Crimes-in-Chicago-analysis-final.ipynb

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     "text": [
      "Requirement already satisfied: dask in /home/kuntalac/miniconda3/lib/python3.9/site-packages (2021.11.1)\n",
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   "source": [
    "# importing the libraries \n",
    "!pip install dask\n",
    "!pip install pyarrow\n",
    "!pip install plotly\n",
    "import dask\n",
    "import dask.dataframe as dd\n",
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import seaborn as sns\n",
    "import os\n",
    "import glob\n",
    "import folium\n",
    "import plotly.express as px\n",
    "from dask.diagnostics import ProgressBar \n",
    "from collections import Counter\n",
    "import warnings \n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
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    "# 1. Dataset:\n",
    "This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2005 to 2016. "
   ]
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    "# 2. Variables of the dataset:\n",
    "\n",
    "ID - Unique identifier for the record.\n",
    "\n",
    "Case Number - The Chicago Police Department RD Number (Records Division Number), which is unique to the incident.\n",
    "\n",
    "Date - Date when the incident occurred. this is sometimes a best estimate.\n",
    "\n",
    "Block - The partially redacted address where the incident occurred, placing it on the same block as the actual address.\n",
    "\n",
    "IUCR - The Illinois Unifrom Crime Reporting code. This is directly linked to the Primary Type and Description. See the list of IUCR codes at https://data.cityofchicago.org/d/c7ck-438e.\n",
    "\n",
    "Primary Type - The primary description of the IUCR code.\n",
    "\n",
    "Description - The secondary description of the IUCR code, a subcategory of the primary description.\n",
    "\n",
    "Location Description - Description of the location where the incident occurred.\n",
    "\n",
    "Arrest - Indicates whether an arrest was made.\n",
    "\n",
    "Domestic - Indicates whether the incident was domestic-related as defined by the Illinois Domestic Violence Act.\n",
    "\n",
    "Beat - Indicates the beat where the incident occurred. A beat is the smallest police geographic area – each beat has a dedicated police beat car. Three to five beats make up a police sector, and three sectors make up a police district. The Chicago Police Department has 22 police districts. See the beats at https://data.cityofchicago.org/d/aerh-rz74.\n",
    "\n",
    "District - Indicates the police district where the incident occurred. See the districts at https://data.cityofchicago.org/d/fthy-xz3r.\n",
    "\n",
    "Ward - The ward (City Council district) where the incident occurred. See the wards at https://data.cityofchicago.org/d/sp34-6z76.\n",
    "\n",
    "Community Area - Indicates the community area where the incident occurred. Chicago has 77 community areas. See the community areas at https://data.cityofchicago.org/d/cauq-8yn6.\n",
    "\n",
    "FBI Code - Indicates the crime classification as outlined in the FBI's National Incident-Based Reporting System (NIBRS). See the Chicago Police Department listing of these classifications at http://gis.chicagopolice.org/clearmap_crime_sums/crime_types.html.\n",
    "\n",
    "X Coordinate - The x coordinate of the location where the incident occurred in State Plane Illinois East NAD 1983 projection. This location is shifted from the actual location for partial redaction but falls on the same block.\n",
    "\n",
    "Y Coordinate - The y coordinate of the location where the incident occurred in State Plane Illinois East NAD 1983 projection. This location is shifted from the actual location for partial redaction but falls on the same block.\n",
    "\n",
    "Year - Year the incident occurred.\n",
    "\n",
    "Updated On - Date and time the record was last updated.\n",
    "\n",
    "Latitude - The latitude of the location where the incident occurred. This location is shifted from the actual location for partial redaction but falls on the same block.\n",
    "\n",
    "Longitude - The longitude of the location where the incident occurred. This location is shifted from the actual location for partial redaction but falls on the same block.\n",
    "\n",
    "Location - The location where the incident occurred in a format that allows for creation of maps and other geographic operations on this data portal. This location is shifted from the actual location for partial redaction but falls on the same block."
