Analyzing Crime Rate Chicago Dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import random\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 533719: expected 23 fields, saw 24\\n'\n",
      "b'Skipping line 1149094: expected 23 fields, saw 41\\n'\n"
     ]
    }
   ],
   "source": [
    "# dataframes creation for both training and testing datasets \n",
    "chicago_df_1 = pd.read_csv('/Users/aika/Desktop/DL and ML Practical Tutorials - Package/Project 3/Chicago_Crimes_2005_to_2007.csv', error_bad_lines=False)\n",
    "chicago_df_2 = pd.read_csv('/Users/aika/Desktop/DL and ML Practical Tutorials - Package/Project 3/Chicago_Crimes_2008_to_2011.csv', error_bad_lines=False)\n",
    "chicago_df_3 = pd.read_csv('/Users/aika/Desktop/DL and ML Practical Tutorials - Package/Project 3/Chicago_Crimes_2012_to_2017.csv', error_bad_lines=False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>Date</th>\n",
       "      <th>Block</th>\n",
       "      <th>IUCR</th>\n",
       "      <th>Primary Type</th>\n",
       "      <th>Description</th>\n",
       "      <th>Location Description</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>...</th>\n",
       "      <th>Ward</th>\n",
       "      <th>Community Area</th>\n",
       "      <th>FBI Code</th>\n",
       "      <th>X Coordinate</th>\n",
       "      <th>Y Coordinate</th>\n",
       "      <th>Year</th>\n",
       "      <th>Updated On</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>4673626</td>\n",
       "      <td>HM274058</td>\n",
       "      <td>04/02/2006 01:00:00 PM</td>\n",
       "      <td>055XX N MANGO AVE</td>\n",
       "      <td>2825</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>HARASSMENT BY TELEPHONE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>45.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>26</td>\n",
       "      <td>1136872.0</td>\n",
       "      <td>1936499.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.981913</td>\n",
       "      <td>-87.771996</td>\n",
       "      <td>(41.981912692, -87.771996382)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>4673627</td>\n",
       "      <td>HM202199</td>\n",
       "      <td>02/26/2006 01:40:48 PM</td>\n",
       "      <td>065XX S RHODES AVE</td>\n",
       "      <td>2017</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>MANU/DELIVER:CRACK</td>\n",
       "      <td>SIDEWALK</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1181027.0</td>\n",
       "      <td>1861693.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.775733</td>\n",
       "      <td>-87.611920</td>\n",
       "      <td>(41.775732538, -87.611919814)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>4673628</td>\n",
       "      <td>HM113861</td>\n",
       "      <td>01/08/2006 11:16:00 PM</td>\n",
       "      <td>013XX E 69TH ST</td>\n",
       "      <td>051A</td>\n",
       "      <td>ASSAULT</td>\n",
       "      <td>AGGRAVATED: HANDGUN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>04A</td>\n",
       "      <td>1186023.0</td>\n",
       "      <td>1859609.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.769897</td>\n",
       "      <td>-87.593671</td>\n",
       "      <td>(41.769897392, -87.593670899)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4673629</td>\n",
       "      <td>HM274049</td>\n",
       "      <td>04/05/2006 06:45:00 PM</td>\n",
       "      <td>061XX W NEWPORT AVE</td>\n",
       "      <td>0460</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>SIMPLE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>08B</td>\n",
       "      <td>1134772.0</td>\n",
       "      <td>1922299.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.942984</td>\n",
       "      <td>-87.780057</td>\n",
       "      <td>(41.942984005, -87.780056951)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4673630</td>\n",
       "      <td>HM187120</td>\n",
       "      <td>02/17/2006 09:03:14 PM</td>\n",
       "      <td>037XX W 60TH ST</td>\n",
       "      <td>1811</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>POSS: CANNABIS 30GMS OR LESS</td>\n",
       "      <td>ALLEY</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1152412.0</td>\n",
       "      <td>1864560.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.784211</td>\n",
       "      <td>-87.716745</td>\n",
       "      <td>(41.784210853, -87.71674491)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0       ID Case Number                    Date  \\\n",
       "0           0  4673626    HM274058  04/02/2006 01:00:00 PM   \n",
       "1           1  4673627    HM202199  02/26/2006 01:40:48 PM   \n",
       "2           2  4673628    HM113861  01/08/2006 11:16:00 PM   \n",
       "3           4  4673629    HM274049  04/05/2006 06:45:00 PM   \n",
       "4           5  4673630    HM187120  02/17/2006 09:03:14 PM   \n",
       "\n",
       "                 Block  IUCR   Primary Type                   Description  \\\n",
       "0    055XX N MANGO AVE  2825  OTHER OFFENSE       HARASSMENT BY TELEPHONE   \n",
       "1   065XX S RHODES AVE  2017      NARCOTICS            MANU/DELIVER:CRACK   \n",
       "2      013XX E 69TH ST  051A        ASSAULT           AGGRAVATED: HANDGUN   \n",
       "3  061XX W NEWPORT AVE  0460        BATTERY                        SIMPLE   \n",
       "4      037XX W 60TH ST  1811      NARCOTICS  POSS: CANNABIS 30GMS OR LESS   \n",
       "\n",
       "  Location Description  Arrest  ...  Ward  Community Area  FBI Code  \\\n",
       "0            RESIDENCE   False  ...  45.0            11.0        26   \n",
       "1             SIDEWALK    True  ...  20.0            42.0        18   \n",
       "2                OTHER   False  ...   5.0            69.0       04A   \n",
       "3            RESIDENCE   False  ...  38.0            17.0       08B   \n",
       "4                ALLEY    True  ...  13.0            65.0        18   \n",
       "\n",
       "   X Coordinate  Y Coordinate  Year              Updated On   Latitude  \\\n",
       "0     1136872.0     1936499.0  2006  04/15/2016 08:55:02 AM  41.981913   \n",
       "1     1181027.0     1861693.0  2006  04/15/2016 08:55:02 AM  41.775733   \n",
       "2     1186023.0     1859609.0  2006  04/15/2016 08:55:02 AM  41.769897   \n",
       "3     1134772.0     1922299.0  2006  04/15/2016 08:55:02 AM  41.942984   \n",
       "4     1152412.0     1864560.0  2006  04/15/2016 08:55:02 AM  41.784211   \n",
       "\n",
       "   Longitude                       Location  \n",
       "0 -87.771996  (41.981912692, -87.771996382)  \n",
       "1 -87.611920  (41.775732538, -87.611919814)  \n",
       "2 -87.593671  (41.769897392, -87.593670899)  \n",
       "3 -87.780057  (41.942984005, -87.780056951)  \n",
       "4 -87.716745   (41.784210853, -87.71674491)  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chicago_df = pd.concat([chicago_df_1, chicago_df_2, chicago_df_3], ignore_index=False, axis=0)\n",
    "chicago_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's see how many null elements are contained in the data\n",
    "plt.figure(figsize=(10,10))\n",
    "sns.heatmap(chicago_df.isnull(), cbar = False, cmap = 'YlGnBu')\n",
    "# black points are all the missing points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Case Number</th>\n",
       "      <th>Date</th>\n",
       "      <th>Block</th>\n",
       "      <th>IUCR</th>\n",
       "      <th>Primary Type</th>\n",
       "      <th>Description</th>\n",
       "      <th>Location Description</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>...</th>\n",
       "      <th>Ward</th>\n",
       "      <th>Community Area</th>\n",
       "      <th>FBI Code</th>\n",
       "      <th>X Coordinate</th>\n",
       "      <th>Y Coordinate</th>\n",
       "      <th>Year</th>\n",
       "      <th>Updated On</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>4673626</td>\n",
       "      <td>HM274058</td>\n",
       "      <td>04/02/2006 01:00:00 PM</td>\n",
       "      <td>055XX N MANGO AVE</td>\n",
       "      <td>2825</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>HARASSMENT BY TELEPHONE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>45.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>26</td>\n",
       "      <td>1136872.0</td>\n",
       "      <td>1936499.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.981913</td>\n",
       "      <td>-87.771996</td>\n",
