460    Shoes   \n",
       "685          711951                Kilback-Gerlach  MJ-21460    Shoes   \n",
       "743          299771          Kuphal, Zieme and Kub  VG-32047    Shirt   \n",
       "812          524021               Hegmann and Sons  FK-71853    Shirt   \n",
       "875          299771          Kuphal, Zieme and Kub  LW-86841    Shoes   \n",
       "935          305803     Davis, Kshlerin and Reilly  FK-71853    Shirt   \n",
       "996          850140                      Kunze Inc  GS-86623    Shoes   \n",
       "\n",
       "     quantity  unit price  ext price                date  \n",
       "1          19       53.62    1018.78 2014-07-29 02:10:44  \n",
       "59         16       66.61    1065.76 2014-07-25 22:56:12  \n",
       "120        16       80.82    1293.12 2014-08-19 00:53:50  \n",
       "174        20       45.32     906.40 2014-07-06 22:06:23  \n",
       "234        10       31.81     318.10 2013-11-18 23:11:16  \n",
       "298        17       75.69    1286.73 2013-11-25 02:35:28  \n",
       "361        13       77.78    1011.14 2013-11-30 17:23:21  \n",
       "432        13       45.97     597.61 2014-07-05 08:56:46  \n",
       "493        15       80.59    1208.85 2014-10-05 18:13:24  \n",
       "561        12       19.81     237.72 2014-10-12 12:33:27  \n",
       "622        17       36.81     625.77 2013-12-05 23:10:45  \n",
       "685        14       40.64     568.96 2014-10-21 15:55:43  \n",
       "743        15       21.39     320.85 2013-12-07 12:59:30  \n",
       "812         9       87.07     783.63 2014-09-10 21:37:02  \n",
       "875        11       87.09     957.99 2013-10-22 16:08:40  \n",
       "935        20       11.96     239.20 2014-09-04 18:27:56  \n",
       "996        16       19.66     314.56 2014-05-03 21:18:15  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.category.str.startswith('S')][::50]#head(17)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GROUPBY ->Group the custommer by name and sum their data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>account number</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Berge LLC</th>\n",
       "      <td>38215944</td>\n",
       "      <td>522</td>\n",
       "      <td>3076.92</td>\n",
       "      <td>30064.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll PLC</th>\n",
       "      <td>16918113</td>\n",
       "      <td>677</td>\n",
       "      <td>2947.25</td>\n",
       "      <td>35934.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cole-Eichmann</th>\n",
       "      <td>50758617</td>\n",
       "      <td>538</td>\n",
       "      <td>2833.00</td>\n",
       "      <td>30435.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davis, Kshlerin and Reilly</th>\n",
       "      <td>12537923</td>\n",
       "      <td>379</td>\n",
       "      <td>2138.16</td>\n",
       "      <td>19054.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ernser, Cruickshank and Lind</th>\n",
       "      <td>26112918</td>\n",
       "      <td>455</td>\n",
       "      <td>2854.91</td>\n",
       "      <td>28089.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gorczany-Hahn</th>\n",
       "      <td>4835796</td>\n",
       "      <td>440</td>\n",
       "      <td>2225.71</td>\n",
       "      <td>22207.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamill-Hackett</th>\n",
       "      <td>29781268</td>\n",
       "      <td>419</td>\n",
       "      <td>2582.64</td>\n",
       "      <td>23433.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hegmann and Sons</th>\n",
       "      <td>30393218</td>\n",
       "      <td>606</td>\n",
       "      <td>3413.61</td>\n",
       "      <td>35213.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heidenreich-Bosco</th>\n",
       "      <td>3920880</td>\n",
       "      <td>431</td>\n",
       "      <td>2322.30</td>\n",
       "      <td>25428.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huel-Haag</th>\n",
       "      <td>13108980</td>\n",
       "      <td>358</td>\n",
       "      <td>2498.97</td>\n",
       "      <td>21087.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kerluke, Reilly and Bechtelar</th>\n",
       "      <td>29323060</td>\n",
       "      <td>556</td>\n",
       "      <td>2578.55</td>\n",
       "      <td>27389.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kihn, McClure and Denesik</th>\n",
       "      <td>43971714</td>\n",
       "      <td>638</td>\n",
       "      <td>3487.45</td>\n",
       "      <td>38935.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kilback-Gerlach</th>\n",
       "      <td>32037795</td>\n",
       "      <td>472</td>\n",
       "      <td>2650.98</td>\n",
       "      <td>26987.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koelpin PLC</th>\n",
       "      <td>10666727</td>\n",
       "      <td>497</td>\n",
       "      <td>2687.66</td>\n",
       "      <td>26811.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kunze Inc</th>\n",
       "      <td>45907560</td>\n",
       "      <td>605</td>\n",
       "      <td>3025.18</td>\n",
       "      <td>34406.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kuphal, Zieme and Kub</th>\n",
       "      <td>15588092</td>\n",
       "      <td>552</td>\n",
       "      <td>2678.55</td>\n",
       "      <td>27031.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Senger, Upton and Breitenberg</th>\n",
       "      <td>54834600</td>\n",
       "      <td>566</td>\n",
       "      <td>3023.81</td>\n",