   ]
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   "source": [
    "# 3. Load data files:"
   ]
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    {
     "data": {
      "text/plain": [
       "['Data/Chicago_Crimes_2005_to_2007.csv',\n",
       " 'Data/Chicago_Crimes_2008_to_2011.csv',\n",
       " 'Data/Chicago_Crimes_2012_to_2017.csv']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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   ],
   "source": [
    "#Loading the four CSV files\n",
    "from glob import glob\n",
    "filenames=sorted(glob(os.path.join(\"Data\",\"*.csv\")))\n",
    "filenames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "dask_all_file=dd.read_csv(filenames,error_bad_lines=False,assume_missing=True,dtype={'ID': np.int64,'PrimaryType': 'str','FBI Code': 'object','Beat': np.uint16,'IUCR': 'str','Latitude': 'object',\n",
    "'Y Coordinate': 'object','Location': 'str'},  parse_dates=['Date'],infer_datetime_format=True)"
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   "source": [
    "# 4. Overview of dataset:"
   ]
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       "Dask DataFrame Structure:\n",
       "               Unnamed: 0     ID Case Number            Date   Block    IUCR Primary Type Description Location Description Arrest Domestic    Beat District     Ward Community Area FBI Code X Coordinate Y Coordinate     Year Updated On Latitude Longitude Location\n",
       "npartitions=25                                                                                                                                                                                                                                                        \n",
       "                  float64  int64      object  datetime64[ns]  object  object       object      object               object   bool     bool  uint16  float64  float64        float64   object      float64       object  float64     object   object   float64   object\n",
       "                      ...    ...         ...             ...     ...     ...          ...         ...                  ...    ...      ...     ...      ...      ...            ...      ...          ...          ...      ...        ...      ...       ...      ...\n",
       "...                   ...    ...         ...             ...     ...     ...          ...         ...                  ...    ...      ...     ...      ...      ...            ...      ...          ...          ...      ...        ...      ...       ...      ...\n",
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    {
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       "Unnamed: 0                     float64\n",
       "ID                               int64\n",
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       "      <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>0.0</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>2006.0</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.981912692</td>\n",
       "      <td>-87.771996</td>\n",
       "      <td>(41.981912692, -87.771996382)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</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>2006.0</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.775732538</td>\n",
       "      <td>-87.611920</td>\n",
       "      <td>(41.775732538, -87.611919814)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</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>2006.0</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.769897392</td>\n",
       "      <td>-87.593671</td>\n",
       "      <td>(41.769897392, -87.593670899)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.0</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>2006.0</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.942984005</td>\n",
       "      <td>-87.780057</td>\n",
       "      <td>(41.942984005, -87.780056951)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</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>2006.0</td>\n",
       "      <td>04/15/2016 08:55:02 AM</td>\n",
       "      <td>41.784210853</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                Block  \\\n",
       "0         0.0  4673626    HM274058 2006-04-02 13:00:00    055XX N MANGO AVE   \n",
       "1         1.0  4673627    HM202199 2006-02-26 13:40:48   065XX S RHODES AVE   \n",
       "2         2.0  4673628    HM113861 2006-01-08 23:16:00      013XX E 69TH ST   \n",
       "3         4.0  4673629    HM274049 2006-04-05 18:45:00  061XX W NEWPORT AVE   \n",
       "4         5.0  4673630    HM187120 2006-02-17 21:03:14      037XX W 60TH ST   \n",
       "\n",
       "   IUCR   Primary Type                   Description Location Description  \\\n",
       "0  2825  OTHER OFFENSE       HARASSMENT BY TELEPHONE            RESIDENCE   \n",
       "1  2017      NARCOTICS            MANU/DELIVER:CRACK             SIDEWALK   \n",
       "2  051A        ASSAULT           AGGRAVATED: HANDGUN                OTHER   \n",
       "3  0460        BATTERY                        SIMPLE            RESIDENCE   \n",
       "4  1811      NARCOTICS  POSS: CANNABIS 30GMS OR LESS                ALLEY   \n",
       "\n",
       "   Arrest  ...  Ward  Community Area  FBI Code  X Coordinate  Y Coordinate  \\\n",
       "0   False  ...  45.0            11.0        26     1136872.0     1936499.0   \n",
       "1    True  ...  20.0            42.0        18     1181027.0     1861693.0   \n",
       "2   False  ...   5.0            69.0       04A     1186023.0     1859609.0   \n",
       "3   False  ...  38.0            17.0       08B     1134772.0     1922299.0   \n",
