Bar_heat_maps.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>C/A</th>\n",
       "      <th>UNIT</th>\n",
       "      <th>SCP</th>\n",
       "      <th>STATION</th>\n",
       "      <th>LINENAME</th>\n",
       "      <th>DIVISION</th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DESC</th>\n",
       "      <th>ENTRIES</th>\n",
       "      <th>EXITS</th>\n",
       "      <th>STATION_LINENAME</th>\n",
       "      <th>DATETIME</th>\n",
       "      <th>DIFF_HRS</th>\n",
       "      <th>DIFF_ENTRIES</th>\n",
       "      <th>DIFF_EXITS</th>\n",
       "      <th>DAY</th>\n",
       "      <th>DIFF_HRS_ROUND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>35983</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>01:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699588</td>\n",
       "      <td>3509815</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 01:00:00</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35984</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>05:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699590</td>\n",
       "      <td>3509838</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 05:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35985</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>09:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699633</td>\n",
       "      <td>3509889</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 09:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>43.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35986</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699686</td>\n",
       "      <td>3509949</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 13:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>53.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35987</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>17:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699751</td>\n",
       "      <td>3510012</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 17:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>65.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index   C/A  UNIT       SCP     STATION LINENAME DIVISION        DATE  \\\n",
       "0  35983  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "1  35984  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "2  35985  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "3  35986  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "4  35987  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "\n",
       "       TIME     DESC  ENTRIES    EXITS STATION_LINENAME            DATETIME  \\\n",
       "0  01:00:00  REGULAR  2699588  3509815  (LIVONIA AV, L) 2019-07-06 01:00:00   \n",
       "1  05:00:00  REGULAR  2699590  3509838  (LIVONIA AV, L) 2019-07-06 05:00:00   \n",
       "2  09:00:00  REGULAR  2699633  3509889  (LIVONIA AV, L) 2019-07-06 09:00:00   \n",
       "3  13:00:00  REGULAR  2699686  3509949  (LIVONIA AV, L) 2019-07-06 13:00:00   \n",
       "4  17:00:00  REGULAR  2699751  3510012  (LIVONIA AV, L) 2019-07-06 17:00:00   \n",
       "\n",
       "  DIFF_HRS  DIFF_ENTRIES  DIFF_EXITS  DAY DIFF_HRS_ROUND  \n",
       "0      NaT           NaN         NaN    5            NaT  \n",
       "1 04:00:00           2.0        23.0    5              4  \n",
       "2 04:00:00          43.0        51.0    5              4  \n",
       "3 04:00:00          53.0        60.0    5              4  \n",