       "      <td>29577.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Volkman, Goyette and Lemke</th>\n",
       "      <td>36022128</td>\n",
       "      <td>538</td>\n",
       "      <td>2832.62</td>\n",
       "      <td>32006.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waelchi-Fahey</th>\n",
       "      <td>35605764</td>\n",
       "      <td>501</td>\n",
       "      <td>3017.41</td>\n",
       "      <td>28968.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waters-Walker</th>\n",
       "      <td>4667800</td>\n",
       "      <td>578</td>\n",
       "      <td>3303.95</td>\n",
       "      <td>36778.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               account number  quantity  unit price  ext price\n",
       "name                                                                          \n",
       "Berge LLC                            38215944       522     3076.92   30064.87\n",
       "Carroll PLC                          16918113       677     2947.25   35934.31\n",
       "Cole-Eichmann                        50758617       538     2833.00   30435.42\n",
       "Davis, Kshlerin and Reilly           12537923       379     2138.16   19054.76\n",
       "Ernser, Cruickshank and Lind         26112918       455     2854.91   28089.02\n",
       "Gorczany-Hahn                         4835796       440     2225.71   22207.90\n",
       "Hamill-Hackett                       29781268       419     2582.64   23433.78\n",
       "Hegmann and Sons                     30393218       606     3413.61   35213.72\n",
       "Heidenreich-Bosco                     3920880       431     2322.30   25428.29\n",
       "Huel-Haag                            13108980       358     2498.97   21087.88\n",
       "Kerluke, Reilly and Bechtelar        29323060       556     2578.55   27389.43\n",
       "Kihn, McClure and Denesik            43971714       638     3487.45   38935.29\n",
       "Kilback-Gerlach                      32037795       472     2650.98   26987.20\n",
       "Koelpin PLC                          10666727       497     2687.66   26811.66\n",
       "Kunze Inc                            45907560       605     3025.18   34406.54\n",
       "Kuphal, Zieme and Kub                15588092       552     2678.55   27031.86\n",
       "Senger, Upton and Breitenberg        54834600       566     3023.81   29577.46\n",
       "Volkman, Goyette and Lemke           36022128       538     2832.62   32006.87\n",
       "Waelchi-Fahey                        35605764       501     3017.41   28968.68\n",
       "Waters-Walker                         4667800       578     3303.95   36778.96"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abc=data.groupby('name')\n",
    "total=abc.sum()\n",
    "total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Berge LLC</th>\n",
       "      <td>522</td>\n",
       "      <td>3076.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll PLC</th>\n",
       "      <td>677</td>\n",
       "      <td>2947.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cole-Eichmann</th>\n",
       "      <td>538</td>\n",
       "      <td>2833.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davis, Kshlerin and Reilly</th>\n",
       "      <td>379</td>\n",
       "      <td>2138.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ernser, Cruickshank and Lind</th>\n",
       "      <td>455</td>\n",
       "      <td>2854.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gorczany-Hahn</th>\n",
       "      <td>440</td>\n",
       "      <td>2225.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamill-Hackett</th>\n",
       "      <td>419</td>\n",
       "      <td>2582.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hegmann and Sons</th>\n",
       "      <td>606</td>\n",
       "      <td>3413.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heidenreich-Bosco</th>\n",
       "      <td>431</td>\n",
       "      <td>2322.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huel-Haag</th>\n",
       "      <td>358</td>\n",
       "      <td>2498.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kerluke, Reilly and Bechtelar</th>\n",
       "      <td>556</td>\n",
       "      <td>2578.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kihn, McClure and Denesik</th>\n",
       "      <td>638</td>\n",
       "      <td>3487.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kilback-Gerlach</th>\n",
       "      <td>472</td>\n",
       "      <td>2650.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koelpin PLC</th>\n",
       "      <td>497</td>\n",
       "      <td>2687.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kunze Inc</th>\n",
       "      <td>605</td>\n",
       "      <td>3025.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kuphal, Zieme and Kub</th>\n",
       "      <td>552</td>\n",
       "      <td>2678.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Senger, Upton and Breitenberg</th>\n",
       "      <td>566</td>\n",
       "      <td>3023.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Volkman, Goyette and Lemke</th>\n",
       "      <td>538</td>\n",
       "      <td>2832.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waelchi-Fahey</th>\n",
       "      <td>501</td>\n",
       "      <td>3017.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waters-Walker</th>\n",
       "      <td>578</td>\n",
       "      <td>3303.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               quantity  unit price\n",