       "4    True  ...  13.0            65.0        18     1152412.0     1864560.0   \n",
       "\n",
       "     Year              Updated On      Latitude  Longitude  \\\n",
       "0  2006.0  04/15/2016 08:55:02 AM  41.981912692 -87.771996   \n",
       "1  2006.0  04/15/2016 08:55:02 AM  41.775732538 -87.611920   \n",
       "2  2006.0  04/15/2016 08:55:02 AM  41.769897392 -87.593671   \n",
       "3  2006.0  04/15/2016 08:55:02 AM  41.942984005 -87.780057   \n",
       "4  2006.0  04/15/2016 08:55:02 AM  41.784210853 -87.716745   \n",
       "\n",
       "                        Location  \n",
       "0  (41.981912692, -87.771996382)  \n",
       "1  (41.775732538, -87.611919814)  \n",
       "2  (41.769897392, -87.593670899)  \n",
       "3  (41.942984005, -87.780056951)  \n",
       "4   (41.784210853, -87.71674491)  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dask_all_file.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Data Cleaning:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.1 Drop unwanted columns:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**We found the following columns not useful for our data analysis, so we decided to drop them.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_drop = ['Unnamed: 0','ID','Case Number','IUCR','X Coordinate','Y Coordinate','Updated On','Location' ]\n",
    "dask_all_file1 = dask_all_file.drop(columns_to_drop, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Block', 'Primary Type', 'Description', 'Location Description',\n",
       "       'Arrest', 'Domestic', 'Beat', 'District', 'Ward', 'Community Area',\n",
       "       'FBI Code', 'Year', 'Latitude', 'Longitude'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dask_all_file1.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2 Persist DataFrame in memory:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Persist is important because Dask DataFrame is lazy by default. It is often ideal to load, filter, and shuffle data once and keep this result in memory. Afterwards, each of the several complex queries can be based off of this in-memory data rather than have to repeat the full load-filter-shuffle process each time.**\n",
    "\n",
    "*Source: \"https://docs.dask.org/en/stable/dataframe-best-practices.html\"*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[                                        ] | 0% Completed |  2.9s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 24743: expected 23 fields, saw 24\\n'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########                                ] | 20% Completed |  6min 59.0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "b'Skipping line 132222: expected 23 fields, saw 41\\n'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 14min 40.9s\n",
      "CPU times: user 12min 54s, sys: 3min 22s, total: 16min 16s\n",
      "Wall time: 14min 40s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "with ProgressBar(): \n",
    "    dask_all_file1 = dask_all_file1.persist() # Persist the dataframe in memory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.3 Handle missing values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "cell_id": "00013-4a0f692c-632b-42ba-9914-bfa9efe36623",
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 101,
    "execution_start": 1636742513640,
    "source_hash": "1954315f",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dask Series Structure:\n",
       "npartitions=1\n",
       "Arrest    int64\n",
       "Year        ...\n",
       "dtype: int64\n",
       "Dask Name: dataframe-sum-agg, 76 tasks"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_values = dask_all_file1.isnull().sum()\n",
    "missing_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "cell_id": "00014-8c701668-bb14-4161-9a3c-f116566ca39e",
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 129,
    "execution_start": 1636742600658,
    "source_hash": "7a14fd37",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dask Series Structure:\n",
       "npartitions=1\n",
       "Arrest    float64\n",
       "Year          ...\n",
       "dtype: float64\n",
       "Dask Name: mul, 129 tasks"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_count = ((missing_values / dask_all_file1.index.size) * 100)\n",
    "missing_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "cell_id": "00015-2492a71d-a44d-4f7f-afd3-8b89381ef9be",
    "deepnote_cell_type": "code",
    "deepnote_to_be_reexecuted": false,
    "execution_millis": 1524838,
    "execution_start": 1636742724481,
    "source_hash": "c57e6bb7",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed |  1.5s\n",
      "CPU times: user 1.41 s, sys: 156 ms, total: 1.56 s\n",
      "Wall time: 1.54 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Date                    0.000000\n",
       "Block                   0.000000\n",
       "Primary Type            0.000000\n",
       "Description             0.000000\n",
       "Location Description    0.032803\n",
       "Arrest                  0.000000\n",
       "Domestic                0.000000\n",
       "Beat                    0.000000\n",
       "District                0.001479\n",
       "Ward                    0.001529\n",
       "Community Area          0.030643\n",
       "FBI Code                0.000000\n",
       "Year                    0.000000\n",
       "Latitude                1.244349\n",
       "Longitude               1.244349\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "with ProgressBar(): \n",
    "    missing_count_pct = missing_count.compute()\n",