       "4 04:00:00          65.0        63.0    5              4  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pickle\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "final_df = pd.read_pickle('final_df.pkl')\n",
    "final_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_traffic = final_df[\"DIFF_ENTRIES\"] + final_df[\"DIFF_EXITS\"]\n",
    "final_df['TOTAL_TRAF'] = total_traffic\n",
    "station_ent_data = final_df.groupby(['STATION','TIME']).agg({'DIFF_ENTRIES':'sum'})\n",
    "station_ent_data1 = final_df.groupby(['STATION']).agg({'DIFF_ENTRIES':'sum'})\n",
    "station_ent_data2 = final_df.groupby(['STATION','TIME','DAY']).agg({'DIFF_ENTRIES':'median'})\n",
    "station_ent_data3 = final_df.groupby(['STATION','TIME','DAY']).agg({'DIFF_EXITS':'median'})\n",
    "station_ent_data4 = final_df.groupby(['STATION','TIME','DAY']).agg({'TOTAL_TRAF':'median'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>C/A</th>\n",
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       "      <th>SCP</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>35983</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
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       "      <td>01:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699588</td>\n",
       "      <td>3509815</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 01:00:00</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35984</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>05:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699590</td>\n",
       "      <td>3509838</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 05:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35985</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>09:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699633</td>\n",
       "      <td>3509889</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 09:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>43.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35986</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>13:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699686</td>\n",
       "      <td>3509949</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 13:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>53.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35987</td>\n",
       "      <td>H038</td>\n",
       "      <td>R350</td>\n",
       "      <td>00-00-00</td>\n",
       "      <td>LIVONIA AV</td>\n",
       "      <td>L</td>\n",
       "      <td>BMT</td>\n",
       "      <td>07/06/2019</td>\n",
       "      <td>17:00:00</td>\n",
       "      <td>REGULAR</td>\n",
       "      <td>2699751</td>\n",
       "      <td>3510012</td>\n",
       "      <td>(LIVONIA AV, L)</td>\n",
       "      <td>2019-07-06 17:00:00</td>\n",
       "      <td>04:00:00</td>\n",
       "      <td>65.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index   C/A  UNIT       SCP     STATION LINENAME DIVISION        DATE  \\\n",
       "0  35983  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "1  35984  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "2  35985  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "3  35986  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "4  35987  H038  R350  00-00-00  LIVONIA AV        L      BMT  07/06/2019   \n",
       "\n",
       "       TIME     DESC  ENTRIES    EXITS STATION_LINENAME            DATETIME  \\\n",