       "name                                               \n",
       "Berge LLC                           522     3076.92\n",
       "Carroll PLC                         677     2947.25\n",
       "Cole-Eichmann                       538     2833.00\n",
       "Davis, Kshlerin and Reilly          379     2138.16\n",
       "Ernser, Cruickshank and Lind        455     2854.91\n",
       "Gorczany-Hahn                       440     2225.71\n",
       "Hamill-Hackett                      419     2582.64\n",
       "Hegmann and Sons                    606     3413.61\n",
       "Heidenreich-Bosco                   431     2322.30\n",
       "Huel-Haag                           358     2498.97\n",
       "Kerluke, Reilly and Bechtelar       556     2578.55\n",
       "Kihn, McClure and Denesik           638     3487.45\n",
       "Kilback-Gerlach                     472     2650.98\n",
       "Koelpin PLC                         497     2687.66\n",
       "Kunze Inc                           605     3025.18\n",
       "Kuphal, Zieme and Kub               552     2678.55\n",
       "Senger, Upton and Breitenberg       566     3023.81\n",
       "Volkman, Goyette and Lemke          538     2832.62\n",
       "Waelchi-Fahey                       501     3017.41\n",
       "Waters-Walker                       578     3303.95"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xyz=customer.groupby('name')\n",
    "total=xyz.sum()#sum(),mean(),max()\n",
    "total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>quantity</th>\n",
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       "      <th>name</th>\n",
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       "  <tbody>\n",
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       "      <th>Kerluke, Reilly and Bechtelar</th>\n",
       "      <td>556</td>\n",
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       "    <tr>\n",
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       "      <th>Kilback-Gerlach</th>\n",
       "      <td>472</td>\n",
       "      <td>2650.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koelpin PLC</th>\n",
       "      <td>497</td>\n",
       "      <td>2687.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kunze Inc</th>\n",
       "      <td>605</td>\n",
       "      <td>3025.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kuphal, Zieme and Kub</th>\n",
       "      <td>552</td>\n",
       "      <td>2678.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               quantity  unit price\n",
       "name                                               \n",
       "Kerluke, Reilly and Bechtelar       556     2578.55\n",
       "Kihn, McClure and Denesik           638     3487.45\n",
       "Kilback-Gerlach                     472     2650.98\n",
       "Koelpin PLC                         497     2687.66\n",
       "Kunze Inc                           605     3025.18\n",
       "Kuphal, Zieme and Kub               552     2678.55"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#filter\n",
    "total.filter(regex='^K',axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "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>name</th>\n",
       "      <th>Berge LLC</th>\n",
       "      <th>Carroll PLC</th>\n",
       "      <th>Cole-Eichmann</th>\n",
       "      <th>Davis, Kshlerin and Reilly</th>\n",
       "      <th>Ernser, Cruickshank and Lind</th>\n",
       "      <th>Gorczany-Hahn</th>\n",
       "      <th>Hamill-Hackett</th>\n",
       "      <th>Hegmann and Sons</th>\n",
       "      <th>Heidenreich-Bosco</th>\n",
       "      <th>Huel-Haag</th>\n",
       "      <th>Kerluke, Reilly and Bechtelar</th>\n",
       "      <th>Kihn, McClure and Denesik</th>\n",
       "      <th>Kilback-Gerlach</th>\n",
       "      <th>Koelpin PLC</th>\n",
       "      <th>Kunze Inc</th>\n",
       "      <th>Kuphal, Zieme and Kub</th>\n",
       "      <th>Senger, Upton and Breitenberg</th>\n",
       "      <th>Volkman, Goyette and Lemke</th>\n",
       "      <th>Waelchi-Fahey</th>\n",
       "      <th>Waters-Walker</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>quantity</th>\n",
       "      <td>522.00</td>\n",
       "      <td>677.00</td>\n",
       "      <td>538.0</td>\n",
       "      <td>379.00</td>\n",
       "      <td>455.00</td>\n",
       "      <td>440.00</td>\n",
       "      <td>419.00</td>\n",
       "      <td>606.00</td>\n",
       "      <td>431.0</td>\n",
       "      <td>358.00</td>\n",
       "      <td>556.00</td>\n",
       "      <td>638.00</td>\n",
       "      <td>472.00</td>\n",
       "      <td>497.00</td>\n",
       "      <td>605.00</td>\n",
       "      <td>552.00</td>\n",
       "      <td>566.00</td>\n",
       "      <td>538.00</td>\n",
       "      <td>501.00</td>\n",
       "      <td>578.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit price</th>\n",
       "      <td>3076.92</td>\n",
       "      <td>2947.25</td>\n",
       "      <td>2833.0</td>\n",
       "      <td>2138.16</td>\n",
       "      <td>2854.91</td>\n",
       "      <td>2225.71</td>\n",
       "      <td>2582.64</td>\n",
       "      <td>3413.61</td>\n",
       "      <td>2322.3</td>\n",
       "      <td>2498.97</td>\n",
       "      <td>2578.55</td>\n",
       "      <td>3487.45</td>\n",
       "      <td>2650.98</td>\n",
       "      <td>2687.66</td>\n",
       "      <td>3025.18</td>\n",
       "      <td>2678.55</td>\n",
       "      <td>3023.81</td>\n",