    "missing_count_pct"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.4 Drop rows with missing values:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**As we have around 8 million of records and percentage of missing in each column is extremely low (less than 10%), we decided to drop the missing instead of updating which is very expensive operation.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 15.6 ms, sys: 31.2 ms, total: 46.9 ms\n",
      "Wall time: 25.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rows_to_drop = list(missing_count_pct[(missing_count_pct > 0) & (missing_count_pct < 5)].index)\n",
    "dask_all_file1 = dask_all_file1.dropna(subset=rows_to_drop)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Check after dropping missing**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dask Series Structure:\n",
       "npartitions=1\n",
       "Arrest    int64\n",
       "Year        ...\n",
       "dtype: int64\n",
       "Dask Name: dataframe-sum-agg, 101 tasks"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_values = dask_all_file1.isnull().sum()\n",
    "missing_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dask Series Structure:\n",
       "npartitions=1\n",
       "Arrest    float64\n",
       "Year          ...\n",
       "dtype: float64\n",
       "Dask Name: mul, 154 tasks"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_count = ((missing_values / dask_all_file1.index.size) * 100)\n",
    "missing_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed |  2.6s\n",
      "CPU times: user 3.31 s, sys: 78.1 ms, total: 3.39 s\n",
      "Wall time: 2.63 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Date                    0.0\n",
       "Block                   0.0\n",
       "Primary Type            0.0\n",
       "Description             0.0\n",
       "Location Description    0.0\n",
       "Arrest                  0.0\n",
       "Domestic                0.0\n",
       "Beat                    0.0\n",
       "District                0.0\n",
       "Ward                    0.0\n",
       "Community Area          0.0\n",
       "FBI Code                0.0\n",
       "Year                    0.0\n",
       "Latitude                0.0\n",
       "Longitude               0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "with ProgressBar(): \n",
    "    missing_count_pct = missing_count.compute()\n",
    "missing_count_pct"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.5 Handle Duplicates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.5.1 Drop duplicate records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 19.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "dask_all_file1 = dask_all_file1.drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Set Date as index**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 29.0s\n",
      "CPU times: user 33.8 s, sys: 13.3 s, total: 47 s\n",
      "Wall time: 29.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "with ProgressBar():\n",
    "    dask_all_file1 = dask_all_file1.set_index('Date') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 4263777 entries, 2005-01-01 00:00:00 to 2017-01-18 10:12:00\n",
      "Data columns (total 14 columns):\n",
      " #   Column                Dtype  \n",
      "---  ------                -----  \n",
      " 0   Block                 object \n",
      " 1   Primary Type          object \n",
      " 2   Description           object \n",
      " 3   Location Description  object \n",
      " 4   Arrest                bool   \n",
      " 5   Domestic              bool   \n",
      " 6   Beat                  uint16 \n",
      " 7   District              float64\n",
      " 8   Ward                  float64\n",
      " 9   Community Area        float64\n",
      " 10  FBI Code              object \n",
      " 11  Year                  float64\n",
      " 12  Latitude              object \n",
      " 13  Longitude             float64\n",
      "dtypes: bool(2), float64(5), object(6), uint16(1)\n",
      "memory usage: 406.6+ MB\n",
      "CPU times: user 32.9 s, sys: 12.2 s, total: 45.2 s\n",
      "Wall time: 30.5 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "dask_all_file1.compute().info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. Writing to Parquet file and Loading DataFrame from Parquet file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Dask DataFrame users are encouraged to store and load data using Parquet. Apache Parquet is a columnar binary format that is easy to split into multiple files (easier for parallel loading) and is generally much simpler to deal with.**\n",
    "\n",
    "Source: https://docs.dask.org/en/stable/dataframe-best-practices.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 34.5s\n",
      "CPU times: user 38.1 s, sys: 11.8 s, total: 49.9 s\n",
      "Wall time: 35.4 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "with ProgressBar():\n",
    "    dask_all_file1.to_parquet('crimes-2005-2016.snappy.parq', compression='SNAPPY')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 10.2 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "crimes_df = dd.read_parquet('crimes-2005-2016.snappy.parq', index='Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.69 s, sys: 2.3 s, total: 5.98 s\n",
      "Wall time: 6.44 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "crimes_df = crimes_df.persist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><strong>Dask DataFrame Structure:</strong></div>\n",
       "<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>Block</th>\n",
       "      <th>Primary Type</th>\n",
       "      <th>Description</th>\n",
       "      <th>Location Description</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>Domestic</th>\n",