       "0  01:00:00  REGULAR  2699588  3509815  (LIVONIA AV, L) 2019-07-06 01:00:00   \n",
       "1  05:00:00  REGULAR  2699590  3509838  (LIVONIA AV, L) 2019-07-06 05:00:00   \n",
       "2  09:00:00  REGULAR  2699633  3509889  (LIVONIA AV, L) 2019-07-06 09:00:00   \n",
       "3  13:00:00  REGULAR  2699686  3509949  (LIVONIA AV, L) 2019-07-06 13:00:00   \n",
       "4  17:00:00  REGULAR  2699751  3510012  (LIVONIA AV, L) 2019-07-06 17:00:00   \n",
       "\n",
       "  DIFF_HRS  DIFF_ENTRIES  DIFF_EXITS  DAY DIFF_HRS_ROUND  TOTAL_TRAF  \n",
       "0      NaT           NaN         NaN    5            NaT         NaN  \n",
       "1 04:00:00           2.0        23.0    5              4        25.0  \n",
       "2 04:00:00          43.0        51.0    5              4        94.0  \n",
       "3 04:00:00          53.0        60.0    5              4       113.0  \n",
       "4 04:00:00          65.0        63.0    5              4       128.0  "
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                TIME  DAY  DIFF_EXITS\n",
      "STATION                              \n",
      "LIVONIA AV  01:00:00    0        29.0\n",
      "LIVONIA AV  01:00:00    1        40.0\n",
      "LIVONIA AV  01:00:00    2        47.0\n",
      "LIVONIA AV  01:00:00    3        39.0\n",
      "LIVONIA AV  01:00:00    4        47.0\n",
      "LIVONIA AV  01:00:00    5        54.0\n",
      "LIVONIA AV  01:00:00    6        40.0\n",
      "LIVONIA AV  04:55:40    6        11.0\n",
      "LIVONIA AV  05:00:00    0         8.0\n",
      "LIVONIA AV  05:00:00    1         9.0\n",
      "LIVONIA AV  05:00:00    2        11.0\n",
      "LIVONIA AV  05:00:00    3        10.0\n",
      "LIVONIA AV  05:00:00    4        10.0\n",
      "LIVONIA AV  05:00:00    5        12.0\n",
      "LIVONIA AV  05:00:00    6        12.0\n",
      "LIVONIA AV  09:00:00    0        91.0\n",
      "LIVONIA AV  09:00:00    1        99.0\n",
      "LIVONIA AV  09:00:00    2       103.0\n",
      "LIVONIA AV  09:00:00    3       103.0\n",
      "LIVONIA AV  09:00:00    4        99.0\n",
      "LIVONIA AV  09:00:00    5        41.0\n",
      "LIVONIA AV  09:00:00    6        14.0\n",
      "LIVONIA AV  10:03:47    0        26.0\n",
      "LIVONIA AV  13:00:00    0        78.0\n",
      "LIVONIA AV  13:00:00    1        78.0\n",
      "LIVONIA AV  13:00:00    2        86.0\n",
      "LIVONIA AV  13:00:00    3        76.0\n",
      "LIVONIA AV  13:00:00    4        82.0\n",
      "LIVONIA AV  13:00:00    5        54.0\n",
      "LIVONIA AV  13:00:00    6        32.5\n",
      "LIVONIA AV  17:00:00    0       110.0\n",
      "LIVONIA AV  17:00:00    1       110.0\n",
      "LIVONIA AV  17:00:00    2       124.0\n",
      "LIVONIA AV  17:00:00    3       116.5\n",
      "LIVONIA AV  17:00:00    4       119.0\n",
      "LIVONIA AV  17:00:00    5        63.0\n",
      "LIVONIA AV  17:00:00    6        48.0\n",
      "LIVONIA AV  21:00:00    0       129.0\n",
      "LIVONIA AV  21:00:00    1       135.0\n",
      "LIVONIA AV  21:00:00    2       137.0\n",
      "LIVONIA AV  21:00:00    3       132.0\n",
      "LIVONIA AV  21:00:00    4       128.0\n",
      "LIVONIA AV  21:00:00    5        56.0\n",
      "LIVONIA AV  21:00:00    6        48.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "final_df4 = station_ent_data2.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = station_ent_data3.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "#plt.plot(final_df4.loc[:,'TIME'],final_df4.loc[:,'DIFF_ENTRIES'])\n",
    "final_df4 = final_df4.loc['LIVONIA AV']\n",
    "final_df5 = final_df5.loc['LIVONIA AV']\n",
    "print(final_df5)\n",
    "final_df4 = final_df4.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "final_df5 = final_df5.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "final_df4.drop(['10:03:47', '04:55:40'], inplace = True)\n",
    "final_df5.drop(['10:03:47', '04:55:40'], inplace = True)\n",
    "final_df4 = final_df4.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = final_df5.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "\n",
    "final_df4 = final_df4.replace(['01:00:00','05:00:00','09:00:00','13:00:00','17:00:00','21:00:00'],[0, 2.5, 5, 7.5, 10, 12.5])\n",
    "r1 = final_df4.loc[:,'TIME']\n",
    "r2 = [x + 1 for x in r1]\n",
    "\n",
    "plt.bar(r1,final_df5.loc[:,'DIFF_EXITS'], label='EXITS')\n",
    "plt.bar(r2,final_df4.loc[:,'DIFF_ENTRIES'], label='ENTRIES')\n",
    "plt.xticks([.5, 3, 5.5, 8, 10.5, 13],['01:00:00', '05:00:00', '09:00:00', '13:00:00', '17:00:00','21:00:00'])\n",
    "plt.legend(['EXITS','ENTRIES'])\n",
    "plt.xlabel('TIMES')\n",
    "plt.title('Livonia Avenue')\n",
    "plt.savefig('Livonia Avenue')\n",
    "# list_times = []\n",
    "# for i in range(final_df4.shape[0]):\n",
    "#     final_df5 = final_df4.reset_index().set_index('DAY')\n",
    "#     list1 = []\n",
    "#     final_df5 = final_df5.loc[i]\n",
    "#     list1 = final_df5.DIFF_ENTRIES.tolist()\n",
    "#     list_times.append(list1)\n",
    "# print(final_df5)\n",
    "# print(list_times[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "final_df4 = station_ent_data2.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = station_ent_data3.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "#plt.plot(final_df4.loc[:,'TIME'],final_df4.loc[:,'DIFF_ENTRIES'])\n",
    "final_df4 = final_df4.loc['EAST BROADWAY']\n",
    "final_df5 = final_df5.loc['EAST BROADWAY']\n",
    "final_df4 = final_df4.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "final_df5 = final_df5.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "\n",
    "final_df4.drop(['10:05:49', '06:58:54','07:01:35','07:00:14','06:57:34','06:54:53','06:56:13', '06:49:30','06:52:12','06:53:33', '06:50:52', '09:26:36' ], inplace = True)\n",
    "final_df5.drop(['10:05:49', '06:58:54','07:01:35','07:00:14','06:57:34','06:54:53','06:56:13', '06:49:30','06:52:12','06:53:33', '06:50:52', '09:26:36' ], inplace = True)\n",
    "final_df4 = final_df4.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = final_df5.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "\n",
    "final_df4 = final_df4.replace(['00:00:00','04:00:00','08:00:00','12:00:00','16:00:00','20:00:00'],[0, 2.5, 5, 7.5, 10, 12.5])\n",
    "r1 = final_df4.loc[:,'TIME']\n",
    "r2 = [x + 1 for x in r1]\n",
    "\n",
    "plt.bar(r1,final_df5.loc[:,'DIFF_EXITS'], label='EXITS')\n",
    "plt.bar(r2,final_df4.loc[:,'DIFF_ENTRIES'], label='ENTRIES')\n",
    "plt.xticks([.5, 3, 5.5, 8, 10.5, 13],['00:00:00', '04:00:00', '08:00:00', '12:00:00', '16:00:00','20:00:00'])\n",
    "plt.legend(['EXITS','ENTRIES'])\n",
    "plt.xlabel('TIMES')\n",
    "plt.title('East Broadway')\n",
    "plt.savefig('East Broadway')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "final_df4 = station_ent_data2.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = station_ent_data3.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "#plt.plot(final_df4.loc[:,'TIME'],final_df4.loc[:,'DIFF_ENTRIES'])\n",