       "      <td>2832.62</td>\n",
       "      <td>3017.41</td>\n",
       "      <td>3303.95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "name        Berge LLC  Carroll PLC  Cole-Eichmann  Davis, Kshlerin and Reilly  \\\n",
       "quantity       522.00       677.00          538.0                      379.00   \n",
       "unit price    3076.92      2947.25         2833.0                     2138.16   \n",
       "\n",
       "name        Ernser, Cruickshank and Lind  Gorczany-Hahn  Hamill-Hackett  \\\n",
       "quantity                          455.00         440.00          419.00   \n",
       "unit price                       2854.91        2225.71         2582.64   \n",
       "\n",
       "name        Hegmann and Sons  Heidenreich-Bosco  Huel-Haag  \\\n",
       "quantity              606.00              431.0     358.00   \n",
       "unit price           3413.61             2322.3    2498.97   \n",
       "\n",
       "name        Kerluke, Reilly and Bechtelar  Kihn, McClure and Denesik  \\\n",
       "quantity                           556.00                     638.00   \n",
       "unit price                        2578.55                    3487.45   \n",
       "\n",
       "name        Kilback-Gerlach  Koelpin PLC  Kunze Inc  Kuphal, Zieme and Kub  \\\n",
       "quantity             472.00       497.00     605.00                 552.00   \n",
       "unit price          2650.98      2687.66    3025.18                2678.55   \n",
       "\n",
       "name        Senger, Upton and Breitenberg  Volkman, Goyette and Lemke  \\\n",
       "quantity                           566.00                      538.00   \n",
       "unit price                        3023.81                     2832.62   \n",
       "\n",
       "name        Waelchi-Fahey  Waters-Walker  \n",
       "quantity           501.00         578.00  \n",
       "unit price        3017.41        3303.95  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 'Berge LLC'),\n",
       " (1, 'Carroll PLC'),\n",
       " (2, 'Cole-Eichmann'),\n",
       " (3, 'Davis, Kshlerin and Reilly'),\n",
       " (4, 'Ernser, Cruickshank and Lind'),\n",
       " (5, 'Gorczany-Hahn'),\n",
       " (6, 'Hamill-Hackett'),\n",
       " (7, 'Hegmann and Sons'),\n",
       " (8, 'Heidenreich-Bosco'),\n",
       " (9, 'Huel-Haag'),\n",
       " (10, 'Kerluke, Reilly and Bechtelar'),\n",
       " (11, 'Kihn, McClure and Denesik'),\n",
       " (12, 'Kilback-Gerlach'),\n",
       " (13, 'Koelpin PLC'),\n",
       " (14, 'Kunze Inc'),\n",
       " (15, 'Kuphal, Zieme and Kub'),\n",
       " (16, 'Senger, Upton and Breitenberg'),\n",
       " (17, 'Volkman, Goyette and Lemke'),\n",
       " (18, 'Waelchi-Fahey'),\n",
       " (19, 'Waters-Walker')]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#filtering using re!\n",
    "list(enumerate(total.index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(0, 5), (1, 9), (2, 4)]\n"
     ]
    }
   ],
   "source": [
    "l=[5,9,4]\n",
    "print(list(enumerate(l)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "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>quantity</th>\n",
       "      <th>unit price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Gorczany-Hahn</th>\n",
       "      <td>440</td>\n",
       "      <td>2225.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamill-Hackett</th>\n",
       "      <td>419</td>\n",
       "      <td>2582.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hegmann and Sons</th>\n",
       "      <td>606</td>\n",
       "      <td>3413.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heidenreich-Bosco</th>\n",
       "      <td>431</td>\n",
       "      <td>2322.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huel-Haag</th>\n",
       "      <td>358</td>\n",
       "      <td>2498.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   quantity  unit price\n",
       "name                                   \n",
       "Gorczany-Hahn           440     2225.71\n",
       "Hamill-Hackett          419     2582.64\n",
       "Hegmann and Sons        606     3413.61\n",
       "Heidenreich-Bosco       431     2322.30\n",
       "Huel-Haag               358     2498.97"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "total.loc[[values for index,values in enumerate(total.index) if re.search(r'H[a-z]+',values)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "bar_plot=total.plot(kind='bar',legend=None, title='total sales',figsize=(16,7))\n",
    "bar_plot.set_xlabel(\"customer\")\n",
    "bar_plot.set_ylabel(\"sales($)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "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>name</th>\n",
       "      <th>category</th>\n",
       "      <th>ext price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carroll PLC</td>\n",
       "      <td>Belt</td>\n",
       "      <td>578.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Heidenreich-Bosco</td>\n",
       "      <td>Shoes</td>\n",
       "      <td>1018.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kerluke, Reilly and Bechtelar</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>289.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Waters-Walker</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>413.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Waelchi-Fahey</td>\n",
       "      <td>Shirt</td>\n",
       "      <td>1793.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            name category  ext price\n",