       "      <th>Beat</th>\n",
       "      <th>District</th>\n",
       "      <th>Ward</th>\n",
       "      <th>Community Area</th>\n",
       "      <th>FBI Code</th>\n",
       "      <th>Year</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>npartitions=1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-01 00:00:00</th>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>object</td>\n",
       "      <td>bool</td>\n",
       "      <td>bool</td>\n",
       "      <td>uint16</td>\n",
       "      <td>float64</td>\n",
       "      <td>float64</td>\n",
       "      <td>float64</td>\n",
       "      <td>object</td>\n",
       "      <td>float64</td>\n",
       "      <td>object</td>\n",
       "      <td>float64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-18 10:12:00</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>\n",
       "<div>Dask Name: read-parquet, 1 tasks</div>"
      ],
      "text/plain": [
       "Dask DataFrame Structure:\n",
       "                      Block Primary Type Description Location Description Arrest Domestic    Beat District     Ward Community Area FBI Code     Year Latitude Longitude\n",
       "npartitions=1                                                                                                                                                          \n",
       "2005-01-01 00:00:00  object       object      object               object   bool     bool  uint16  float64  float64        float64   object  float64   object   float64\n",
       "2017-01-18 10:12:00     ...          ...         ...                  ...    ...      ...     ...      ...      ...            ...      ...      ...      ...       ...\n",
       "Dask Name: read-parquet, 1 tasks"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataframe structure\n",
    "crimes_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 0 ns, sys: 0 ns, total: 0 ns\n",
      "Wall time: 8.2 ms\n"
     ]
    },
    {
     "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>Block</th>\n",
       "      <th>Primary Type</th>\n",
       "      <th>Description</th>\n",
       "      <th>Location Description</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>Domestic</th>\n",
       "      <th>Beat</th>\n",
       "      <th>District</th>\n",
       "      <th>Ward</th>\n",
       "      <th>Community Area</th>\n",
       "      <th>FBI Code</th>\n",
       "      <th>Year</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>050XX W PATTERSON AVE</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>HARASSMENT BY TELEPHONE</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1634</td>\n",
       "      <td>16.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.946964747</td>\n",
       "      <td>-87.753144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>047XX W CONGRESS PKWY</td>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT:$300 &amp;UNDER</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1131</td>\n",
       "      <td>11.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>06</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.874125711</td>\n",
       "      <td>-87.743684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>030XX W FULTON BLVD</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>FORCIBLE ENTRY</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>1331</td>\n",
       "      <td>12.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>05</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.886474422</td>\n",
       "      <td>-87.701800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>058XX S NORDICA AVE</td>\n",
       "      <td>CRIMINAL DAMAGE</td>\n",
       "      <td>TO PROPERTY</td>\n",
       "      <td>RESIDENTIAL YARD (FRONT/BACK)</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>811</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>14</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.78581508</td>\n",
       "      <td>-87.797485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>073XX N DAMEN AVE</td>\n",
       "      <td>OTHER OFFENSE</td>\n",
       "      <td>VIOLATE ORDER OF PROTECTION</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>2424</td>\n",
       "      <td>24.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>42.014842024</td>\n",
       "      <td>-87.680487</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Block     Primary Type  \\\n",
       "Date                                                 \n",
       "2005-01-01  050XX W PATTERSON AVE    OTHER OFFENSE   \n",
       "2005-01-01  047XX W CONGRESS PKWY            THEFT   \n",
       "2005-01-01    030XX W FULTON BLVD         BURGLARY   \n",
       "2005-01-01    058XX S NORDICA AVE  CRIMINAL DAMAGE   \n",
       "2005-01-01      073XX N DAMEN AVE    OTHER OFFENSE   \n",
       "\n",
       "                               Description           Location Description  \\\n",
       "Date                                                                        \n",
       "2005-01-01         HARASSMENT BY TELEPHONE                      RESIDENCE   \n",
       "2005-01-01  FINANCIAL ID THEFT:$300 &UNDER                      RESIDENCE   \n",
       "2005-01-01                  FORCIBLE ENTRY                      RESIDENCE   \n",
       "2005-01-01                     TO PROPERTY  RESIDENTIAL YARD (FRONT/BACK)   \n",
       "2005-01-01     VIOLATE ORDER OF PROTECTION                      RESIDENCE   \n",
       "\n",
       "            Arrest  Domestic  Beat  District  Ward  Community Area FBI Code  \\\n",
       "Date                                                                          \n",