       "      <td>(41.981912692, -87.771996382)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>4673627</td>\n",
       "      <td>HM202199</td>\n",
       "      <td>02/26/2006 01:40:48 PM</td>\n",
       "      <td>065XX S RHODES AVE</td>\n",
       "      <td>2017</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>MANU/DELIVER:CRACK</td>\n",
       "      <td>SIDEWALK</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1181027.0</td>\n",
       "      <td>1861693.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.775733</td>\n",
       "      <td>-87.611920</td>\n",
       "      <td>(41.775732538, -87.611919814)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>4673628</td>\n",
       "      <td>HM113861</td>\n",
       "      <td>01/08/2006 11:16:00 PM</td>\n",
       "      <td>013XX E 69TH ST</td>\n",
       "      <td>051A</td>\n",
       "      <td>ASSAULT</td>\n",
       "      <td>AGGRAVATED: HANDGUN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>04A</td>\n",
       "      <td>1186023.0</td>\n",
       "      <td>1859609.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.769897</td>\n",
       "      <td>-87.593671</td>\n",
       "      <td>(41.769897392, -87.593670899)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4673629</td>\n",
       "      <td>HM274049</td>\n",
       "      <td>04/05/2006 06:45:00 PM</td>\n",
       "      <td>061XX W NEWPORT AVE</td>\n",
       "      <td>0460</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>SIMPLE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>08B</td>\n",
       "      <td>1134772.0</td>\n",
       "      <td>1922299.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.942984</td>\n",
       "      <td>-87.780057</td>\n",
       "      <td>(41.942984005, -87.780056951)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4673630</td>\n",
       "      <td>HM187120</td>\n",
       "      <td>02/17/2006 09:03:14 PM</td>\n",
       "      <td>037XX W 60TH ST</td>\n",
       "      <td>1811</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>POSS: CANNABIS 30GMS OR LESS</td>\n",
       "      <td>ALLEY</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1152412.0</td>\n",
       "      <td>1864560.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.784211</td>\n",
       "      <td>-87.716745</td>\n",
       "      <td>(41.784210853, -87.71674491)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0       ID Case Number                    Date  \\\n",
       "0           0  4673626    HM274058  04/02/2006 01:00:00 PM   \n",
       "1           1  4673627    HM202199  02/26/2006 01:40:48 PM   \n",
       "2           2  4673628    HM113861  01/08/2006 11:16:00 PM   \n",
       "3           4  4673629    HM274049  04/05/2006 06:45:00 PM   \n",
       "4           5  4673630    HM187120  02/17/2006 09:03:14 PM   \n",
       "\n",
       "                 Block  IUCR   Primary Type                   Description  \\\n",
       "0    055XX N MANGO AVE  2825  OTHER OFFENSE       HARASSMENT BY TELEPHONE   \n",
       "1   065XX S RHODES AVE  2017      NARCOTICS            MANU/DELIVER:CRACK   \n",
       "2      013XX E 69TH ST  051A        ASSAULT           AGGRAVATED: HANDGUN   \n",
       "3  061XX W NEWPORT AVE  0460        BATTERY                        SIMPLE   \n",
       "4      037XX W 60TH ST  1811      NARCOTICS  POSS: CANNABIS 30GMS OR LESS   \n",
       "\n",
       "  Location Description  Arrest  ...  Ward  Community Area  FBI Code  \\\n",
       "0            RESIDENCE   False  ...  45.0            11.0        26   \n",
       "1             SIDEWALK    True  ...  20.0            42.0        18   \n",
       "2                OTHER   False  ...   5.0            69.0       04A   \n",
       "3            RESIDENCE   False  ...  38.0            17.0       08B   \n",
       "4                ALLEY    True  ...  13.0            65.0        18   \n",
       "\n",
       "   X Coordinate  Y Coordinate  Year              Updated On   Latitude  \\\n",
       "0     1136872.0     1936499.0  2006  04/15/2016 08:55:02 AM  41.981913   \n",
       "1     1181027.0     1861693.0  2006  04/15/2016 08:55:02 AM  41.775733   \n",
       "2     1186023.0     1859609.0  2006  04/15/2016 08:55:02 AM  41.769897   \n",
       "3     1134772.0     1922299.0  2006  04/15/2016 08:55:02 AM  41.942984   \n",
       "4     1152412.0     1864560.0  2006  04/15/2016 08:55:02 AM  41.784211   \n",
       "\n",
       "   Longitude                       Location  \n",
       "0 -87.771996  (41.981912692, -87.771996382)  \n",
       "1 -87.611920  (41.775732538, -87.611919814)  \n",
       "2 -87.593671  (41.769897392, -87.593670899)  \n",
       "3 -87.780057  (41.942984005, -87.780056951)  \n",
       "4 -87.716745   (41.784210853, -87.71674491)  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chicago_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assembling a datetime by rearranging the dataframe column \"Date\". \n",
    "\n",
    "chicago_df.Date = pd.to_datetime(chicago_df.Date, format='%m/%d/%Y %I:%M:%S %p')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# setting the index to be the date \n",
    "chicago_df.index = pd.DatetimeIndex(chicago_df.Date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ID</th>\n",
       "      <th>Case Number</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006-04-02 13:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>4673626</td>\n",
       "      <td>HM274058</td>\n",
       "      <td>2006-04-02 13:00:00</td>\n",
       "      <td>055XX N MANGO AVE</td>\n",
       "      <td>2825</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>HARASSMENT BY TELEPHONE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>45.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>26</td>\n",
       "      <td>1136872.0</td>\n",
       "      <td>1936499.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.981913</td>\n",
       "      <td>-87.771996</td>\n",
       "      <td>(41.981912692, -87.771996382)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-02-26 13:40:48</th>\n",
       "      <td>1</td>\n",
       "      <td>4673627</td>\n",
       "      <td>HM202199</td>\n",
       "      <td>2006-02-26 13:40:48</td>\n",
       "      <td>065XX S RHODES AVE</td>\n",
       "      <td>2017</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>MANU/DELIVER:CRACK</td>\n",
       "      <td>SIDEWALK</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1181027.0</td>\n",
       "      <td>1861693.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.775733</td>\n",
       "      <td>-87.611920</td>\n",
       "      <td>(41.775732538, -87.611919814)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-08 23:16:00</th>\n",
       "      <td>2</td>\n",
       "      <td>4673628</td>\n",
       "      <td>HM113861</td>\n",
       "      <td>2006-01-08 23:16:00</td>\n",
       "      <td>013XX E 69TH ST</td>\n",
       "      <td>051A</td>\n",
       "      <td>ASSAULT</td>\n",
       "      <td>AGGRAVATED: HANDGUN</td>\n",
       "      <td>OTHER</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>04A</td>\n",
       "      <td>1186023.0</td>\n",
       "      <td>1859609.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.769897</td>\n",
       "      <td>-87.593671</td>\n",
       "      <td>(41.769897392, -87.593670899)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-04-05 18:45:00</th>\n",
       "      <td>4</td>\n",
       "      <td>4673629</td>\n",
       "      <td>HM274049</td>\n",
       "      <td>2006-04-05 18:45:00</td>\n",
       "      <td>061XX W NEWPORT AVE</td>\n",
       "      <td>0460</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>SIMPLE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>08B</td>\n",
       "      <td>1134772.0</td>\n",
       "      <td>1922299.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.942984</td>\n",
       "      <td>-87.780057</td>\n",
       "      <td>(41.942984005, -87.780056951)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-02-17 21:03:14</th>\n",
       "      <td>5</td>\n",
       "      <td>4673630</td>\n",
       "      <td>HM187120</td>\n",
       "      <td>2006-02-17 21:03:14</td>\n",
       "      <td>037XX W 60TH ST</td>\n",
       "      <td>1811</td>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>POSS: CANNABIS 30GMS OR LESS</td>\n",