       "0                    Carroll PLC     Belt     578.24\n",
       "1              Heidenreich-Bosco    Shoes    1018.78\n",
       "2  Kerluke, Reilly and Bechtelar    Shirt     289.92\n",
       "3                  Waters-Walker    Shirt     413.40\n",
       "4                  Waelchi-Fahey    Shirt    1793.52"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#groupby----unstack\n",
    "customer=data[['name','category','ext price']]\n",
    "customer.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "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></th>\n",
       "      <th>ext price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Berge LLC</th>\n",
       "      <th>Belt</th>\n",
       "      <td>6033.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>9670.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>14361.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Carroll PLC</th>\n",
       "      <th>Belt</th>\n",
       "      <td>9359.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>13717.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>12857.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Cole-Eichmann</th>\n",
       "      <th>Belt</th>\n",
       "      <td>8112.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>14528.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>7794.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Davis, Kshlerin and Reilly</th>\n",
       "      <th>Belt</th>\n",
       "      <td>1604.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>7533.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>9917.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Ernser, Cruickshank and Lind</th>\n",
       "      <th>Belt</th>\n",
       "      <td>5894.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>16944.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>5250.45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       ext price\n",
       "name                         category           \n",
       "Berge LLC                    Belt        6033.53\n",
       "                             Shirt       9670.24\n",
       "                             Shoes      14361.10\n",
       "Carroll PLC                  Belt        9359.26\n",
       "                             Shirt      13717.61\n",
       "                             Shoes      12857.44\n",
       "Cole-Eichmann                Belt        8112.70\n",
       "                             Shirt      14528.01\n",
       "                             Shoes       7794.71\n",
       "Davis, Kshlerin and Reilly   Belt        1604.13\n",
       "                             Shirt       7533.03\n",
       "                             Shoes       9917.60\n",
       "Ernser, Cruickshank and Lind Belt        5894.38\n",
       "                             Shirt      16944.19\n",
       "                             Shoes       5250.45"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_group=customer.groupby(['name','category']).sum()\n",
    "category_group.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">ext price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <th>Belt</th>\n",
       "      <th>Shirt</th>\n",
       "      <th>Shoes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Berge LLC</th>\n",
       "      <td>6033.53</td>\n",
       "      <td>9670.24</td>\n",
       "      <td>14361.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carroll PLC</th>\n",
       "      <td>9359.26</td>\n",
       "      <td>13717.61</td>\n",
       "      <td>12857.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cole-Eichmann</th>\n",
       "      <td>8112.70</td>\n",
       "      <td>14528.01</td>\n",
       "      <td>7794.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davis, Kshlerin and Reilly</th>\n",
       "      <td>1604.13</td>\n",
       "      <td>7533.03</td>\n",
       "      <td>9917.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ernser, Cruickshank and Lind</th>\n",
       "      <td>5894.38</td>\n",
       "      <td>16944.19</td>\n",
       "      <td>5250.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gorczany-Hahn</th>\n",
       "      <td>3642.48</td>\n",
       "      <td>12576.83</td>\n",
       "      <td>5988.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamill-Hackett</th>\n",
       "      <td>1609.74</td>\n",
       "      <td>8880.04</td>\n",
       "      <td>12944.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hegmann and Sons</th>\n",
       "      <td>4909.38</td>\n",
       "      <td>16774.47</td>\n",
       "      <td>13529.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heidenreich-Bosco</th>\n",
       "      <td>6262.94</td>\n",
       "      <td>5965.25</td>\n",
       "      <td>13200.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Huel-Haag</th>\n",
       "      <td>2219.51</td>\n",
       "      <td>11944.01</td>\n",
       "      <td>6924.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kerluke, Reilly and Bechtelar</th>\n",
       "      <td>4102.11</td>\n",
       "      <td>12958.23</td>\n",
       "      <td>10329.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kihn, McClure and Denesik</th>\n",
       "      <td>10116.90</td>\n",
       "      <td>18956.35</td>\n",
       "      <td>9862.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kilback-Gerlach</th>\n",
       "      <td>2863.40</td>\n",
       "      <td>9904.85</td>\n",
       "      <td>14218.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Koelpin PLC</th>\n",