       "2005-01-01   False     False  1634      16.0  38.0            15.0       26   \n",
       "2005-01-01   False     False  1131      11.0  24.0            25.0       06   \n",
       "2005-01-01   False     False  1331      12.0  27.0            27.0       05   \n",
       "2005-01-01   False     False   811       8.0  23.0            56.0       14   \n",
       "2005-01-01    True      True  2424      24.0  49.0             1.0       26   \n",
       "\n",
       "              Year      Latitude  Longitude  \n",
       "Date                                         \n",
       "2005-01-01  2005.0  41.946964747 -87.753144  \n",
       "2005-01-01  2005.0  41.874125711 -87.743684  \n",
       "2005-01-01  2005.0  41.886474422 -87.701800  \n",
       "2005-01-01  2005.0   41.78581508 -87.797485  \n",
       "2005-01-01  2005.0  42.014842024 -87.680487  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "crimes_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 7. Data Analysis and Visualization:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "cell_id": "00018-75ba7829-3153-4f76-b6f3-f3d673b745e6",
    "deepnote_cell_type": "markdown",
    "tags": []
   },
   "source": [
    "## 7.1 Top 10 Years with highest crime records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "cell_id": "00019-eb1e72bd-e917-4352-b5c4-182f939d3382",
    "deepnote_cell_type": "code",
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2005    448196\n",
       "2006    443504\n",
       "2007    434158\n",
       "2008    418947\n",
       "2009    385174\n",
       "2010    367797\n",
       "2011    349917\n",
       "2012    333872\n",
       "2013    303730\n",
       "2014    268947\n",
       "dtype: int64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crime_by_year=crimes_df.groupby([crimes_df.index.year]).size().compute()\n",
    "        \n",
    "top_10_years = crime_by_year.nlargest(10).sort_values(axis=0,ascending=False)\n",
    "top_10_years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top 10 high crime years\n",
    "top_10_years.plot(kind='bar', figsize=(10,8))\n",
    "plt.title('High Crime Years between 2005 to 2016)')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Number of Crimes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2005 we see the highest crimes reported**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.2. Top 10 of most violent community area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 62.5 ms, sys: 2.14 s, total: 2.2 s\n",
      "Wall time: 2.27 s\n"
     ]
    },
    {
     "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>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CommunityName</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Austin</th>\n",
       "      <td>276375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Shore</th>\n",
       "      <td>142048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Near North Side</th>\n",
       "      <td>139191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humboldt Park</th>\n",
       "      <td>135257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Englewood</th>\n",
       "      <td>127218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auburn Gresham</th>\n",
       "      <td>123574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Town</th>\n",
       "      <td>123068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Lawndale</th>\n",
       "      <td>122176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Near West Side</th>\n",
       "      <td>119817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roseland</th>\n",
       "      <td>116685</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Total\n",
       "CommunityName          \n",
       "Austin           276375\n",
       "South Shore      142048\n",
       "Near North Side  139191\n",
       "Humboldt Park    135257\n",
       "West Englewood   127218\n",
       "Auburn Gresham   123574\n",
       "West Town        123068\n",
       "North Lawndale   122176\n",
       "Near West Side   119817\n",
       "Roseland         116685"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "# upload the community file\n",
    "community_areas = pd.read_csv('chicago-community-areas.csv')\n",
    "# apply groupby function and calculate the amount of crime, rename to Total\n",
    "community_areas['Total'] = crimes_df.groupby('Community Area').size().compute().rename('Total')\n",
    "# sort value\n",
    "community_crime = community_areas.sort_values(by='Total', ascending=False).dropna()\n",
    "# drop unused columns and reindex\n",
    "community_crime = community_crime.drop(['CommunityArea','Side'], axis=1)\n",
    "community_crime = community_crime.set_index('CommunityName')\n",
    "# top 10 of most violent community area\n",
    "community_crime.nlargest(10,'Total')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top 10 high crime communities\n",
    "community_crime.nlargest(10,'Total').plot(kind='bar', figsize=(10,8))\n",
    "plt.title('High Crime Chicago Communities (2001-2017)')\n",
    "plt.xlabel('Chicago Community')\n",
    "plt.ylabel('Number of Crimes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Austin is the highest crime community area in Chicago as per the above chart.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.3. Count of Arrest, domestic and total crimes group by crime types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                   Arrest  Domestic   Total\n",
      "Primary Type                                               \n",
      "THEFT                              102482     21787  891547\n",