       "      <td>ALLEY</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>18</td>\n",
       "      <td>1152412.0</td>\n",
       "      <td>1864560.0</td>\n",
       "      <td>2006</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.784211</td>\n",
       "      <td>-87.716745</td>\n",
       "      <td>(41.784210853, -87.71674491)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-03 23:33:00</th>\n",
       "      <td>6250330</td>\n",
       "      <td>10508679</td>\n",
       "      <td>HZ250507</td>\n",
       "      <td>2016-05-03 23:33:00</td>\n",
       "      <td>026XX W 23RD PL</td>\n",
       "      <td>0486</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>DOMESTIC BATTERY SIMPLE</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>28.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>08B</td>\n",
       "      <td>1159105.0</td>\n",
       "      <td>1888300.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>05/10/2016 03:56:50 PM</td>\n",
       "      <td>41.849222</td>\n",
       "      <td>-87.691556</td>\n",
       "      <td>(41.849222028, -87.69155551)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-03 23:30:00</th>\n",
       "      <td>6251089</td>\n",
       "      <td>10508680</td>\n",
       "      <td>HZ250491</td>\n",
       "      <td>2016-05-03 23:30:00</td>\n",
       "      <td>073XX S HARVARD AVE</td>\n",
       "      <td>1310</td>\n",
       "      <td>CRIMINAL DAMAGE</td>\n",
       "      <td>TO PROPERTY</td>\n",
       "      <td>APARTMENT</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>14</td>\n",
       "      <td>1175230.0</td>\n",
       "      <td>1856183.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>05/10/2016 03:56:50 PM</td>\n",
       "      <td>41.760744</td>\n",
       "      <td>-87.633335</td>\n",
       "      <td>(41.760743949, -87.63333531)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-03 00:15:00</th>\n",
       "      <td>6251349</td>\n",
       "      <td>10508681</td>\n",
       "      <td>HZ250479</td>\n",
       "      <td>2016-05-03 00:15:00</td>\n",
       "      <td>024XX W 63RD ST</td>\n",
       "      <td>041A</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>AGGRAVATED: HANDGUN</td>\n",
       "      <td>SIDEWALK</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>04B</td>\n",
       "      <td>1161027.0</td>\n",
       "      <td>1862810.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>05/10/2016 03:56:50 PM</td>\n",
       "      <td>41.779235</td>\n",
       "      <td>-87.685207</td>\n",
       "      <td>(41.779234743, -87.685207125)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-03 21:07:00</th>\n",
       "      <td>6253257</td>\n",
       "      <td>10508690</td>\n",
       "      <td>HZ250370</td>\n",
       "      <td>2016-05-03 21:07:00</td>\n",
       "      <td>082XX S EXCHANGE AVE</td>\n",
       "      <td>0486</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>DOMESTIC BATTERY SIMPLE</td>\n",
       "      <td>SIDEWALK</td>\n",
       "      <td>False</td>\n",
       "      <td>...</td>\n",
       "      <td>7.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>08B</td>\n",
       "      <td>1197261.0</td>\n",
       "      <td>1850727.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>05/10/2016 03:56:50 PM</td>\n",
       "      <td>41.745252</td>\n",
       "      <td>-87.552773</td>\n",
       "      <td>(41.745251975, -87.552773464)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-03 23:38:00</th>\n",
       "      <td>6253474</td>\n",
       "      <td>10508692</td>\n",
       "      <td>HZ250517</td>\n",
       "      <td>2016-05-03 23:38:00</td>\n",
       "      <td>001XX E 75TH ST</td>\n",
       "      <td>5007</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>OTHER WEAPONS VIOLATION</td>\n",
       "      <td>PARKING LOT/GARAGE(NON.RESID.)</td>\n",
       "      <td>True</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>26</td>\n",
       "      <td>1178696.0</td>\n",
       "      <td>1855324.0</td>\n",
       "      <td>2016</td>\n",
       "      <td>05/10/2016 03:56:50 PM</td>\n",
       "      <td>41.758309</td>\n",
       "      <td>-87.620658</td>\n",
       "      <td>(41.75830866, -87.620658418)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6017767 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Unnamed: 0        ID Case Number                Date  \\\n",
       "Date                                                                        \n",
       "2006-04-02 13:00:00           0   4673626    HM274058 2006-04-02 13:00:00   \n",
       "2006-02-26 13:40:48           1   4673627    HM202199 2006-02-26 13:40:48   \n",
       "2006-01-08 23:16:00           2   4673628    HM113861 2006-01-08 23:16:00   \n",
       "2006-04-05 18:45:00           4   4673629    HM274049 2006-04-05 18:45:00   \n",
       "2006-02-17 21:03:14           5   4673630    HM187120 2006-02-17 21:03:14   \n",
       "...                         ...       ...         ...                 ...   \n",
       "2016-05-03 23:33:00     6250330  10508679    HZ250507 2016-05-03 23:33:00   \n",
       "2016-05-03 23:30:00     6251089  10508680    HZ250491 2016-05-03 23:30:00   \n",
       "2016-05-03 00:15:00     6251349  10508681    HZ250479 2016-05-03 00:15:00   \n",
       "2016-05-03 21:07:00     6253257  10508690    HZ250370 2016-05-03 21:07:00   \n",
       "2016-05-03 23:38:00     6253474  10508692    HZ250517 2016-05-03 23:38:00   \n",
       "\n",
       "                                    Block  IUCR     Primary Type  \\\n",
       "Date                                                               \n",
       "2006-04-02 13:00:00     055XX N MANGO AVE  2825    OTHER OFFENSE   \n",
       "2006-02-26 13:40:48    065XX S RHODES AVE  2017        NARCOTICS   \n",
       "2006-01-08 23:16:00       013XX E 69TH ST  051A          ASSAULT   \n",
       "2006-04-05 18:45:00   061XX W NEWPORT AVE  0460          BATTERY   \n",
       "2006-02-17 21:03:14       037XX W 60TH ST  1811        NARCOTICS   \n",
       "...                                   ...   ...              ...   \n",
       "2016-05-03 23:33:00       026XX W 23RD PL  0486          BATTERY   \n",
       "2016-05-03 23:30:00   073XX S HARVARD AVE  1310  CRIMINAL DAMAGE   \n",
       "2016-05-03 00:15:00       024XX W 63RD ST  041A          BATTERY   \n",
       "2016-05-03 21:07:00  082XX S EXCHANGE AVE  0486          BATTERY   \n",
       "2016-05-03 23:38:00       001XX E 75TH ST  5007    OTHER OFFENSE   \n",
       "\n",
       "                                      Description  \\\n",
       "Date                                                \n",
       "2006-04-02 13:00:00       HARASSMENT BY TELEPHONE   \n",
       "2006-02-26 13:40:48            MANU/DELIVER:CRACK   \n",
       "2006-01-08 23:16:00           AGGRAVATED: HANDGUN   \n",
       "2006-04-05 18:45:00                        SIMPLE   \n",
       "2006-02-17 21:03:14  POSS: CANNABIS 30GMS OR LESS   \n",
       "...                                           ...   \n",
       "2016-05-03 23:33:00       DOMESTIC BATTERY SIMPLE   \n",
       "2016-05-03 23:30:00                   TO PROPERTY   \n",
       "2016-05-03 00:15:00           AGGRAVATED: HANDGUN   \n",
       "2016-05-03 21:07:00       DOMESTIC BATTERY SIMPLE   \n",
       "2016-05-03 23:38:00       OTHER WEAPONS VIOLATION   \n",
       "\n",
       "                               Location Description  Arrest  ...  Ward  \\\n",
       "Date                                                         ...         \n",
       "2006-04-02 13:00:00                       RESIDENCE   False  ...  45.0   \n",
       "2006-02-26 13:40:48                        SIDEWALK    True  ...  20.0   \n",
       "2006-01-08 23:16:00                           OTHER   False  ...   5.0   \n",
       "2006-04-05 18:45:00                       RESIDENCE   False  ...  38.0   \n",
       "2006-02-17 21:03:14                           ALLEY    True  ...  13.0   \n",
       "...                                             ...     ...  ...   ...   \n",
       "2016-05-03 23:33:00                       APARTMENT    True  ...  28.0   \n",
       "2016-05-03 23:30:00                       APARTMENT    True  ...  17.0   \n",
       "2016-05-03 00:15:00                        SIDEWALK   False  ...  15.0   \n",
       "2016-05-03 21:07:00                        SIDEWALK   False  ...   7.0   \n",