       "      <td>5327.96</td>\n",
       "      <td>7908.28</td>\n",
       "      <td>13575.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kunze Inc</th>\n",
       "      <td>4264.59</td>\n",
       "      <td>15638.87</td>\n",
       "      <td>14503.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kuphal, Zieme and Kub</th>\n",
       "      <td>2009.69</td>\n",
       "      <td>12101.14</td>\n",
       "      <td>12921.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Senger, Upton and Breitenberg</th>\n",
       "      <td>9509.88</td>\n",
       "      <td>7659.70</td>\n",
       "      <td>12407.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Volkman, Goyette and Lemke</th>\n",
       "      <td>4429.01</td>\n",
       "      <td>12791.27</td>\n",
       "      <td>14786.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waelchi-Fahey</th>\n",
       "      <td>8285.72</td>\n",
       "      <td>11689.05</td>\n",
       "      <td>8993.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waters-Walker</th>\n",
       "      <td>5957.24</td>\n",
       "      <td>18633.71</td>\n",
       "      <td>12188.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              ext price                    \n",
       "category                           Belt     Shirt     Shoes\n",
       "name                                                       \n",
       "Berge LLC                       6033.53   9670.24  14361.10\n",
       "Carroll PLC                     9359.26  13717.61  12857.44\n",
       "Cole-Eichmann                   8112.70  14528.01   7794.71\n",
       "Davis, Kshlerin and Reilly      1604.13   7533.03   9917.60\n",
       "Ernser, Cruickshank and Lind    5894.38  16944.19   5250.45\n",
       "Gorczany-Hahn                   3642.48  12576.83   5988.59\n",
       "Hamill-Hackett                  1609.74   8880.04  12944.00\n",
       "Hegmann and Sons                4909.38  16774.47  13529.87\n",
       "Heidenreich-Bosco               6262.94   5965.25  13200.10\n",
       "Huel-Haag                       2219.51  11944.01   6924.36\n",
       "Kerluke, Reilly and Bechtelar   4102.11  12958.23  10329.09\n",
       "Kihn, McClure and Denesik      10116.90  18956.35   9862.04\n",
       "Kilback-Gerlach                 2863.40   9904.85  14218.95\n",
       "Koelpin PLC                     5327.96   7908.28  13575.42\n",
       "Kunze Inc                       4264.59  15638.87  14503.08\n",
       "Kuphal, Zieme and Kub           2009.69  12101.14  12921.03\n",
       "Senger, Upton and Breitenberg   9509.88   7659.70  12407.88\n",
       "Volkman, Goyette and Lemke      4429.01  12791.27  14786.59\n",
       "Waelchi-Fahey                   8285.72  11689.05   8993.91\n",
       "Waters-Walker                   5957.24  18633.71  12188.01"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_group.unstack()#original data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['account number', 'name', 'sku', 'category', 'quantity', 'unit price',\n",
       "       'ext price', 'date'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "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>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>578.24</td>\n",
       "      <td>2014-09-27 07:13:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1018.78</td>\n",
       "      <td>2014-07-29 02:10:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>289.92</td>\n",
       "      <td>2014-03-01 10:51:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>413.40</td>\n",
       "      <td>2013-11-17 20:41:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1793.52</td>\n",
       "      <td>2014-01-03 08:14:27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ext price                date\n",
       "0     578.24 2014-09-27 07:13:03\n",
       "1    1018.78 2014-07-29 02:10:44\n",
       "2     289.92 2014-03-01 10:51:24\n",
       "3     413.40 2013-11-17 20:41:11\n",
       "4    1793.52 2014-01-03 08:14:27"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purches=data[['ext price','date']]\n",
    "purches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'DataFrame' object has no attribute 'set_ylabel'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-32-6a40a9794cca>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mpurches_plot\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_title\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"purches pattern\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mpurches_plot\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"order amount($)\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mpurches\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_ylabel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"no. of order:\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   5272\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5273\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5274\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5275\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5276\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'set_ylabel'"
     ]
    },
    {
     "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": [
    "purches_plot=purches['ext price'].hist(bins=20) \n",
    "purches_plot.set_title(\"purches pattern\")\n",
    "purches_plot.set_xlabel(\"order amount($)\")\n",
    "purches.set_ylabel(\"no. of order:\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "purches=data[data['ext price']<=300][['category','ext price']]\n",