    "final_df4 = final_df4.loc['103 ST']\n",
    "final_df5 = final_df5.loc['103 ST']\n",
    "final_df4 = final_df4.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "final_df5 = final_df5.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "final_df4.drop(['14:06:54','08:56:17','08:06:06', '08:17:24'], inplace = True)\n",
    "final_df5.drop(['14:06:54','08:56:17','08:06:06', '08:17:24'], inplace = True)\n",
    "final_df4 = final_df4.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df5 = final_df5.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "\n",
    "final_df4 = final_df4.replace(['01:00:00','05:00:00','09:00:00','13:00:00','17:00:00','21:00:00'],[0, 2.5, 5, 7.5, 10, 12.5])\n",
    "\n",
    "r1 = final_df4.loc[:,'TIME']\n",
    "r2 = [x + 1 for x in r1]\n",
    "\n",
    "plt.bar(r1,final_df5.loc[:,'DIFF_EXITS'], label='EXITS')\n",
    "plt.bar(r2,final_df4.loc[:,'DIFF_ENTRIES'], label='ENTRIES')\n",
    "plt.xticks([.5, 3, 5.5, 8, 10.5, 13],['01:00:00', '05:00:00', '09:00:00', '13:00:00', '17:00:00','21:00:00'])\n",
    "plt.legend(['EXITS','ENTRIES'], loc=2 )\n",
    "plt.xlabel('TIMES')\n",
    "plt.title('103 ST')\n",
    "plt.savefig('103 ST')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        STATION      TIME  TOTAL_TRAF\n",
      "DAY                                  \n",
      "6    LIVONIA AV  01:00:00        62.0\n",
      "6    LIVONIA AV  05:00:00        19.0\n",
      "6    LIVONIA AV  09:00:00        44.0\n",
      "6    LIVONIA AV  13:00:00        68.0\n",
      "6    LIVONIA AV  17:00:00        96.0\n",
      "6    LIVONIA AV  21:00:00        86.0\n",
      "[[50.0, 14.0, 255.0, 134.0, 209.0, 214.0], [63.0, 17.0, 270.0, 160.0, 210.0, 222.0], [65.0, 19.0, 285.0, 169.0, 228.0, 221.0], [61.0, 18.0, 283.0, 158.0, 228.5, 237.0], [72.0, 18.0, 250.0, 163.0, 234.0, 216.0], [74.5, 22.0, 81.0, 98.0, 117.0, 106.0], [62.0, 19.0, 44.0, 68.0, 96.0, 86.0]]\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWAAAAEICAYAAABhxi57AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAdW0lEQVR4nO3de5xdZX3v8c83IYAkBIhczA0CGLXAQaDRoigHhSOCreAFhFaJiJ3aqkDVcwp4KqLFaluxWs9BA6hB5abRSgWViFy0cmmCkQQCNZJAQgJUwiVcBGbm1z/WM7IMs/dee8/es/ZafN++ntfsvfa6/CaMv3nmt571PIoIzMxs/E0oOwAzs+crJ2Azs5I4AZuZlcQJ2MysJE7AZmYlcQI2MyuJE3CNSXqtpDvH4Tq3STqk19cxqxt5HHD1SVoDvDciflx2LJ2QNBm4H7g+Io4sOx6z8eIesPWDtwNPAW+QNL3sYMzGixNwjUk6RNK69Po0Sd/e7PPPS/pCej1D0uWSNkpaJenPc/t9XNJlki6UtCmVHOblPl8j6bD0+pWSbpD0sKQNkr4oacsWoc4HvgTcCvxZ7rytYt5O0gXpOvdK+jtJE9Nn75b0M0n/JOkhSaslHTFazLnv8Ru59wdK+nn6Pn7pEov1ghPw88fFwJGSpgKkRHUscFHu83XADLIe6ackHZo7/s3AJcD2wOXAFxtcZwj4a2BH4FXAocBfNQpK0q7AIcA3UzuhjZgXAoPAi4H9gTcA780d/0fAnSmWfwAukKRGseRimglcAfwdMA34CLBI0k6tjjVrhxPw80RE3A3cAhydNr0eeCIibpQ0G3gN8DcR8duIWAacD7wrd4qfRcSVETEEfB14eYPrLI2IGyNiMCLWAF8G/meT0E4Abo2I28kS7t6S9i8Q8y7AEcCpEfF4RDwAfA44LnfuuyPivBTzQmA6sEurfyvgncCV6fsdjojFwBLA9WnrKifg55eLgOPT6z/l2Z7kDGBjRGzK7Xs3MDP3/r7c6yeArSVtsfkFJL1E0vcl3SfpUeBTZD3QRk4g6/kSEeuB68hKEq1i3g2YBGxIZYKHyZL9zqPFHBFPpJdTmsQyYjfgmJHzpnO/hiyBm3WNE/Dzy7eAQyTNAt7Cs8lsPTBN0ra5fXcF7u3gGucCdwBzI2IqcAYw6p/9kl4NzAVOTwn7PrKywfG55N4o5rVkN+52jIjtU5saEXsXjPNxYJvc+xflXq8Fvp477/YRMTkiPl3w3GaFOAHXxyRJW+fac3qnEfFfwLXAV4HVEbEybV8L/Bz4+3TsvsBJpJ5pm7YFHgUek/Qy4C+b7DsfWAzsBeyX2j5kifGIFjFvAK4CPitpqqQJkvaU1KzckbcMOE7SpHRD8e25z74B/ImkwyVNTP8mI78EzLrGCbg+rgSezLWPN9jvIuAwnu1JjjgemEPWG/4ucGaqfbbrI2Slgk3AecClo+0kaWuyG2r/EhH35dpqshrz5mWI0WI+AdgSuB14CPg2xcsEfwvsmY47K3/u9AvpKLLe+3+R9Yj/N/7/i3WZH8QwMyuJf6ObmZXECdjMrCROwGZmJXECNjMryXOGKnXbvOmvrdRdvmUP3lV2CG3b9OOzyw6hbT855kdlh9CWQ947WHYI7duq1RQc/Wfyx77Z8lHxVp75zV2Fc86kHfcY8/XGwj1gM7OS9LwHbGY2roaHyo6gMCdgM6uXoeqUi5yAzaxWIobLDqEwJ2Azq5dhJ2Azs3K4B2xmVhLfhDMzK4l7wGZm5QiPgjAzK4lvwpmZlcQlCDOzkvgmnJlZSdwDNjMrSR1vwkmaCOySPyYi7ulFUGZmHavbTThJHwTOBO4HRr67APZtsP8AMACw69QXs9M2Lxp7pGZmBUTUrwZ8CvDSiHiwyM4RsQBYANWbkN3MKq6GNeC1wCO9DMTMrCvqVoIA7gKulXQF8NTIxog4pydRmZl1qoY94HtS2zI1M7P+NPRM2REUVigBR8RZAJK2zd7GYz2NysysUxUqQRRalFPSPpJ+AawAbpO0VNLevQ3NzKwDMVy8laxoCWIB8KGIuAZA0iHAecCrexSXmVlnKtQDLpqAJ48kX4CIuFbS5B7FZGbWuQol4EIlCOAuSX8raU5q/xdY3cvAzMw6EUPPFG7NSJot6RpJKyXdJumUtP3jku6VtCy1I3PHnC5plaQ7JR3eKtaiPeD3AGcB3wEEXA+cWPBYM7Px073a7iDw4Yi4JQ1AWCppcfrscxHxT/mdJe0FHAfsDcwAfizpJdHk0byioyAeAk7u5DswMxtXXSpBRMQGYEN6vUnSSmBmk0OOAi6JiKeA1ZJWAa8Ebmh0QNMELOnyFgG+udnnZmbjro0ecH7emmRBmkph8/3mAPsDNwEHAR+QdAKwhKyX/BBZcr4xd9g6mifslj3gV5E9hnxxurBa7G9mVq42esD5eWsakTQFWAScGhGPSjoX+CTZhGSfBD5LVqYdLT82nQunVQJ+EfC/gOOBPwWuAC6OiNtaHGdmVo4uju+VNIks+X4zIr4DEBH35z4/D/h+ersOmJ07fBawvtn5mybgVDz+IfBDSVuRJeJrJX0iIv6lyDcwbYtqjVaboOp18ifstFvZIbRtz+0qNrfThCllR9A2Ta1ezF0x2J0J2SUJuABYmZ/3RtL0VB8GeAvZA2oAlwMXSTqH7CbcXODmZtdoeRMuJd43kSXfOcAXyEZDmJn1n+71gA8C3gUsl7QsbTsDOF7SfmTlhTXAXwBExG2SLgNuJxtB8f5mIyCg9U24hcA+wA+AsyJiRbP9zcxK171RED9j9LrulU2OORs4u+g1WvWA3wU8DrwEOFnP/nmu7FoxteiFzMzGRR/M8VBUqxpw0SflzMz6Q4UeRfaqyGZWL3XpAZuZVU6XRkGMBydgM6uXqM46wE7AZlYvrgGbmZXECdjMrCS+CWdmVpKhpg+f9RUnYDOrF5cgzMxKUtcELGk7YGZE3N6jeMzMxqZCNeCWjxpLulrSVEk7AMvJplv7x96HZmbWvhiOwq1sReZ6mBYRjwJvBRZGxH5A09U+JQ1IWiJpybrH1nYjTjOzYoaHi7eSFUnAW0jaCTgG+LciJ42IBRExLyLmzZoyu/UBZmbdMjRUvJWsSA34bOA64GcRcbOkPYDVvQ3LzKxDfdCzLaplAo6IS4BLcu/vIlt+2cys/1QoARe5CfdiST+S9Mv0fl9Jp/c+NDOzDkQUbyUrUgM+HzgLGPm1shx4Z88iMjMbiwrdhCtSA54cET8fWY4oIkLSM70Ny8ysQ30wvKyoIgn4QUm7k60AiqSjgft6GpWZWaf6YHRDUUUS8AeAC4CXSbob2EC2RL2ZWd+JPigtFFVkFMQq4PXpMWRFxMO9D8vMrEN1KkFIOmOz9wBExKd6FJOZWecqNBdEkRJEvqCyNfAm4LbehGNmNkZ16gFHxGfy7yV9BvjXnkVkZjYWg/W6Cbe5rYA9ux2ImVlX1KEEIWmLiBiU9AvSEDRgIjAdcP3XzPpTTUoQNwMHAG/PbRsE7ouIp4peYCLqMLRyTFCRhwP7y4Sddis7hLZtM7Xwj1Bf0OyXlh1C+x57rOwISlGXYWgCiIhfj1MsZmZjV5Me8E6SPtTow4g4pwfxmJmNTYUScLO/tycCU4BtGzQzs/7TpQnZJc2WdI2klZJuk3RK2j5N0mJJv0pfd0jbJekLklZJulXSAa1CbdYD3hARn2jn+zYzK1sX13obBD4cEbdI2hZYKmkx8G7g6oj4tKTTgNOAvwGOAOam9kfAuelrQ816wNW6e2ZmBlkJomhrIiI2RMQt6fUmYCUwk2xBioVpt4XA0en1UcCFkbkR2F7S9GbXaNYDPrTlN2pm1m96MApC0hxgf+AmYJeI2ABZkpa0c9ptJpBfhXhd2rah0Xkb9oAjYuPYQjYzK0EbPeD8Cu6pDWx+OklTgEXAqWmF+EZGqxo07WZ38iScmVn/aqMGHBELgAWNPpc0iSz5fjMivpM23y9peur9TgceSNvXAfll4GcB65tdv3pPHZiZNRFDw4VbM8qmfrwAWLnZsNvLgfnp9Xzge7ntJ6TREAcCj4yUKhpxD9jM6qV7oyAOAt4FLJe0LG07A/g0cJmkk4B7gGPSZ1cCRwKrgCeAE1tdwAnYzGqlW8PQIuJnNB4N9pxBChERwPvbuYYTsJnVS4WehHMCNrN6qc5cPE7AZlYvMVidDNw0ATebjAc8IY+Z9aHq5N+WPeCRSXdeCryCbJgFwJ8A1zc6KA1mHgDYe/u9mT1ldqNdzcy6qotzQfRc0wQcEWcBSLoKOCA9D42kjwPfanLc7wY3HzH7iOr8a5hZ9dWoBzxiV+Dp3PungTldj8bMbIxq0wPO+Tpws6Tvkj3b/Bbgwp5FZWbWqbr1gCPibEk/AF6bNp0YEb/oXVhmZp2JwbIjKK6dYWjbAI9GxFcl7SRp94hY3avAzMw6UaFV6YslYElnAvPIRkN8FZgEfIPsWWkzs/5RtwRMVvPdHxiZHX59WqLDzKyv1K4HDDwdESEpACRN7mFMZmYdq2MCvkzSl8nWOPpz4D3Aeb0Ly8ysMzFUneUsWz2KfCrw78A/A68DHiWrA38sIhb3Pjwzs/bUqQc8C/g88DLgVuDnZAl5aY/jMjPrSAzXpAccER8BkLQl2SiIV5PKD5Iejoi9eh+imVlxdeoBj3gBMBXYLrX1wPJeBWVm1qmImvSAJS0A9gY2ATeRlSDOiYiHxiE2M7O21akHvCuwFfAr4F6yZZcfbucCT8dQZ5GVJKjORB6/M1ytf2OAxx/ZquwQ2rJj2QF0QNNnlB1CKYbrMgoiIt6Ylmbem6z++2FgH0kbgRsi4sxxiNHMrLDa3ISD3630uULSw8Ajqf0x8ErACdjM+kptErCkk8l6vgcBz5ANQbsB+Aq+CWdmfSgqVEVs1QOeA3wb+OuI2ND7cMzMxqY2PeCIaLoop5lZv6nNMDQzs6oZqssoCDOzqnEP2MysJLWpAZuZVU2dRkGYmVWKe8BmZiUZGp5QdgiFOQGbWa1UqQRRnV8VZmYFDIcKt1YkfUXSA5JW5LZ9XNK9kpaldmTus9MlrZJ0p6TDW52/ZQKWdNDIIpyS3inpHEm7tYzczKwEESrcCvga8MZRtn8uIvZL7UoASXsBx5FNXvZG4P9Lmtjs5EV6wOcCT0h6OfB/gLuBC4tEbmY23iKKt9bniuuBjQUvfRRwSUQ8FRGrgVVkk5Y1VCQBD6YZ0Y4CPh8Rnwe2bXaApAFJSyQtuffxdQVjNzMbu3ZKEPlcldpAwct8QNKtqUSxQ9o2E1ib22dd2tZQkQS8SdLpwDuBK1KXelKzAyJiQUTMi4h5MyfPKnAJM7PuGBqeULjlc1VqCwpc4lxgT2A/YAPw2bR9tJpG0352kQT8DuAp4KSIuI8so/9jgePMzMZdtNE6On/E/RExFBHDwHk8W2ZYB8zO7TqLbP3MhlrNBzwR+EZEHJa7+D24BmxmfarI6IaxkDQ9Nz3vW4CRERKXAxdJOgeYAcwFbm52rlbTUQ5JekLSdhHxyBjjNjPruW5OxiPpYuAQYEdJ68hWATpE0n5kneg1wF9k143bJF0G3A4MAu+PaL4oZpEHMX4LLJe0GHh8ZGNEnNz2d2Nm1mPdXBQ5Io4fZfMFTfY/Gzi76PmLJOArUjMz63sx6r2w/lRkUc6F4xGImVk3DNZpPmBJqxnlhmFE7NGTiMzMxqBWPWBgXu711sAxwLTehGNmNjbdrAH3WstxwBHxYK7dGxH/DLx+HGIzM2tboMKtbEVKEAfk3k4g6xE3fRTZzKwsVeoBFylBfDb3epBs3NuxPYnGzGyMhvqgZ1tUkVEQrxuPQMzMuqFCKxIVKkFsBbwNmJPfPyI+0buwzMw6M1ynHjDwPeARYCnZpDxt2W7i1u0eYm0aXLa47BDaNmlS0yc0+462rt7P8fBdq8sOoRQVWpGoUAKeFRGjzQhvZtZ3qnQTrsh0lD+X9D96HomZWRcMS4Vb2Rr2gNMidMNpnxMl3UVWghAQEbHv+IRoZlZclYpbzUoQM8lmfDczq4y6jIJYHRF3j1skZmZdUJdREDtL+lCjDyPinB7EY2Y2JnUZBTERmMLoC82ZmfWlupQgNvhhCzOrmioNQ2uWgCv0e8TMLDNUoczVLAEfOm5RmJl1SS16wBGxcTwDMTPrhlokYDOzKqrQknBOwGZWL+4Bm5mVpC6PIpuZVU5dxgEj6bKIOFbScn7/AZOmE/JIGgAGAPabti+7T9mtW/GamTVVpxLEKenrH7dz0ohYACwAeOtub67Sk4FmVnG1ScARsUHSROCCiDhsnGIyM+tYlXp8RRblHJL0hKTtIuKR8QjKzKxTtakB5/wWWC5pMfD4yMaIOLknUZmZdaiOoyCuSM3MrK8NV6gI0WoUxK4RcU9ELByvgMzMxqKbN+EkfYVsEMIDEbFP2jYNuBSYA6wBjo2IhyQJ+DxwJPAE8O6IuKXZ+VstyvmvuUAWdfg9mJmNm2ijFfA1YPNV4U8Dro6IucDV6T3AEcDc1AaAc1udvFUCzpez9ygQrJlZqYbbaK1ExPXA5hOTHQWMVAUWAkfntl8YmRuB7SVNb3b+Vgk4Grw2M+tLg4rCTdKApCW5NlDgErtExAbIhuoCO6ftM4G1uf3WpW0NtboJ93JJj5L1hF+QXsOzT8JNLRCsmdm4aaenmH9orAtGGwDXNJxWD2JMHFM4ZmbjbByehLtf0vT0oNp04IG0fR0wO7ffLGB9sxO1KkGYmVXKMFG4dehyYH56PR/4Xm77CcocCDwyUqpoxLOhmVmtdPNmlaSLgUOAHSWtA84EPg1cJukk4B7gmLT7lWRD0FaRDUM7sdX5nYDNrFa6WYKIiOMbfPScNTMjIoD3t3P+nifgSRWrckyaUL3fSX81cHXZIbRtBi8sO4S27HrG2tY79ZmNFbyDc/pHx36OoQoN2KpetjEza6I201GamVVNuAdsZlYO94DNzEpSm9nQzMyqpjrp1wnYzGpmsEIp2AnYzGrFN+HMzErim3BmZiVxD9jMrCTuAZuZlWQo3AM2MyuFxwGbmZWkSjXgQlOVSdqqyDYzs7J1c1HOXis6V+QNBbeZmZVqHFbE6JqmJQhJLyJb1fMFkvbn2UXnpgLbNDluABgA+MNpL2fPKXO6EqyZWStVKkG0qgEfDrybbHG5c3LbNwFnNDoov9LoO3Y7ujr/GmZWebUZBRERC4GFkt4WEYvGKSYzs471Q2mhqEKjICJikaQ3AXsDW+e2f6JXgZmZdaIfbq4VVSgBS/oSWc33dcD5wNuBm3sYl5lZR6pUAy46CuLVEXEC8FBEnAW8Cpjdu7DMzDpTm1EQOU+mr09ImgFsBHbvTUhmZp2LutyEy/m+pO2BfwCWpm3n9yYkM7PO1WZZekmvANZGxCfT+ynAcuAO4HO9D8/MrD39UFooqlUN+MvA0wCSDgY+nbY9Qhrna2bWTyKicCtbqxLExIjYmF6/A1iQxgMvkrSst6GZmbWvTj3giZJGkvShwE9yn3kmNTPrO9HG/8rWKoleDFwn6TdkIyF+CiDpxWRlCDOzvlKnR5HPlnQ1MB24Kp4tmkwAPtjr4MzM2lWlEkTLMkJE3DjKtv/sTThmZmNTqwQ8Vg8OP9l6pz4yODxUdghtu/nJdWWH0LY9ttqp7BDaMrjFtmWH0LZHqd7Pcjd0c3SDpDVksz8OAYMRMU/SNOBSYA6wBjg2Ih7q5PxFH0U2M6uEHjyK/LqI2C8i5qX3pwFXR8Rc4Or0viNOwGZWK+MwCuIoYGF6vRA4utMTOQGbWa0MxXDhJmlA0pJcG9jsdAFcJWlp7rNdImIDQPq6c6exeiyvmdVKOzXg/Oo9DRwUEesl7QwslnTHWOPLcw/YzGqlmzXgiFifvj4AfBd4JXC/pOkA6esDncbqBGxmtdKtGrCkyZK2HXkNvAFYAVwOzE+7zQe+12msLkGYWa0Md28Y2i7AdyVBlisviogfSvoP4DJJJwH3AMd0egEnYDOrlW7N8RARdwEvH2X7g2Rz44yZE7CZ1cpQVGdZTidgM6uVLpYges4J2MxqpR+mmSzKCdjMasU9YDOzkrgHbGZWkqGozixwhROwpIlk4+J+d0xE3NOLoMzMOtUPi20WVSgBS/ogcCZwPzAyxiOAfRvsPwAMALxs+72YOWXW2CM1MyugjhOynwK8NA1Abik/wcVhsw+vzr+GmVVe7XrAwFq8CKeZVUAdR0HcBVwr6QrgqZGNEXFOT6IyM+tQHUdB3JPalqmZmfWl2j2KHBFn9ToQM7NuqF0NWNI18Nx+fUS8vusRmZmNQR1rwB/Jvd4aeBsw2P1wzMzGpnY94IhYutmmf5d0XQ/iMTMbk9qNA5Y0Lfd2AjAPeFFPIjIzG4Pa9YCBpTxbAx4E1gAn9SIgM7OxqM0oCEmvANZGxO7p/Xyy+u8a4PaeR2dm1qYq3YRrtSryl4GnASQdDPw9sJDsqbgFvQ3NzKx9EVG4la1VCWJiRGxMr98BLIiIRcAiSct6G5qZWfuq9CRcqx7wREkjSfpQ4Ce5zzyXsJn1nTr1gC8GrpP0G+BJ4KcAkl6MJ+cxsz5UpRqwWv0WkHQgMB24KiIeT9teAkyJiFt6H2LT2AbS1JeVULV4oXoxVy1ecMzPZy0TcD+TtCQi5pUdR1FVixeqF3PV4gXH/HzWqgZsZmY94gRsZlaSqifgqtWgqhYvVC/mqsULjvl5q9I1YDOzKqt6D9jMrLKcgM3MStKXCVjSVyQ9IGlFg88l6QuSVkm6VdIBuc/mS/pVavPHMeY1kpZLWiZpSb/HLOkUSSsk3Sbp1H6Md7SfA0mfTPEsk3SVpBkNjh01Rkl/mP47rUrfn8Yh5ktTvMvSz8moj/FLeqOkO1Nsp+W27y7ppvS9XCqpa+sySpot6RpJK9PPwilp+zHp/bCkhsPNyoi5Vtp5bG+8GnAwcACwosHnRwI/AAQcCNyUtk8jW8F5GrBDer3DOMW8Btixyed9EzOwD7AC2IbsacgfA3P7Ld7Rfg6AqbnXJwNfGuW4hjECNwOvSt/XD4Ajxvln97PAx0bZPhH4NbAH2cK3vwT2Sp9dBhyXXn8J+MsuxjsdOCC93hb4T2Av4A+AlwLXAvMaHFtKzHVqfdkDjojrgY1NdjkKuDAyNwLbS5oOHA4sjoiNEfEQsBh4Y+8jLqSfYv4D4MaIeCIiBoHrgLf0W7yj/RxExKO5t5MZZa3CRjGm+KdGxA2RZYYLgaN7HfOI1Ns+luwR/829ElgVEXdFxNPAJcBR6ZjXA99O+y3sZswRsSHSE60RsQlYCcyMiJURcWeLw0uJuU76MgGPRtL7JL0vvZ0JrM19vC5ta7R9PARwlaSlkgagr2NeARws6YWStiHr7c7u43h/j6SzJa0F/gz4WNo2T9L5aZdmsa8bZft4eS1wf0T8CkDSDElXps8axfxC4OH0izK/veskzQH2B25qsk9fxVx1lZnRLCK+lHs7Wt0ummwfDwdFxHpJOwOLJd3RrzFHxEpJnyHrGT5G9qfjYL/G+5yLRXwU+Kik04EPAGdGxBLgvWmXfo39eHK934hYT/bLD0qOWdIUYBFw6mZ/Zfz+hfso5jqoTA94M+uA2bn3s4D1Tbb3XPrBJCIeAL5L9udZXl/FHBEXRMQBEXEw2Z/Mv9psl76Kt4GLyFZo2Vyz2GeNsr3nlE3r+lbg0ga7NIr5N2Tlny02297N2CaRJd9vRsR32ji0tJjroqoJ+HLghHSn/kDgkYjYAPwIeIOkHSTtALwhbespSZMlbTvyOl138xEc/RbzzunrrmSJYfO6ZF/Fm4t7bu7tm4E7Rtlt1BhT/JskHZjqlCcA3+t50JnDgDsiYl2Dz/8DmJtGD2wJHAdcnmrV1wBvT/vNp4sxp3+HC4CVEXFOm4eXEnOtlH0XcLRGlgw2AM+Q/ZY9CXgf8L70uYD/R3YHdjm5u7TAe4BVqZ04TvHuQfZn/C+B24CPpu39HPNPydb1+yVwaD/G2+DnYBHZL7dbgX8ju2EE2Urd57eKMe23In1fXyQ9DdrLmNP2r4382+b2nQFcmXt/JNkohF+P/Azlfr5uTt/Lt4Ctuhjva8jKA7cCy1I7kuym7DrgKeB+sl9gfRFznZofRTYzK0lVSxBmZpXnBGxmVhInYDOzkjgBm5mVxAnYzKwkTsBmZiVxAjYzK8l/A8//9yocknuTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "final_df6 = station_ent_data4.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "final_df6 = final_df6.reset_index().sort_values(['DAY']).set_index('TIME')\n",
    "#final_df6.drop(['14:06:54','08:56:17','08:06:06', '08:17:24'], inplace = True)\n",
    "final_df6.drop(['10:03:47', '04:55:40'], inplace = True)\n",
    "#final_df6.drop(['10:05:49', '06:58:54','07:01:35','07:00:14','06:57:34','06:54:53','06:56:13', '06:49:30','06:52:12','06:53:33', '06:50:52', '09:26:36' ], inplace = True)\n",
    "final_df6 = final_df6.reset_index().sort_values(['TIME','DAY']).set_index('STATION')\n",
    "#final_df6 = final_df6.loc['103 ST']\n",
    "final_df6 = final_df6.loc['LIVONIA AV']\n",
    "#final_df6 = final_df6.loc['EAST BROADWAY']\n",
    "\n",
    "\n",
    "list_times = []\n",
    "for i in range(7):#final_df4.shape[0]):\n",
    "    final_df7 = final_df6.reset_index().set_index('DAY')\n",
    "    list1 = []\n",
    "    final_df7 = final_df7.loc[i]\n",
    "    list1 = final_df7.TOTAL_TRAF.tolist()\n",
    "    list_times.append(list1)\n",
    "print(final_df7)\n",
    "print(list_times)\n",
    "#for i in range(len(list_times)):\n",
    "xlabels = ['1:00', '5:00', '9:00', '13:00', '17:00','21:00']\n",
    "ylabels = ['Mon','Tues','Wed','Thurs','Fri','Sat','Sun']\n",
    "heat = sns.heatmap(list_times, xticklabels = xlabels, yticklabels = ylabels)\n",
    "heat.set_title('Livonia Avenue')\n",
    "plt.savefig('Heat Livonia Avenue', dpi = 300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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