       "2016-05-03 23:38:00  PARKING LOT/GARAGE(NON.RESID.)    True  ...   6.0   \n",
       "\n",
       "                     Community Area  FBI Code  X Coordinate  Y Coordinate  \\\n",
       "Date                                                                        \n",
       "2006-04-02 13:00:00            11.0        26     1136872.0     1936499.0   \n",
       "2006-02-26 13:40:48            42.0        18     1181027.0     1861693.0   \n",
       "2006-01-08 23:16:00            69.0       04A     1186023.0     1859609.0   \n",
       "2006-04-05 18:45:00            17.0       08B     1134772.0     1922299.0   \n",
       "2006-02-17 21:03:14            65.0        18     1152412.0     1864560.0   \n",
       "...                             ...       ...           ...           ...   \n",
       "2016-05-03 23:33:00            30.0       08B     1159105.0     1888300.0   \n",
       "2016-05-03 23:30:00            69.0        14     1175230.0     1856183.0   \n",
       "2016-05-03 00:15:00            66.0       04B     1161027.0     1862810.0   \n",
       "2016-05-03 21:07:00            46.0       08B     1197261.0     1850727.0   \n",
       "2016-05-03 23:38:00            69.0        26     1178696.0     1855324.0   \n",
       "\n",
       "                     Year              Updated On   Latitude  Longitude  \\\n",
       "Date                                                                      \n",
       "2006-04-02 13:00:00  2006  04/15/2016 08:55:02 AM  41.981913 -87.771996   \n",
       "2006-02-26 13:40:48  2006  04/15/2016 08:55:02 AM  41.775733 -87.611920   \n",
       "2006-01-08 23:16:00  2006  04/15/2016 08:55:02 AM  41.769897 -87.593671   \n",
       "2006-04-05 18:45:00  2006  04/15/2016 08:55:02 AM  41.942984 -87.780057   \n",
       "2006-02-17 21:03:14  2006  04/15/2016 08:55:02 AM  41.784211 -87.716745   \n",
       "...                   ...                     ...        ...        ...   \n",
       "2016-05-03 23:33:00  2016  05/10/2016 03:56:50 PM  41.849222 -87.691556   \n",
       "2016-05-03 23:30:00  2016  05/10/2016 03:56:50 PM  41.760744 -87.633335   \n",
       "2016-05-03 00:15:00  2016  05/10/2016 03:56:50 PM  41.779235 -87.685207   \n",
       "2016-05-03 21:07:00  2016  05/10/2016 03:56:50 PM  41.745252 -87.552773   \n",
       "2016-05-03 23:38:00  2016  05/10/2016 03:56:50 PM  41.758309 -87.620658   \n",
       "\n",
       "                                          Location  \n",
       "Date                                                \n",
       "2006-04-02 13:00:00  (41.981912692, -87.771996382)  \n",
       "2006-02-26 13:40:48  (41.775732538, -87.611919814)  \n",
       "2006-01-08 23:16:00  (41.769897392, -87.593670899)  \n",
       "2006-04-05 18:45:00  (41.942984005, -87.780056951)  \n",
       "2006-02-17 21:03:14   (41.784210853, -87.71674491)  \n",
       "...                                            ...  \n",
       "2016-05-03 23:33:00   (41.849222028, -87.69155551)  \n",
       "2016-05-03 23:30:00   (41.760743949, -87.63333531)  \n",
       "2016-05-03 00:15:00  (41.779234743, -87.685207125)  \n",
       "2016-05-03 21:07:00  (41.745251975, -87.552773464)  \n",
       "2016-05-03 23:38:00   (41.75830866, -87.620658418)  \n",
       "\n",
       "[6017767 rows x 23 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chicago_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "THEFT                                1245111\n",
       "BATTERY                              1079178\n",
       "CRIMINAL DAMAGE                       702702\n",
       "NARCOTICS                             674831\n",
       "BURGLARY                              369056\n",
       "OTHER OFFENSE                         368169\n",
       "ASSAULT                               360244\n",
       "MOTOR VEHICLE THEFT                   271624\n",
       "ROBBERY                               229467\n",
       "DECEPTIVE PRACTICE                    225180\n",
       "CRIMINAL TRESPASS                     171596\n",
       "PROSTITUTION                           60735\n",
       "WEAPONS VIOLATION                      60335\n",
       "PUBLIC PEACE VIOLATION                 48403\n",
       "OFFENSE INVOLVING CHILDREN             40260\n",
       "CRIM SEXUAL ASSAULT                    22789\n",
       "SEX OFFENSE                            20172\n",
       "GAMBLING                               14755\n",
       "INTERFERENCE WITH PUBLIC OFFICER       14009\n",
       "LIQUOR LAW VIOLATION                   12129\n",
       "ARSON                                   9269\n",
       "HOMICIDE                                5879\n",
       "KIDNAPPING                              4734\n",
       "INTIMIDATION                            3324\n",
       "STALKING                                2866\n",
       "OBSCENITY                                422\n",
       "PUBLIC INDECENCY                         134\n",
       "OTHER NARCOTIC VIOLATION                 122\n",
       "NON-CRIMINAL                              96\n",
       "CONCEALED CARRY LICENSE VIOLATION         90\n",
       "NON - CRIMINAL                            38\n",
       "HUMAN TRAFFICKING                         28\n",
       "RITUALISM                                 16\n",
       "NON-CRIMINAL (SUBJECT SPECIFIED)           4\n",
       "Name: Primary Type, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# counting specific number of elements within specific column\n",
    "chicago_df['Primary Type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='count', ylabel='Primary Type'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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yWEmSJEnqFpMCHVNVtwOfopcYIMlqwAuAR1XV7KqaDRxE3xKCqroXeA+wWpJnAu8FXpTkcSNtkrwwyZb0Nhl8Q7OZ4Mimgm8ETmYIVfU74MPAqUnWbPrYqul/6yR7t5rPAX48ke9AkiRJktTj0we66WTglc37JwM3VdVNrfpvAo9IslX7oKqqJG8DXltV+yeZD5yUZHPg3ua4c6vqf5O8DvhckjWAu5tjFk8gxuOBtwFXJ7kL+C3wf4A1mjG3Bu4CbgFeMZGTlyRJkiT1pOp+L/OWHtB2mr1BvetfnjDdYUiSNCHzXvzF6Q5BkjRDJFlUVf1LvAGXD0iSJEmS1FkmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqqFnTHYA02TbadBfmvfiL0x2GJEmSJD3gOFNAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHWUjyTUjHfz7ddx6ieeOd1hSBrS0Yd9abpDkCRJ6gxnCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFOirJiiSLk1ye5HtJntiU75vkgr62pyeZ17y/KMk1zXGXJZnTardukg8kWZrk+0kWJXlZUzc7yVVjxPOZJJf0lZ2Q5KYmzquTLEiyeZJlSbZstXt/ktevki9GkiRJkjrEpEB3La+qOVW1F/AG4B0TOPaw5rj3Aye2yj8E/BLYpaoeDRwAbDxeZ0k2BPYGNkyyQ1/1KVU1BzgI+I+m/3cBJzXH7g3sA5w8gfglSZIkSZgUUM/69G62J+oSYBuAJDsBjwWOr6p7Aarqlqp61xD9PB/4HHAWMH9Qg6q6DvgdsBFwGrBTkv2A9wKvrKq7VyJ+SZIkSeq0WdMdgKbN2kkWA2sBWwFPXYk+DgDOb97vAVw+khCYoAXAm4FfAOcwYNZCMyPguqq6ufn898DXgc9W1TdXYkxJkiRJ6jyTAt21vJmWT5InAGck2ROoUdq3yz+R5KHA6vSm/f+ZJG8CXgBsXlVbjxZEki2AnYFvVVUluSfJnlU1sv/AMc2+BDvSS0L0gqla3OxR8P5R+j0SOBJgo03WGm14SZIkSeo0lw+IqroE2BTYDLiN3hT9to2BW1ufDwN2AD4JvK8puxrYK8lqTZ9vb5IO648z/KHNeMuS3ADM5r5LCE6pqt2admckad/h39u8Bp3TaVU1t6rmrrv+muOEIEmSJEndZFJAJNmd3q/+twHXAVsneXhTtz2wF7C4fUyzhv944PFJHl5V1wMLgbclWb05di0g4wy/ADigqmZX1WzgMQzYV6Cqzm36f9FKnqYkSZIkqY/LB7prZE8B6N24v6iqVgArkrwQ+GhzU3838NKq+nV/B1W1PMnJwLHA3wEvpfc0guuT3A4sB17XOmS3JDe2Pr8HeBjw3Vafy5LckeRxA2J+C/DJJP+5knsXSJIkSZJaUjXaEnJpZnjYjhvUsW99/HSHIWlIRx/2pekOQZIkaUZJsqiq5g6qc/mAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHWUSQFJkiRJkjrKpIAkSZIkSR1lUkCSJEmSpI6aNd0BSJNt84134ejDvjTdYUiSJEnSA44zBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR/lIQs14N/zqOl583gHTHYakIXz0kC9OdwiSJEmd4kwBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHWUSQFJkiRJkjrKpIAkSZIkSR1lUmCaJdk2yWeSXJdkaZL3JFkzyTOTLG5edya5pnl/RpJ9k1zQ18/pSeY17y9qtV+c5Jym/IQkNzVlVydZMEZcRyb5YfO6NMk+rbr+/kfGXdEqW5xkdhPrr/vKn9a0ryQnt/o9NskJzfvdmnEWJ/lBktOa8lH7kyRJkiRNzKzpDqDLkgQ4F/hAVR2UZHXgNODtVXUc8KWm3UXAsVW1sPm87xDdHzbSvs8pVXVSkl2ARUnOqaq7++I6EHg5sE9V3Zpkb+D8JI+tqv8do//lVTWnr6/ZwMVVdeCAWH4PPC/JO6rq1r66U5tYP9P088hW3Wj9SZIkSZImwJkC0+upwF1V9VGAqloBHAO8JMk6kzlwVV0H/A7YaED164DjRm7Uq+p7wMeAo1ZxGPfQS4IcM6BuK+DGVrxXruKxJUmSJKnzTApMrz2ARe2CqroD+Amw8zjHPqk9hR54bl/9J1r1J/Yf3Pz6f11V3TxMXMDCpnxQ/5s0ZWu3ys4bLdYkO7Xq3gcclmSDvvFOAb6e5L+THJNkwyH7kyRJkiQNyeUD0ytATaC87T5T6JOc3lc/2vKBY5K8DNgROOB+xDrU8oFBsbZV1R1JzgCOBpa3yj+a5EtNjAcBL0+y13j9/THY5EjgSICHbrbWWE0lSZIkqbOcKTC9lgBz2wVJ1ge2A5ZO0pinVNVuwKHAGUkG3TFfDTymr2zvpnwy/Dvwd8BD24VV9bOq+khVHURvqcGew3ZYVadV1dyqmrvW+muu0mAlSZIkaaYwKTC9vgask+RwgGajwZOB06vqd5M5cFWdS29JwIsGVL8beNfIsoAkc4AjgPdPUiy3A5+ilxigGfOAJGs077cENgFumozxJUmSJKmrTApMo6oq4BDgBUmuA64F7gLeuAq6b6/5/+oobd4CvCbJff45qKrPAh8BvpPkh8B/Ai+sqp+vZCz9ewDMG9DmZGDT1udnAFcluZzeUxiOaz35YJj+JEmSJEnjSO++VJq5Nt15g3rOiU+Y7jAkDeGjh3xxukOQJEmacZIsqqq5g+qcKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR82a7gCkyTZ7w1346CFfnO4wJEmSJOkBx5kCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjfCShZrzrfvVznn3e26Y7DEl9vnDI8dMdgiRJUuc5U0CSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kU0LiSHJKkkuzefF4tyalJrkpyZZLLkuzQ1L2kKbuiqT+or6/Lk5zZV3ZRkrmtz7OTXNW83zfJBc37RyZZ3LxuT7Ksef/Vyf4OJEmSJGkmmjXdAehBYQHwLWA+cAJwKLA18KiqujfJtsBvmz/fBOxdVb9Osi6w2UgnSR5OLxH15CQPrarfTiSIqroSmNP0dTpwQVWdcz/PTZIkSZI6y5kCGlNzY/+XwN/RSwoAbAX8vKruBaiqG6vql8DmwG+AO5vyO6tqWau7vwE+DnwZeO7UnIEkSZIkaTQmBTSeg4EvVtW1wO1J9gY+BTynmbp/cpJHN20vB34BLEvy0STP6evrUOBs4Ex6sw8kSZIkSdPIpIDGswA4q3l/FrCgqm4EdgPeANwLfC3J/lW1AjgAmAdcC5yS5ASAJH8B3FJVPwa+BuydZKOm3xow7qCyoSU5MsnCJAv/cMeEVilIkiRJUme4p4BGlWQT4KnAnkkKWB2oJK+tqt8D/w38d5Jf0JtR8LWqKuBS4NIkXwE+Sm8fggXA7kluaLpfH3g+8CHgNmAkQQCwMXDr/Ym9qk4DTgPYYOdt7leCQZIkSZJmKmcKaCzzgDOqavuqml1V2wHL6G0UuDX0nkQAPAr4cZKtm+UFI+Y05asBL6C3MeHsqpoNHMSflhBcBLwwSZrPLwIunNxTkyRJkiQ5U0BjWQC8s6/s08Dp9PYXeEhTdinwXmAL4KQmYXAXcAvwCuDJwE1VdVOrn28Cj0iyFb1f9HcHLm9mJCyktzRhxP5Jbmx9fsEqODdJkiRJ6jyTAhpVVe07oOxU4NRRDvkxveUG/ZYCj+/rZwW9pxiMeOUoMVwErD2g6pJRYpAkSZIkDWnc5QNJdk3ytSRXNZ8fleT4yQ9NkiRJkiRNpmH2FPhPelO57waoqiv40/PqJUmSJEnSg9QwSYF1qurSvrJ7JiMYSZIkSZI0dYZJCtyaZCea58YnmQf8fFKjkiRJkiRJk26YjQaPotkdPslN9B5Jd9ikRiVJkiRJkibduEmBqvoR8LQkDwVWq6rfTH5YkiRJkiRpsg3z9IFNkpwKXAxclOQ9STaZ/NAkSZIkSdJkGmZPgbOAW4DnA/Oa92dPZlCSJEmSJGnyDbOnwMZV9dbW57clOXiS4pEkSZIkSVNkmKTAhUnmA59qPs8DPj95IUmr1i4bbsUXDjl+usOQJEmSpAecYZYPvBz4JPD75nUW8Jokv0lyx2QGJ0mSJEmSJs8wTx9YbyoCkSRJkiRJU2uYpw+ck+TZSYaZVSBJkiRJkh4khrnR/yBwGHBdkncm2X2SY5IkSZIkSVNg3KRAVX21qg4D9gZuAL6S5DtJXpxkjckOUJIkSZIkTY6hlgQk2QQ4Angp8H3gPfSSBF+ZtMgkSZIkSdKkGjUpkOT05s9zgYuBdYDnVNVzq+rsqnoVsO6URClJkiRJkla5sZ4+8Kjmz/dW1dcHNaiquas+JGnVuu6Xt/JXn/7QdIchTcjnn//S6Q5BkiRJHTBWUmCdJI8GfpVk7/7Kqvre5IUlSZIkSZIm21hJgW2Ak4EMqCvgqZMSkSRJkiRJmhJjJQWurypv/CVJkiRJmqGGevqAJEmSJEmaecZKCrxuyqKQJEmSJElTbtSkQFV9eSoDkSRJkiRJU8vlA5IkSZIkddS4SYEke05FIJIkSZIkaWoNM1Pgg0kuTfIPSTac7IAkSZIkSdLUGDcpUFX7AIcB2wELk3wyydMnPbIpkKSSfLz1eVaSW5Jc0Co7OMkVSX6Y5MokBzfl70uyOMnVSZY37xcnmZee45Ncl+TaJBcm2aPV5w1NX1ck+UaS7QfEdnqSl/eVHZzkC837Fa0xFyd5fVN+UZK5rWNmJ7mqeb9v37k9K8nCJD9ozu+kpvyEJMcOiGngmK36sb6T05PM62t/ZyvG5X19H973XY2U/0vr/Z1JrmnenzHGpZYkSZIkDTBrmEZVdV2S44GFwKnAo5MEeGNVnTuZAU6y3wJ7Jlm7qpYDTwduGqlMshdwEvD0qlqWZAfgK0l+VFVHNW1mAxdU1ZzWca8EngjsVVW/S/IM4LNJ9qiqu5pm+1XVrUneDBwPvKwvtjOB1wP/0Sqb35QDLG+POVHNspD3An9VVT9MMgs4cpzDxhxznO/kwHH6XjpG3/tV1a2tz29u+rwIOLaqFo7TtyRJkiRpgGH2FHhUklOAHwBPBZ5TVQ9v3p8yyfFNhf8G/qp5v4A/3XQDHAv8a1UtA2j+fAdw3Dh9vg54VVX9rjnuy8B36M246HcJsM2A8q8CuyfZCiDJOsDTgPPHP6WhvBZ4e1X9sInxnqp6/yrqW5IkSZL0IDDMngLvBb5H71fvo6rqewBV9TN6v3A/2J0FzE+yFvAo4H9adXsAi/raL2zKB0qyPvDQqlo65HEHMOBGv6pWAOcCf90UPRe4sKp+03xeu2+6/aGtwz8xUg58YZRQ9+TPz208Y405jBPbx/fV7dTX95NadRc2Zf+DJEmSJGmVGXP5QJLVgZ9W1ccH1Y9W/mBSVVc0090X8Oc30AFqiLJh9B93YZItgJsZPblyJnAi8B56Swfa6+bHmsp/2MiU+pGp/CsR7yD3a8kCcFxVnTPyYWRPgcZElg+MK8mRNMsh1tp044nGKUmSJEmdMOZMgebX6k2SrDlF8UyXz9LbO+DMvvIlwNy+sr2Bq0frqKruAH6bZMdxjtsP2L4Z4y2jdPdtYKtmb4MnMvqv/itjCfCYVdjfA0pVnVZVc6tq7prrrzfd4UiSJEnSA9Iwywd+DHw7yT8nec3Ia7IDm2IfAd5SVVf2lZ8EvKH5tX3kV/c3AieP09+JwKlJ1m6OexqwD/DJdqNmc8NXA4cn+bOfs6uqgE8BHwO+0NqkcFU4EXhjkl2bGFebgddVkiRJkjSGYZ4+8LPmtRowI39yraob6U3R7y9fnOR1wOeSrAHcDby2qhaP0+X/BTYCrkyyAvhf4KAmCdA/xs+TnAkcBbx1QF9n0tvY8PV95Wv3rcv/YlX1txlVs2zi1cCZzSaGBXy+1eT4pn6k/bb3d8xx7NTX90eq6tRV1LckSZIkaYD0foyWZq4Ndppd+7x7JuyJqS75/PNfOt0hSJIkaYZIsqiq+pfGA0PMFEiyGb3H1+0BrDVSXlVPXWURSpIkSZKkKTfMngKfAH4I7AC8GbgBuGwSY5IkSZIkSVNgmKTAJlX1YeDuqvpGVb0EePwkxyVJkiRJkibZMBsN3t38+fMkf0Vv08FtJy8kSZIkSZI0FYZJCrwtyQbAP9HbVX994JhJjUqSJEmSJE26cZMCVXVB8/bXwH6TG44kSZIkSZoqwzx9YAfgVcDsdvuqeu7khSVJkiRJkibbMMsHzgc+DHwOuHdSo5EkSZIkSVNmmKTAXVV16qRHIkmSJEmSplSqauwGyd8AuwBfBn4/Ul5V35vc0KRVY+7cubVw4cLpDkOSJEmSpkWSRVU1d1DdMDMFHgn8LfBU/rR8oJrPkiRJkiTpQWqYpMAhwI5V9YfJDkaSJEmSJE2d1YZoczmw4STHIUmSJEmSptgwMwW2AH6Y5DLuu6eAjySUJEmSJOlBbJikwL9MehSSJEmSJGnKjZsUqKpvTEUgkiRJkiRpao2aFEjyraraJ8lv6D1t4I9VQFXV+pMenSRJkiRJmjSjJgWqap/mz/WmLhxp1bv+l7/iOeecO91haAb43LznTXcIkiRJ0io15tMHkqyW5KqpCkaSJEmSJE2dMZMCVXUvcHmSh01RPJIkSZIkaYoM8/SBrYAlSS4FfjtS6CMJJUmSJEl6cBsmKfDmSY9CkiRJkiRNubGePrAW8ApgZ+BK4MNVdc9UBSZJkiRJkibXWHsKfAyYSy8h8Czg5CmJSJIkSZIkTYmxlg88oqoeCZDkw8ClUxOSJEmSJEmaCmPNFLh75I3LBiRJkiRJmnnGmimwV5I7mvcB1m4+B6iqWn/So5MkSZIkSZNm1JkCVbV6Va3fvNarqlmt9yYEZqgkK5IsTnJVks8l2bBVt0eSrye5Nsl1Sf45SZq6I5Lc0hy7JMk5SdZp6k5IclNT98MkH0iyWlN3epJlTd3iJN8Z0N8PkxyTZK3m/SNbMb02yQen9EuSJEmSpBlirOUD6qblVTWnqvYEbgeOAkiyNvBZ4J1VtSuwF/BE4B9ax57dHLsH8Afg0FbdKVU1B3gE8EjgKa2645rj5lTVE/v7A/4SeBOwGfBq4P3p2QZ4OfCGVXPqkiRJktQtJgU0lkuAbZr3fwN8u6q+DFBVvwNeCby+/6Aks4CHAr8c0OeawFqj1A1UVbcB1wNbVdUXgZ8DhwOnACdU1dB9SZIkSZL+xKSABkqyOrA/vdkBAHsAi9ptqmopsG6SkeUkhyZZDNwEbAx8rtX8mKbu58C1VbW4VXdia/nAJwbE8jB6iYQrmqJXA28HNquqj6/sOUqSJElS15kUUL+1m5v32+jd2H+lKQ9QoxwzUj4y3X9L4ErguFabkeUDmwMPTTK/VddePnBYq/zQJEuAHwHvqaq7AKrqZ8DXgQ+MdhJJjkyyMMnCP9zx6/HOWZIkSZI6yaSA+i1vbt63pzfV/6imfAkwt90wyY7AnVX1m3Z5VRW9WQJP7u+8qu4GvjioboCzm/0JngScnGTLVt29zWugqjqtquZW1dw1199giKEkSZIkqXtMCmigqvo1cDRwbJI1gE8A+yR5Gvxx48FTgXeP0sU+wNL+wuZpBU8cVDdGLJcAHwf+cSLnIEmSJEkam0kBjaqqvg9cDsyvquXAQcDxSa6htzzgMuC9rUMObfYFuAJ4NPDWVt3IngJXAbOA97fq2nsKLE6y5oBw3gW8OMl6q+r8JEmSJKnr0pvpLc1cG+60cz3pXaNNaJCG97l5z5vuECRJkqQJS7KoquYOqnOmgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSOmjXdAUiTbeeNNuRz85433WFIkiRJ0gOOMwUkSZIkSeookwKSJEmSJHWUSQFJkiRJkjrKpIAkSZIkSR1lUkCSJEmSpI4yKSBJkiRJUkf5SELNeEt/eSeHfPpb0x2GHqTOe/4+0x2CJEmSNGmcKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUGEKSFUkWJ1mS5PIkr0myWlO3b5JfN/Ujr6c1dVsmOSvJ0iRXJ/lCkl2TzE6yvO+Yw5tjbkhyZTPOl5s+/qdp85Mkt7SOmd203zTJRUme2Rf3q5O8f6zx+tpflOSaZuxvJ9ltQPllSeb0HfeeJDeNfCet8sOTXNV8b1cnOTbJ+5rxr+6LaV6S05PMa45dI8k7k1zX9HFpkmf1fUcjx566yi62JEmSJHXIrOkO4EFieVXNAUiyOfBJYAPgX5r6i6vqwPYBSQKcB3ysquY3ZXOALYCfAktH+hxgv6q6Ncm/Am+sqsc1xx8BzK2qV7bGGXl7JjAf+FKrn/nAcc37scZrO6yqFiY5EjgReG5f+Yub8qc3468GHNKc05OBi5ryZwGvBp5RVT9Lshbwt1V1VFM/G7igHVOS9nf4VmArYM+q+n2SLYCn9H9HQ5yPJEmSJGkUzhSYoKq6GTgSeGVad+QD7AfcXVUfbB27uKounsBw3wR2HrLtOcCBSR4Cf7zp3hr41gTGG2bsS4BtWp/3A64CPgAsaJW/ATi2qn4GUFV3VdV/DjNwknWAlwGvqqrfN8f/oqo+NeGzkCRJkiSNyqTASqiqH9H77jZvip7UNzV/J2BPYNEY3ezUd8yTBrQ5ELhyyJhuAy4FDmiK5gNnV1VNYLy254wy9gHA+a3PC+jNUjiPXlJijaZ8vPMfy87AT6rqjjHaXNg6l2NWchxJkiRJ6jSXD6y89iyBQcsHxjt+rOn8FyZZAVwBHD+BmEaWEHym+fMlQ47X9okky4EbgFf1lT8UWB3YGyDJmsCzgWOq6jdJ/gd4BvD5CcS8ssZcPtAsfzgSYO1Nt5iCcCRJkiTpwceZAishyY7ACuDmMZotAR6zkkPsV1VzqurwqvrVBI47H9g/yd7A2lX1vZUY+7Bm7IOr6qftcmAHevspvK8pO4De3gpXJrkB2Ic/LSG4P+d/PfCwJOut5PFU1WlVNbeq5j5k/Q1XthtJkiRJmtFMCkxQks2ADwLvbU3NH+TrwEOSvKx17F8kecoYx9wvVXUnvY3+PkJv1sCq7v9uejMXHp/k4fQSAC+tqtlVNZte0uAZzZ4A7wDenWRLgCQPSXL0kOP8DvgwcGozG4EkWyV54ao+J0mSJEnqMpMCw1m7Wbu+BPgq8GXgza36/j0F5jUJg0OAp6f3SMIlwAnAz5pj+tf4D3XDPIQzgb2As/rKV8l4VbUcOBl4LfBMWksFquq39DY2fE5VfYHejIKvNue+iIktVzkeuAW4OslV9GZB3NKqb+8pcMbKnIskSZIkdV3G/rFbevDbaKfda993f2i6w9CD1HnP32e6Q5AkSZLulySLqmruoDpnCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqqFnTHYA02XbaaF3Oe/4+0x2GJEmSJD3gOFNAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHWUjyTUjPfTX/2Bo8/76XSHoQk69ZDtpjsESZIkacZzpoAkSZIkSR1lUkCSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpsJKSbJnkrCRLk1yd5AtJdk0yO8nyJIub8jOSrNEcs2+SC5r3RySpJPu3+jykKZvXfL4oydzm/Q1JPt1qOy/J6X0xfSbJJX1lJyQ5dozz+J8m1p8kuaV5v7g5jxuSXJnkiiTfSLJ967gVrbaLk7y+KT8wyfeTXN6c/8tbcdzUtL0qyXNbfR2T5K4kG7TK1knyiWb8q5J8K8m6Td2bkixp4lqc5HETuHSSJEmSpMas6Q7gwShJgPOAj1XV/KZsDrAF8FNgaVXNSbI68BXgr4FPDOjqSmAB8LXm83zg8jGGnptkj6paMiCmDYG9gTuT7FBVy4Y5l6p6XHP8EcDcqnplq0+A/arq1iRvBo4HXtZUL6+qOX0xrAGcBjy2qm5M8hBgdqvJKVV1UpKHAxcn2byq7m2+g8uAQ4DTm7b/CPyiqh7Z9L0bcHeSJwAHAntX1e+TbAqsOcy5SpIkSZLuy5kCK2c/4O6q+uBIQVUtrqqL242qagVwKbDNKP1cDDw2yRrNr+A7A4vHGPck4I2j1D0f+BxwFr3kwqp2CaOfx4j16CWabgOoqt9X1TX9jarqB8A9wKZJdgLWpZdwWNBqthVwU+uYa6rq9035rc17qurWqvrZSp+VJEmSJHWYSYGVsyewaLxGSdYCHgd8cZQmBXwVeCZwEPDZcbr8FLB3kp0H1C0AzmxeCwbU318HAOe3Pq/dt3zg0Kq6nd45/DjJmUkOS/Jn/4w10/3vBW5pxX0xsFuSzZtmHwFel+SSJG9LsktT/mVguyTXJnl/kqdMwrlKkiRJUieYFJgcOyVZTO8X859U1RVjtB35ZX8+vZvjsawATgTe0C5MsgW9WQbfqqprgXuS7LmSsfe7MMnNwNOAT7bKl1fVnNbrbICqeimwP70ZEsfSu7kfcUzzvZwEHFpVRe+8z2qWEZwLvKDpZzGwY3O+GwOXJXl4Vd0JPAY4kl5S4exm6cN9JDkyycIkC5ffcfsq+iokSZIkaWYxKbByltC7MR3N0ma9/c7A49ub6vWrqkvpzTzYtLmhH8/HgScDD2uVHQpsBCxLcgO9dfyragnBfsD29M75LcMcUFVXVtUpwNPpLWsYcUqTQHhSVV2c5FHALsBXmrjn05rlUFV3VtW5VfUPwP8Dnt2Ur6iqi6rqX4BX9o0xcuxpVTW3quauvf7GK3HakiRJkjTzmRRYOV8HHpJkZNM9kvxF/1T2qvo58Hr6ftkf4A2MvlfAfVTV3cApwKtbxQuAA6pqdlXNppewWGX7ClTV8ma8w5OMeoedZN0k+7aK5gA/HqPrBcAJI3FX1dbANkm2T/KXSTZq+l0TeAS9ZQm7tZYSDDOGJEmSJGkUJgVWQjPt/RDg6ek9knAJcAIwaMO784F1kjxpjP7+u6ounEAIH6Z5ckSS2fRmDXy31d8y4I7Wo/qOT3LjyGsC47Rj/Dm95Q1HNUX9ewq8Ewjw2iTXNMsE3gwcMUa38+k9xaHtvKZ8J+AbSa4Evg8sBD5Nb1PCjzWPO7yCXrLghJU5J0mSJEnquvTub6WZa4udH1WHnvj56Q5DE3TqIdtNdwiSJEnSjJBkUVXNHVTnTAFJkiRJkjrKpIAkSZIkSR1lUkCSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOmrWdAcgTbbtNlyTUw/ZbrrDkCRJkqQHHGcKSJIkSZLUUSYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSO8pGEmvF+9ct7OPecW6c7jIGeN2/T6Q5BkiRJUoc5U0CSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUeJBIsiLJ4iRXJfmvJOsMKP9ckg1bx+yR5OtJrk1yXZJ/TpKmboskFyS5PMnVSb6Q5JFNX4uT3J5kWfP+q0lmN2M8s9XmziTXNO/PSHJEkvf2xX1RkrlJ/qdp95Mkt7T6mJ3khiSbNu23TfKZJt6lSd6TZM2mbt8kleQ5rf4vSLLvpF8ASZIkSZqBTAo8eCyvqjlVtSfwB+AVA8pvB44CSLI28FngnVW1K7AX8ETgH5rj3gJ8par2qqpHAK+vqiubvuY0xx7XfH7aSBBV9aVWm4XAYc3nw8cKvqoe1xzzf4CzR/qoqhtG2jQJi3OB86tqF2BXYF3g7a2ubgTeNJEvTpIkSZI0mEmBB6eLgZ0HlF8CbNO8/xvg21X1ZYCq+h3wSuD1Tf1W9G6waeqvmLRoh/dU4K6q+ihAVa0AjgFeMjIzArgc+HWSp09TjJIkSZI0Y5gUeJBJMgt4FnBlX/nqwP70fuEH2ANY1G5TVUuBdZOsD7wP+HCSC5O8KcnWkx78+AbFfAfwE+6bBHkbcPwUxiVJkiRJM5JJgQePtZMspjdl/yfAh/vKbwM2Br7SlAeoUfqqqvoSsCPwn8DuwPeTbHY/Yxx1vCGPHy3m+5RX1cUASZ40akfJkUkWJln46ztuG3J4SZIkSeoWkwIPHstb6/BfVVV/aJcD2wNr0uwpACwB5rY7SLIjcGdV/Qagqm6vqk9W1d8ClwFPvp8x3gZs1Fe2MXDrkMcPinl9YDtgaV/btzPG3gJVdVpVza2quRusv8mQw0uSJElSt5gUmCGq6tfA0cCxSdYAPgHsk+Rp8MeNB08F3t18fmrrCQbrATvRm4Fwf1wG/GWSLZt+5wIPAX465PFfA9ZJcnhz/OrAycDpzZ4If9TslbARvQ0UJUmSJEkrwaTADFJV36e3Ed/8qloOHAQcn+QaensQXAaMPDLwMcDCJFfQ26DwQ1V12f0c/xfAPwJfaJY0/DuwoKruHfL4Ag4BXpDkOuBa4C7gjaMc8nZg2/sTsyRJkiR1WXr3YdLMtfNOc+rd7/rqdIcx0PPmbTrdIUiSJEma4ZIsqqq5g+qcKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR82a7gCkybbhRrN43rxNpzsMSZIkSXrAcaaAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHXUrOkOQJpsv7v1Hr7/oZunO4yBHv3Szac7BEmSJEkd5kwBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRJgUkSZIkSeookwKSJEmSJHWUSQFJkiRJkjrKpMAYkpyS5NWtz19K8qHW55OTvCbJ7CTLkyxuvQ5vtXt0kkryzL7+VzRtr0ryX0nWacq3TfKZJNclWZrkPUnWbOr2bfp6TqufC5Ls27w/MMn3k1ye5OokL+8bc3aSG5Os1le+OMljk5yQ5NimLEmOb+K4NsmFSfZoHXNDkk1H+e6OSXJXkg2SbNL6Xv43yU2tz2smubN13B5Jvt6Md12Sf06Spu6IJPcmeVSr/VVJZo9+FSVJkiRJozEpMLbvAE8EaG6iNwX2aNU/Efh2835pVc1pvc5otVsAfKv5s21503ZP4A/AK5ob4HOB86tqF2BXYF3g7a3jbgTe1B9skjWA04DnVNVewKOBi9ptquoG4KfAk1rH7Q6sV1WX9nV5VHOOe1XVrsA7gM8mWat/7AEWAJcBh1TVbSPfC/BB4JTW9/SHVhxrA58F3tmMt1cz/j+Md+6SJEmSpIkzKTC2b9MkBeglA64CfpNkoyQPAR4OfH+sDpqb/HnAEcAzxrihvhjYGXgqcFdVfRSgqlYAxwAvGZlJAFwO/DrJ0/v6WA+YBdzWHPv7qrpmwFhnAvNbn+c3Zf1eB7yqqn7X9PdleomSw0Y9YSDJTvQSGcfz54mQsfwN8O1mHJpxXwm8vtXmAmCPJLtNoF9JkiRJ0gAmBcZQVT8D7knyMHrJgUuA/wGeAMwFrmj90r1T3/KBkV/i/xJYVlVL6f1q/+z+cZLMAp4FXEkv+bCoL447gJ/QSxqMeBu9m+52u9vp/dL+4yRnJjmsf5lA41PAwc24AIcCZ/XFtD7w0CbutoXcd7bEIAvoJRkuBnZLsvk47UcMOvelwLpNPAD3Au8G3jhkn5IkSZKkUZgUGN/IbIGRpMAlrc/fabXrXz5wcVO+gD/dcJ/FfX85XzvJYno32j8BPgwEqAFx3Kd8pP9W8mGk/KXA/sClwLHAR/o7qqr/BZYA+yeZA9xdVVeN+S2MEsco5gNnVdW99JZCvGAV9N0u/yTw+CQ7jNpRcmSShUkW/vI3tw05vCRJkiR1y6zxm3TeyL4Cj6S3fOCnwD8BdzDghrstyerA84HnJnkTvZveTZKsV1W/odlToO+YJc0x7bL1ge2ApcAmraq301tff0+7fVVdCVyZ5OPAMnpLF/qNLCH4BQOWDlTVHUl+m2THqvpRq2pv4BtjnPOjgF2ArzT7A64J/Ah432jHtCwBntzX347AnVX1m6Y/quqeJCfTW94wUFWdRm9/BR4xe854SQxJkiRJ6iRnCozv28CBwO1VtaKZor8hvSUEl4xz7NOAy6tqu6qaXVXbA58GDh7jmK8B64w8vaBJLJwMnD6ytn9Es/Z+I3ob8pFk3ZGnEDTmAD8eZZxP01vK8GdLB1pOBE5tNgAkydOAfej9Uj+aBcAJzfnOrqqtgW2SbD/GMSM+AezTjDOy8eCp9JYL9Dud3ve72RD9SpIkSZIGMCkwvivpPXXgu31lv66qW1tl/XsKHE3vBvm8vv4+TW9DvYGqqoBDgBckuQ64FriL0dfQvx3Ytnkf4LVJrmmWJbyZwbMEqKpfNef0i6paNkrf/5feEwSuTHIN8M/AQVW1vNXmiuYRhzcm+Td6sw/6z/k87rux4UBNvwcBxzfjXdmM/94Bbf9AL2Ew7H4FkiRJkqQ+6d2DSjPXI2bPqU8c/+XpDmOgR7/UnIYkSZKkyZVkUVXNHVTnTAFJkiRJkjrKpIAkSZIkSR1lUkCSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHTVrugOQJts6m87i0S/dfLrDkCRJkqQHHGcKSJIkSZLUUSYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSO8pGEmvHu/sXv+d+Trp+Wsbc8dudpGVeSJEmShuFMAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6asYlBZKsSLI4yVVJ/ivJOklmJ7mqr90JSY5t3p+eZFlz3A+T/Eur3UVJ5vYdu2+SC1qfn5VkYZIfNMefNCCuI5Lc0oxxdZKXDSgfeT2iddwxSe5KskFffwPHbM7rpr7+Nuw7dlmS3frK/j3Jawec28FJrmjGuDLJwa2605PMG+U6PDpJJXlm8/m8Jpbrk/y6FdsT299xkg2SnJFkafM6Y+Tcm+tYSV7VGue9SY4YFIMkSZIkaWwzLikALK+qOVW1J/AH4BVDHndcVc0B5gAvSrLDMAcl2RN4L/DCqno4sCfwo1Gan92MsS/wr0m2aJe3Xle3jlkAXAYcMoExT+nr71d9cZwFzG/1txowDzi779z2Ak4CDqqq3YHnAicledSYX8qf4v5W8ydVdUhz7i8FLm7F9p2+4z4M/KiqdqqqnYBlwIda9TcD/5hkzSFikCRJkiSNYSYmBdouBnae4DFrNX/+dsj2rwXeXlU/BKiqe6rq/WMdUFU3A0uB7cdql2QnYF3geJqb65Uds8+ZtJICwJOBG6rqx33tjgX+taqWNeMsA94BHDdO3KGXZDgCeEaStcZq3zpuZ+AxwFtbxW8B5jbfBcAtwNeAFw3TpyRJkiRpdDM2KZBkFvAs4MohDzkxyWLgRuCs5sZ9GHsCiyYY247AjsD1TdGhfdP9127KF9C7gb8Y2C3J5kOOeUyrrwv7K6vqCuDeZiYA9BIEZw7oZ48B4yxsysfyl8CyqloKXAQ8e5z2Ix4BLK6qFa1YVwCL+8Z8J/BPSVYfsl9JkiRJ0gAzMSmwdnNzvxD4Cb3p6DVK23b5yPKBLYH9kzxxEmI7tIntTODlVXV7U96/fGB5Uz6fXoLiXuBc4AVDjtNePrDfKG3OBOY3yZODgP8a0Cb8+Xc3qKzfAnpLFGj+XDBG22H6vk95M2PhUuBvRu0oObLZc2HhbXfePlozSZIkSeq0WdMdwCRY3tzc/1GS24CN+tptTG+9+n1U1Z1JLgL2AfrXuw+yhN6U98uHaHt2Vb1yiHY06/Z3Ab7Sm43PmvT2DXjfBMcczZnAl4FvAFeMMjNiCTAXuKJVtjdw9YC2I3GvDjwfeG6SN9G7od8kyXpV9ZtxYloCPDrJak0iZGS/g72AH/S1/VfgHOCbgzqqqtOA0wD22u6R4yUxJEmSJKmTZuJMgT9TVXcCP0+yP0CSjYED6G2Edx/NL+ePo7fmfxgnAm9Msmtz/GpJXrMKwl4AnFBVs5vX1sA2SbZfFWM2U/tvozcVf9DSAehtMviGJLObcWYDbwROHqPrpwGXV9V2TdzbA58GDh4ipuuB79PbQ2HE8cD3mrp22x/SS04cOF6/kiRJkqTBOpEUaBwOHN9M3/868ObmxnjEyJ4CV9Dbh+DcVt3nk9zYvO4zzb5Zn/9q4MwkPwCuAraaYGz9ewo8kd7SgfP62p0HzB9izGP6+ps9yrhnArsPGGfk3BYDrwM+l+SHwOeA1zblI/6j9d1cQi+Z0d/fpxljqn+fvwN2bR5duBTYtSkb5O3AtkP2K0mSJEnqkypnVmtm22u7R9aX/nFg3mPSbXnsRB9+IUmSJEmrVpJFVTV3UF2XZgpIkiRJkqQWkwKSJEmSJHWUSQFJkiRJkjrKpIAkSZIkSR1lUkCSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkddSs6Q5AmmxrbPEQtjx25+kOQ5IkSZIecJwpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6ykcSasa7++bf8ItTL5r0cbY4et9JH0OSJEmSViVnCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjjIpIEmSJElSR5kUkCRJkiSpo0wKSJIkSZLUUSYFJEmSJEnqqElLCiTZNslnklyXZGmS9yRZs6nbN8mvkyxuXl9tyk9IclOr/J1N+UVJrmmVn9Nq/7skm7fGvbP1/k1JliS5ojnucWP11xf/EUneO944TV/P7Dv21Une37zfJ8mlSX7YvI5stTshybGtz8uS7NbX178neW3znV3Qiu3eJI9qtbsqyezm/bpJPtB8799PsijJy0a5TlsmOatpe3WSLyTZNcnsJFf1tf1jvElOTzKv9R3M7Ws7co2/33zX30xyYF9fI9f66iQLWnWnN9/FyPX5zjDnLUmSJEmamElJCiQJcC5wflXtAuwKrAu8vdXs4qqa07ye1io/pVX++lb5Ya3yea3yW4F/GhDDE4ADgb2r6lHA04CfDtHfaAaOA5wJzO8rmw+cmWRL4JPAK6pqd2Af4OVJ/mqUMc5q95VkNWAecPaAtjcCbxqlnw8BvwR2qapHAwcAG/c3aq7TecBFVbVTVT0CeCOwxSj9TtTFVfXoqtoNOBp4b5L9W/WnVNUc4CDgP5Ks0ao7rnV9ntgqH+u8JUmSJEkTMFkzBZ4K3FVVHwWoqhXAMcBLkqyzisf6CHBokv6b3q2AW6vq900Mt1bVzyZhnHOAA5M8BKD51Xpr4FvAUcDpVfW9kRiA1wKvZ7D+BMOTgRuq6scD2l4A7DFgZsFOwGOB46vq3mbcW6rqXQP62A+4u6o+OFJQVYur6uJR4ltpVbUYeAvwygF11wG/AzYaoquB5y1JkiRJmrjJSgrsASxqF1TVHcBPgJ2boie1poe3f/k9plXenpb/iVb5ia3yO+ndsP9jXwxfBrZLcm2S9yd5Sl/9aP2NZuA4VXUbcCm9X+Ohd1N/dlXVoO8BWNiU/5mqugK4N8lerb7OHCWee4F30/tlv20P4PKRhMA49hwQX9tOre9oMfCKIfocy/eA3fsLk+wNXFdVN7eKT2yN/YlW+WjnLUmSJEmaoFmT1G+AGqf84qo6cECbU6rqpAHlh1XVwlHGOxVYnOTkkYKqujPJY4An0ftF/Owkr6+q04fobzR/Nk5j5Bf+zzR/vqQpH+17GFR2n76SLKE3rf7/jNH2k8CbkuwwWoMm4fICYPOq2nqMvgZZ2kzvH+nrhAke/2fh9H0+ptnrYEf+lFQZcVxV/dleD41hzvtI4EiAbTdaVashJEmSJGlmmayZAkuA/o3n1ge2A5au6sGq6lf0bhT/oa98RVVdVFX/Qm/a+vMnYxzgfGD/5hfvtUeWCzDgewAeA1w9xjBnAn9Nbw+EK/p+Pe+P5x7gZOB1reKrgb2a/Qioqrc3N/brD+hiSRPPVHk08IPW51Oa/QYOBc5IstYwnYxy3v1tTququVU1d+N1N7g/MUuSJEnSjDVZSYGvAeskORwgyer0buJOr6rfTdKY/wa8nGb2Q5LdkuzSqp8DDFqbf7/Ggd6sBOAiessL2tP93wcckWROE9MmwLvoTX8fqKqWArcB72T0pQNtp9NLIGzWHH89vSUKb2u+d5qb7f5f6QG+Djyk/WSCJH8xYKnF/dY8MeCf6X0n91FV5zYxv2gCXZ5O67wlSZIkSRM3KUmBZj39IcALklwHXAvcxf1bB97eA+CrA8a8ld5O+g9pitYFPtY87u4K4BHACcP2N5oB44w4E9iL3hMERtr+HHgh8J9Jfgh8B/hIVX2uddzxSW4cebX62r0ZZ7x4/kBvWcPmreKXApsA1ydZBHyVAb+qt67T05tHEi6h9x2tzIaMn2+dx381ZU8aeSQhvWTA0VX1tVGOfwvwmpEZDtx3T4HFaR5nOc55S5IkSZImIL37Qmnm2uthu9WXj/2PSR9ni6P3nfQxJEmSJGmikiyqqv6l7cDkLR+QJEmSJEkPcCYFJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqSOMikgSZIkSVJHmRSQJEmSJKmjTApIkiRJktRRs6Y7AGmyrbH5emxx9L7THYYkSZIkPeA4U0CSJEmSpI4yKSBJkiRJUkeZFJAkSZIkqaNSVdMdgzSpkvwGuGa649C02RS4dbqD0LTx+neb17/bvP7yn4Fu8/rf1/ZVtdmgCjcaVBdcU1VzpzsITY8kC73+3eX17zavf7d5/eU/A93m9R+eywckSZIkSeookwKSJEmSJHWUSQF1wWnTHYCmlde/27z+3eb17zavv/xnoNu8/kNyo0FJkiRJkjrKmQKSJEmSJHWUSQHNGEkOSHJNkuuTvH5AfZKc2tRfkWTv6YhTk2OI639Yc92vSPKdJHtNR5yaHONd/1a7v0iyIsm8qYxPk2uY659k3ySLkyxJ8o2pjlGTZ4j//m+Q5HNJLm+u/4unI05NjiQfSXJzkqtGqffvfzPYENffv/8NwaSAZoQkqwPvA54FPAJYkOQRfc2eBezSvI4EPjClQWrSDHn9lwFPqapHAW/FdWYzxpDXf6Tdu4AvTW2EmkzDXP8kGwLvB55bVXsAL5jqODU5hvz3/yjg6qraC9gXODnJmlMaqCbT6cABY9T797+Z7XTGvv7+/W8IJgU0UzwWuL6qflRVfwDOAg7qa3MQcEb1fBfYMMlWUx2oJsW417+qvlNVv2w+fhfYdopj1OQZ5t9/gFcBnwZunsrgNOmGuf5/A5xbVT8BqCr/GZg5hrn+BayXJMC6wO3APVMbpiZLVX2T3jUdjX//m8HGu/7+/W84JgU0U2wD/LT1+cambKJt9OA00