      "BATTERY                            178020    341020  770855\n",
      "CRIMINAL DAMAGE                     34015     38299  493515\n",
      "NARCOTICS                          458495       184  462487\n",
      "BURGLARY                            14499      1703  260876\n",
      "OTHER OFFENSE                       45170     78580  260054\n",
      "ASSAULT                             61718     56589  258235\n",
      "MOTOR VEHICLE THEFT                 15074       965  194550\n",
      "ROBBERY                             16307      2463  164055\n",
      "DECEPTIVE PRACTICE                  26534      1785  159178\n",
      "CRIMINAL TRESPASS                   88584      3961  122021\n",
      "WEAPONS VIOLATION                   35077       135   43842\n",
      "PROSTITUTION                        39672         3   39922\n",
      "PUBLIC PEACE VIOLATION              24683      1350   34810\n",
      "OFFENSE INVOLVING CHILDREN           5550     15723   28122\n",
      "CRIM SEXUAL ASSAULT                  2306      2081   15973\n",
      "SEX OFFENSE                          4274      1044   13858\n",
      "INTERFERENCE WITH PUBLIC OFFICER    10306        45   11124\n",
      "GAMBLING                             9759         1    9845\n",
      "LIQUOR LAW VIOLATION                 8082         6    8193\n",
      "ARSON                                 785       326    6577\n",
      "HOMICIDE                             2388       377    5681\n",
      "KIDNAPPING                            364       738    3354\n",
      "INTIMIDATION                          409       293    2277\n",
      "STALKING                              320       841    2074\n",
      "OBSCENITY                             260        45     320\n",
      "PUBLIC INDECENCY                      107         1     108\n",
      "OTHER NARCOTIC VIOLATION               59         0      89\n",
      "CONCEALED CARRY LICENSE VIOLATION      72         0      84\n",
      "NON-CRIMINAL                            7         1      80\n",
      "NON - CRIMINAL                          6         0      38\n",
      "HUMAN TRAFFICKING                       2         1      20\n",
      "RITUALISM                               1         3       9\n",
      "NON-CRIMINAL (SUBJECT SPECIFIED)        1         3       4\n",
      "CPU times: user 500 ms, sys: 344 ms, total: 844 ms\n",
      "Wall time: 842 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# get crime types\n",
    "crime_types = crimes_df[['Primary Type']]\n",
    "\n",
    "# get crime counts by primary type\n",
    "crime_type_total = crimes_df.groupby('Primary Type').size().compute()\n",
    "\n",
    "# get arrests and domestic counts for each primary crime type\n",
    "crime_type_counts = crimes_df[['Primary Type', 'Arrest', 'Domestic']].groupby('Primary Type').sum().compute()\n",
    "\n",
    "# add crime type totals column\n",
    "crime_type_counts['Total'] = crime_type_total\n",
    "\n",
    "# print all crimes (arrests, domestic, and totals)\n",
    "print(crime_type_counts.sort_values(by='Total', ascending=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.4. Plot crimes by primary type counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 703 ms, sys: 281 ms, total: 984 ms\n",
      "Wall time: 413 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "all_crime_types = crime_type_counts.sort_values(by='Total', ascending=True).drop(['Arrest', 'Domestic'], axis=1) # denotes column\n",
    "all_crime_types.plot(kind='barh', figsize=(10,8))\n",
    "plt.title('All Chicago Crimes by Type (2005-2016)')\n",
    "plt.xlabel('Number of Crime reports')\n",
    "plt.ylabel('Crime Type')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Theft is the most common crime type in Chicago.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.5. Top 10 types of crimes and their number of occurences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 734 ms, sys: 219 ms, total: 953 ms\n",
      "Wall time: 647 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "Prim_Type = crimes_df[\"Primary Type\"]\n",
    "Prim_Type2 = Counter(Prim_Type)\n",
    "Top_Prim_Type = Prim_Type2.most_common(10)\n",
    "x,y = zip(*Top_Prim_Type)\n",
    "x,y  = list(x),list(y)\n",
    "plt.figure(figsize=(15,8))\n",
    "ax = sns.barplot(x=x, y=y, palette = sns.cubehelix_palette(len(x), rot=-.4, reverse=True))\n",
    "plt.xticks(rotation= 15)\n",
    "plt.title(\"Top 10 primary types based on their number of occurances\")\n",
    "plt.xlabel(\"Primary Type\")\n",
    "plt.ylabel(\"Crimes\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Top 10 types of crimes are Theft, Battery, Criminal damage, Narcotics, Burglary, Other Offense, Assault, Motor Vehicle Theft , Robbery and Deceptive Practice**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Closer look at the Theft crimes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 406 ms, sys: 78.1 ms, total: 484 ms\n",
      "Wall time: 602 ms\n"
     ]
    },
    {
     "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>Primary Type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>$500 AND UNDER</th>\n",
       "      <td>314692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OVER $500</th>\n",
       "      <td>216373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FROM BUILDING</th>\n",
       "      <td>159521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RETAIL THEFT</th>\n",
       "      <td>115633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FINANCIAL ID THEFT: OVER $300</th>\n",
       "      <td>27687</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               Primary Type\n",