    "purches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PIVOT TABLE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivot1=pd.pivot_table(data,index=['name','category'],values=['quantity'])\n",
    "pivot1.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[data['name'].str.contains(r'Ca')&(data['category']=='shirt')]['quantity'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivot1.loc[['waters-waker','category']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>len</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>ext price</th>\n",
       "      <th>ext price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th>category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Berge LLC</th>\n",
       "      <th>Belt</th>\n",
       "      <td>670.392222</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>483.512000</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>624.395652</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Carroll PLC</th>\n",
       "      <th>Belt</th>\n",
       "      <td>668.518571</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>623.527727</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>612.259048</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Cole-Eichmann</th>\n",
       "      <th>Belt</th>\n",
       "      <td>624.053846</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>691.810000</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>458.512353</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Davis, Kshlerin and Reilly</th>\n",
       "      <th>Belt</th>\n",
       "      <td>267.355000</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>470.814375</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>521.978947</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Ernser, Cruickshank and Lind</th>\n",
       "      <th>Belt</th>\n",
       "      <td>654.931111</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>706.007917</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>375.032143</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Gorczany-Hahn</th>\n",
       "      <th>Belt</th>\n",
       "      <td>303.540000</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>598.896667</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>665.398889</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Hamill-Hackett</th>\n",
       "      <th>Belt</th>\n",
       "      <td>402.435000</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>522.355294</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>562.782609</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Hegmann and Sons</th>\n",
       "      <th>Belt</th>\n",
       "      <td>490.938000</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>645.171923</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>614.994091</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Heidenreich-Bosco</th>\n",
       "      <th>Belt</th>\n",
       "      <td>626.294000</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>596.525000</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>660.005000</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Huel-Haag</th>\n",
       "      <th>Belt</th>\n",
       "      <td>246.612222</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>628.632105</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>461.624000</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Kerluke, Reilly and Bechtelar</th>\n",
       "      <th>Belt</th>\n",
       "      <td>512.763750</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>617.058571</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>449.090870</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Kihn, McClure and Denesik</th>\n",
       "      <th>Belt</th>\n",
       "      <td>843.075000</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>702.087037</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>519.054737</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Kilback-Gerlach</th>\n",
       "      <th>Belt</th>\n",
       "      <td>477.233333</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>582.638235</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>646.315909</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Koelpin PLC</th>\n",
       "      <th>Belt</th>\n",
       "      <td>380.568571</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>527.218667</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>565.642500</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Kunze Inc</th>\n",
       "      <th>Belt</th>\n",
       "      <td>710.765000</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>625.554800</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>630.568696</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Kuphal, Zieme and Kub</th>\n",
       "      <th>Belt</th>\n",
       "      <td>502.422500</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>550.051818</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>496.962692</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Senger, Upton and Breitenberg</th>\n",
       "      <th>Belt</th>\n",
       "      <td>500.520000</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>450.570588</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>539.473043</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Volkman, Goyette and Lemke</th>\n",
       "      <th>Belt</th>\n",