Wv7d8B/T2pEmkrjXv8k2wCHAB+cwrg0NYb5939XYKMkFyVZlOTwKYtOk22Y6/9e4OHAz4ArgX+sqnunJjw9APj3P43w73+jmDXdAUirSAaU9T9aY5g2enAa+tom2Y/e/xT2mdSINJWGuf7/Dryuqlb0fizUDDLM9Z8FPAbYH1gbuCTJd6vq2skOTpNumOv/TGAx8FRgJ+ArSS6uqjsmOTY9MPj3P/n3v3GYFNBMcSOwXevztvR+EZhoGz04DXVtkzwK+BDwrKq6bYpi0+Qb5vrPBc5qEgKbAs9Ock9VnT8lEWoyDfvf/1ur6rfAb5N8E9gLMCnw4DfM9X8x8M7qPYf7+iTLgN2BS6cmRE0z//7Xcf79b3wuH9BMcRmwS5Idms2D5gOf7WvzWeDwZhfaxwO/rqqfT3WgmhTjXv8kDwPOBf7WXwdnnHGvf1XtUFWzq2o2cA7wDyYEZoxh/vv/GeBJSWYlWQd4HPCDKY5Tk2OY6/8TerNESLIFsBvwoymNUtPJv/91mH//G44zBTQjVNU9SV5Jb1fx1YGPVNWSJK9o6j8IfAF4NnA98Dt6vxxoBhjy+v8fYBPg/c2vxfdU1dzpilmrzpDXXzPUMNe/qn6Q5IvAFcC9wIeqauDjq/TgMuS//28FTk9yJb2p5K+rqlunLWitUknOpPdUiU2T3Aj8C7AG+Pe/Lhji+vv3vyGkN5NKkiRJkiR1jcsHJEmSJEnqKJMCkiRJkiR1lEkBSZIkSZI6yqSAJEmSJEkdZVJAkiRJkqQHqCQfSXJzkqGenJPkr5NcnWRJkk+O196kgCRJ0gNEklcnWWe645AkPaCcDhwwTMMkuwBvAP6yqvYAXj3eMSYFJEmSHjheDZgUkCT9UVV9E7i9XZZkpyRfTLIoycVJdm+qXga8r6p+2Rx783j9mxSQJEmagCSHJ7kiyeVJPp5k+yRfa8q+luRhTbvTk8xrHXdn8+e+SS5Kck6SHyb5RHqOBrYGLkxy4fScnSTpQeI04FVV9RjgWOD9TfmuwK5Jvp3ku0nGnWEwaxKDlCRJmlGS7AG8id60zFuTbAx8DDijqj6W5CXAqcDB43T1aGAP4GfAt5v+Tk3yGmC/qrp10k5CkvSglmRd4InAfyUZKX5I8+csYBdgX2Bb4OIke1bVr0brz6SAJEnS8J4KnDNy015Vtyd5AvC8pv7jwLuH6OfSqroRIMliYDbwrVUerSRpJloN+FVVzRlQdyPw3aq6G1iW5Bp6SYLLxupMkiRJwwlQ47QZqb+H5u9a6f2Us2arze9b71fgDzWSpCFV1R30bvhfAL3/xyTZq6k+H9ivKd+U3nKCH43Vn0kBSZKk4X0N+OskmwA0ywe+A8xv6g/jT7/43wA8pnl/ELDGEP3/BlhvVQUrSXrwS3ImcAmwW5Ibk/wdvf/f/F2Sy4El9P4/A/Al4LYkVwMXAsdV1W1j9W9WWpIkaUhVtSTJ24FvJFkBfB84GvhIkuOAW4AXN83/E/hMkkvpJRN+O8QQpwH/neTnVbXfqj8DSdKDTVUtGKXqzzYRrKoCXtO8hpLeMZIkSZIkqWtcPiBJkiRJUkeZFJAkSZIkqaNMCkiSJEmS1FEmBSRJkiRJ6iiTApIkSZIkdZRJAUmSJEmSOsqkgCRJkiRJHWVSQJIkSZKkjvr/7ziTRnSfdygAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (15, 10))\n",
    "sns.countplot(y= 'Primary Type', data = chicago_df, order = chicago_df['Primary Type'].value_counts().iloc[:15].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2005-12-31    455811\n",
       "2006-12-31    794684\n",
       "2007-12-31    621848\n",
       "2008-12-31    852053\n",
       "2009-12-31    783900\n",
       "2010-12-31    700691\n",
       "2011-12-31    352066\n",
       "2012-12-31    335670\n",
       "2013-12-31    306703\n",
       "2014-12-31    274527\n",
       "2015-12-31    262995\n",
       "2016-12-31    265462\n",
       "2017-12-31     11357\n",
       "Freq: A-DEC, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# frequency of occurence of crimes in each year\n",
    "chicago_df.resample('Y').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of Crimes')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# Resample is a Convenience method for frequency conversion and resampling of time series.\n",
    "\n",
    "plt.plot(chicago_df.resample('Y').size())\n",
    "plt.title('Crimes Count Per Year')\n",
    "plt.xlabel('Years')\n",
    "plt.ylabel('Number of Crimes')\n",
    "# as we can see in graph number of crimes decreasing over a years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of Crimes')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "# Resample is a Convenience method for frequency conversion and resampling of time series.\n",
    "\n",
    "plt.plot(chicago_df.resample('M').size())\n",
    "plt.title('Crimes Count Per Month')\n",
    "plt.xlabel('Months')\n",
    "plt.ylabel('Number of Crimes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Date</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-31</td>\n",
       "      <td>33983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-02-28</td>\n",
       "      <td>32042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-03-31</td>\n",
       "      <td>36970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-30</td>\n",
       "      <td>38963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-05-31</td>\n",
       "      <td>40572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>23235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2016-10-31</td>\n",
       "      <td>23314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>21140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2016-12-31</td>\n",
       "      <td>19580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2017-01-31</td>\n",
       "      <td>11357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date      0\n",
       "0   2005-01-31  33983\n",
       "1   2005-02-28  32042\n",
       "2   2005-03-31  36970\n",
       "3   2005-04-30  38963\n",
       "4   2005-05-31  40572\n",
       "..         ...    ...\n",
       "140 2016-09-30  23235\n",
       "141 2016-10-31  23314\n",
       "142 2016-11-30  21140\n",
       "143 2016-12-31  19580\n",
       "144 2017-01-31  11357\n",
       "\n",
       "[145 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chicago_prophet = chicago_df.resample('M').size().reset_index()\n",
    "chicago_prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "chicago_prophet.columns = ['Date', 'Crime Count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "chicago_prophet_df = pd.DataFrame(chicago_prophet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Crime Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-31</td>\n",
       "      <td>33983</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-02-28</td>\n",
       "      <td>32042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-03-31</td>\n",
       "      <td>36970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-30</td>\n",
       "      <td>38963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-05-31</td>\n",
       "      <td>40572</td>\n",
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       "      <td>2016-09-30</td>\n",
       "      <td>23235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2016-10-31</td>\n",
       "      <td>23314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2016-11-30</td>\n",
       "      <td>21140</td>\n",
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       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2016-12-31</td>\n",
       "      <td>19580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2017-01-31</td>\n",
       "      <td>11357</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  Crime Count\n",
       "0   2005-01-31        33983\n",
       "1   2005-02-28        32042\n",
       "2   2005-03-31        36970\n",
       "3   2005-04-30        38963\n",
       "4   2005-05-31        40572\n",
       "..         ...          ...\n",
       "140 2016-09-30        23235\n",
       "141 2016-10-31        23314\n",
       "142 2016-11-30        21140\n",
       "143 2016-12-31        19580\n",
       "144 2017-01-31        11357\n",
       "\n",
       "[145 rows x 2 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chicago_prophet_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# STEP #4: MAKE PREDICTIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "chicago_prophet_df_final = chicago_prophet_df.rename(columns={'Date':'ds', 'Crime Count':'y'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Importing plotly failed. Interactive plots will not work.\n",
      "INFO:numexpr.utils:NumExpr defaulting to 4 threads.\n",
      "INFO:fbprophet:Disabling weekly seasonality. Run prophet with weekly_seasonality=True to override this.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f9d86f24280>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from fbprophet import Prophet\n",
    "\n",
    "m = Prophet()\n",
    "m.fit(chicago_prophet_df_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Forcasting into the future in 365 days\n",
    "future = m.make_future_dataframe(periods=365)\n",
    "forecast = m.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>trend</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>trend_lower</th>\n",
       "      <th>trend_upper</th>\n",
       "      <th>additive_terms</th>\n",
       "      <th>additive_terms_lower</th>\n",
       "      <th>additive_terms_upper</th>\n",
       "      <th>yearly</th>\n",
       "      <th>yearly_lower</th>\n",
       "      <th>yearly_upper</th>\n",
       "      <th>multiplicative_terms</th>\n",
       "      <th>multiplicative_terms_lower</th>\n",
       "      <th>multiplicative_terms_upper</th>\n",
       "      <th>yhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-01-31</td>\n",
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       "      <td>39963.624165</td>\n",
       "      <td>71639.472300</td>\n",
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       "      <th>1</th>\n",
       "      <td>2005-02-28</td>\n",
       "      <td>60339.063153</td>\n",
       "      <td>33329.619350</td>\n",
       "      <td>68976.843115</td>\n",
       "      <td>60339.063153</td>\n",
       "      <td>60339.063153</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>-9621.875889</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50717.187264</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-03-31</td>\n",
       "      <td>60194.487093</td>\n",
       "      <td>41580.812346</td>\n",
       "      <td>75543.918236</td>\n",
       "      <td>60194.487093</td>\n",
       "      <td>60194.487093</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>-1316.121235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58878.365858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-30</td>\n",
       "      <td>60054.574777</td>\n",
       "      <td>44713.972820</td>\n",
       "      <td>77125.381472</td>\n",
       "      <td>60054.574777</td>\n",
       "      <td>60054.574777</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>1152.227091</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61206.801868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-05-31</td>\n",
       "      <td>59909.998717</td>\n",
       "      <td>48664.557271</td>\n",
       "      <td>82309.104405</td>\n",
       "      <td>59909.998717</td>\n",
       "      <td>59909.998717</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>5505.352549</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65415.351267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>2018-01-27</td>\n",
       "      <td>9946.266510</td>\n",
       "      <td>-11366.900045</td>\n",
       "      <td>21734.494901</td>\n",
       "      <td>9800.024783</td>\n",
       "      <td>10087.073256</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>-4303.833060</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5642.433450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>2018-01-28</td>\n",
       "      <td>9933.009136</td>\n",
       "      <td>-11264.928905</td>\n",
       "      <td>21895.610033</td>\n",
       "      <td>9785.626288</td>\n",
       "      <td>10074.474938</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>-4442.268308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5490.740828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>2018-01-29</td>\n",
       "      <td>9919.751763</td>\n",
       "      <td>-13215.422842</td>\n",
       "      <td>23022.825733</td>\n",
       "      <td>9771.387287</td>\n",
       "      <td>10061.876619</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>-4592.938494</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5326.813269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>9906.494390</td>\n",
       "      <td>-11597.988529</td>\n",
       "      <td>22503.652125</td>\n",
       "      <td>9758.119175</td>\n",
       "      <td>10049.278301</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>-4755.641260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5150.853131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>2018-01-31</td>\n",
       "      <td>9893.237017</td>\n",
       "      <td>-11630.693418</td>\n",
       "      <td>22219.154689</td>\n",
       "      <td>9744.775217</td>\n",
       "      <td>10036.679982</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>-4930.222749</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4963.014269</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>510 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ds         trend    yhat_lower    yhat_upper   trend_lower  \\\n",
       "0   2005-01-31  60469.647981  39963.624165  71639.472300  60469.647981   \n",
       "1   2005-02-28  60339.063153  33329.619350  68976.843115  60339.063153   \n",
       "2   2005-03-31  60194.487093  41580.812346  75543.918236  60194.487093   \n",
       "3   2005-04-30  60054.574777  44713.972820  77125.381472  60054.574777   \n",
       "4   2005-05-31  59909.998717  48664.557271  82309.104405  59909.998717   \n",
       "..         ...           ...           ...           ...           ...   \n",
       "505 2018-01-27   9946.266510 -11366.900045  21734.494901   9800.024783   \n",
       "506 2018-01-28   9933.009136 -11264.928905  21895.610033   9785.626288   \n",
       "507 2018-01-29   9919.751763 -13215.422842  23022.825733   9771.387287   \n",
       "508 2018-01-30   9906.494390 -11597.988529  22503.652125   9758.119175   \n",
       "509 2018-01-31   9893.237017 -11630.693418  22219.154689   9744.775217   \n",
       "\n",
       "      trend_upper  additive_terms  additive_terms_lower  additive_terms_upper  \\\n",
       "0    60469.647981    -4975.708247          -4975.708247          -4975.708247   \n",
       "1    60339.063153    -9621.875889          -9621.875889          -9621.875889   \n",
       "2    60194.487093    -1316.121235          -1316.121235          -1316.121235   \n",
       "3    60054.574777     1152.227091           1152.227091           1152.227091   \n",
       "4    59909.998717     5505.352549           5505.352549           5505.352549   \n",
       "..            ...             ...                   ...                   ...   \n",
       "505  10087.073256    -4303.833060          -4303.833060          -4303.833060   \n",
       "506  10074.474938    -4442.268308          -4442.268308          -4442.268308   \n",
       "507  10061.876619    -4592.938494          -4592.938494          -4592.938494   \n",
       "508  10049.278301    -4755.641260          -4755.641260          -4755.641260   \n",
       "509  10036.679982    -4930.222749          -4930.222749          -4930.222749   \n",
       "\n",
       "          yearly  yearly_lower  yearly_upper  multiplicative_terms  \\\n",
       "0   -4975.708247  -4975.708247  -4975.708247                   0.0   \n",
       "1   -9621.875889  -9621.875889  -9621.875889                   0.0   \n",
       "2   -1316.121235  -1316.121235  -1316.121235                   0.0   \n",
       "3    1152.227091   1152.227091   1152.227091                   0.0   \n",
       "4    5505.352549   5505.352549   5505.352549                   0.0   \n",
       "..           ...           ...           ...                   ...   \n",
       "505 -4303.833060  -4303.833060  -4303.833060                   0.0   \n",
       "506 -4442.268308  -4442.268308  -4442.268308                   0.0   \n",
       "507 -4592.938494  -4592.938494  -4592.938494                   0.0   \n",
       "508 -4755.641260  -4755.641260  -4755.641260                   0.0   \n",
       "509 -4930.222749  -4930.222749  -4930.222749                   0.0   \n",
       "\n",
       "     multiplicative_terms_lower  multiplicative_terms_upper          yhat  \n",
       "0                           0.0                         0.0  55493.939734  \n",
       "1                           0.0                         0.0  50717.187264  \n",
       "2                           0.0                         0.0  58878.365858  \n",
       "3                           0.0                         0.0  61206.801868  \n",
       "4                           0.0                         0.0  65415.351267  \n",
       "..                          ...                         ...           ...  \n",
       "505                         0.0                         0.0   5642.433450  \n",
       "506                         0.0                         0.0   5490.740828  \n",
       "507                         0.0                         0.0   5326.813269  \n",
       "508                         0.0                         0.0   5150.853131  \n",
       "509                         0.0                         0.0   4963.014269  \n",
       "\n",
       "[510 rows x 16 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast\n",
    "# creates trend, upper bound and lower bound basd on the crime count dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure = m.plot(forecast, xlabel='Date', ylabel='Crime Rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure3 = m.plot_components(forecast)\n",
    "# in first figure the trend is go down\n",
    "# second graph seasonality shows that crime rate is low in the beginning of the year and goes up in July"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}