       "      <td>553.626250</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>639.563500</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>739.329500</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Waelchi-Fahey</th>\n",
       "      <th>Belt</th>\n",
       "      <td>487.395294</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>584.452500</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>529.053529</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Waters-Walker</th>\n",
       "      <th>Belt</th>\n",
       "      <td>992.873333</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shirt</th>\n",
       "      <td>776.404583</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shoes</th>\n",
       "      <td>609.400500</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              mean       len\n",
       "                                         ext price ext price\n",
       "name                          category                      \n",
       "Berge LLC                     Belt      670.392222       9.0\n",
       "                              Shirt     483.512000      20.0\n",
       "                              Shoes     624.395652      23.0\n",
       "Carroll PLC                   Belt      668.518571      14.0\n",
       "                              Shirt     623.527727      22.0\n",
       "                              Shoes     612.259048      21.0\n",
       "Cole-Eichmann                 Belt      624.053846      13.0\n",
       "                              Shirt     691.810000      21.0\n",
       "                              Shoes     458.512353      17.0\n",
       "Davis, Kshlerin and Reilly    Belt      267.355000       6.0\n",
       "                              Shirt     470.814375      16.0\n",
       "                              Shoes     521.978947      19.0\n",
       "Ernser, Cruickshank and Lind  Belt      654.931111       9.0\n",
       "                              Shirt     706.007917      24.0\n",
       "                              Shoes     375.032143      14.0\n",
       "Gorczany-Hahn                 Belt      303.540000      12.0\n",
       "                              Shirt     598.896667      21.0\n",
       "                              Shoes     665.398889       9.0\n",
       "Hamill-Hackett                Belt      402.435000       4.0\n",
       "                              Shirt     522.355294      17.0\n",
       "                              Shoes     562.782609      23.0\n",
       "Hegmann and Sons              Belt      490.938000      10.0\n",
       "                              Shirt     645.171923      26.0\n",
       "                              Shoes     614.994091      22.0\n",
       "Heidenreich-Bosco             Belt      626.294000      10.0\n",
       "                              Shirt     596.525000      10.0\n",
       "                              Shoes     660.005000      20.0\n",
       "Huel-Haag                     Belt      246.612222       9.0\n",
       "                              Shirt     628.632105      19.0\n",
       "                              Shoes     461.624000      15.0\n",
       "Kerluke, Reilly and Bechtelar Belt      512.763750       8.0\n",
       "                              Shirt     617.058571      21.0\n",
       "                              Shoes     449.090870      23.0\n",
       "Kihn, McClure and Denesik     Belt      843.075000      12.0\n",
       "                              Shirt     702.087037      27.0\n",
       "                              Shoes     519.054737      19.0\n",
       "Kilback-Gerlach               Belt      477.233333       6.0\n",
       "                              Shirt     582.638235      17.0\n",
       "                              Shoes     646.315909      22.0\n",
       "Koelpin PLC                   Belt      380.568571      14.0\n",
       "                              Shirt     527.218667      15.0\n",
       "                              Shoes     565.642500      24.0\n",
       "Kunze Inc                     Belt      710.765000       6.0\n",
       "                              Shirt     625.554800      25.0\n",
       "                              Shoes     630.568696      23.0\n",
       "Kuphal, Zieme and Kub         Belt      502.422500       4.0\n",
       "                              Shirt     550.051818      22.0\n",
       "                              Shoes     496.962692      26.0\n",
       "Senger, Upton and Breitenberg Belt      500.520000      19.0\n",
       "                              Shirt     450.570588      17.0\n",
       "                              Shoes     539.473043      23.0\n",
       "Volkman, Goyette and Lemke    Belt      553.626250       8.0\n",
       "                              Shirt     639.563500      20.0\n",
       "                              Shoes     739.329500      20.0\n",
       "Waelchi-Fahey                 Belt      487.395294      17.0\n",
       "                              Shirt     584.452500      20.0\n",
       "                              Shoes     529.053529      17.0\n",
       "Waters-Walker                 Belt      992.873333       6.0\n",
       "                              Shirt     776.404583      24.0\n",
       "                              Shoes     609.400500      20.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(data,index=['name','category'],values=['ext price'],aggfunc=[np.mean,len])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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