       "Description                                \n",
       "$500 AND UNDER                       314692\n",
       "OVER $500                            216373\n",
       "FROM BUILDING                        159521\n",
       "RETAIL THEFT                         115633\n",
       "FINANCIAL ID THEFT: OVER $300         27687"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "Theft_Crimes = crimes_df[crimes_df['Primary Type']== \"THEFT\"]\n",
    "Theft_Crimes_details = Theft_Crimes[['Primary Type', 'Description']].groupby('Description').count().compute().sort_values(by='Primary Type', ascending=False)\n",
    "Theft_Crimes_details.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Most of the theft reported cases are '$500 and under' description.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.6. Plot top crimes (>= 200,000 reports)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 391 ms, sys: 125 ms, total: 516 ms\n",
      "Wall time: 242 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "crime_type_counts[crime_type_counts['Total'] >= 200000].sort_values(by='Total', ascending=True).plot(kind='barh', figsize=(10,8))\n",
    "plt.title('Top Chicago Crimes (>= 200K reports) - (2005-2016)')\n",
    "plt.xlabel('Number of Crimes')\n",
    "plt.ylabel('Crime Type')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Above graph depicts that in Narcotics related crimes, the arrest rate is very high.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.7. Top 10 locations by no. of crimes (Based on Location Description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 859 ms, sys: 203 ms, total: 1.06 s\n",
      "Wall time: 742 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "Loc_Desc = crimes_df[\"Location Description\"]\n",
    "counted = Counter(Loc_Desc) \n",
    "top_Loc_Desc = counted.most_common(10)\n",
    "x,y = zip(*top_Loc_Desc)\n",
    "x,y = list(x),list(y)\n",
    "plt.figure(figsize = (20,8))\n",
    "ax = sns.barplot(x = x , y = y, palette = sns.cubehelix_palette(len(x), reverse=True))\n",
    "plt.xticks(rotation= 15)\n",
    "plt.xlabel(\"Location Description\")\n",
    "plt.ylabel(\"Crimes\")\n",
    "plt.title(\"Top 10 crime places based on Location Description \")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The most common crime location is Chicago streets.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.8. Get 'other offenses' crimes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 312 ms, sys: 93.8 ms, total: 406 ms\n",
      "Wall time: 410 ms\n"
     ]
    },
    {
     "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>Primary Type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TELEPHONE THREAT</th>\n",
       "      <td>85712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HARASSMENT BY TELEPHONE</th>\n",
       "      <td>59052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIOLATE ORDER OF PROTECTION</th>\n",
       "      <td>20191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OTHER VEHICLE OFFENSE</th>\n",
       "      <td>19460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HARASSMENT BY ELECTRONIC MEANS</th>\n",
       "      <td>17370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FALSE/STOLEN/ALTERED TRP</th>\n",
       "      <td>14351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OTHER WEAPONS VIOLATION</th>\n",
       "      <td>6442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VEHICLE TITLE/REG OFFENSE</th>\n",
       "      <td>4965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OTHER CRIME INVOLVING PROPERTY</th>\n",
       "      <td>4863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LICENSE VIOLATION</th>\n",
       "      <td>4771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Primary Type\n",
       "Description                                 \n",
       "TELEPHONE THREAT                       85712\n",
       "HARASSMENT BY TELEPHONE                59052\n",
       "VIOLATE ORDER OF PROTECTION            20191\n",
       "OTHER VEHICLE OFFENSE                  19460\n",
       "HARASSMENT BY ELECTRONIC MEANS         17370\n",
       "FALSE/STOLEN/ALTERED TRP               14351\n",
       "OTHER WEAPONS VIOLATION                 6442\n",
       "VEHICLE TITLE/REG OFFENSE               4965\n",
       "OTHER CRIME INVOLVING PROPERTY          4863\n",
       "LICENSE VIOLATION                       4771"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "other_offenses = crimes_df[crimes_df['Primary Type']=='OTHER OFFENSE']\n",
    "other_offense_crimes = other_offenses[['Primary Type', 'Description']].groupby('Description').count().compute().sort_values(by='Primary Type', ascending=False)\n",
    "other_offense_crimes.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.9. Plot top 20 other offense crimes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 422 ms, sys: 188 ms, total: 609 ms\n",
      "Wall time: 329 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "other_offense_crimes[:20].sort_values(by='Primary Type', ascending=True).plot(kind='barh', figsize=(6,6), color='#166DA7')\n",
    "plt.title('Top Chicago Other Offense Crimes (2005-2016)')\n",
    "plt.xlabel('Number of Crimes')\n",
    "plt.ylabel('Other Offense Crime')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.10. Comparing Arrested or Not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([False, True], [3078389, 1185388])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Arrest = crimes_df[\"Arrest\"]\n",
    "Arrest2 = Counter(Arrest)\n",
    "MostCommonCA = Arrest2.most_common()\n",
    "x,y = zip(*MostCommonCA)\n",
    "x,y = list(x),list(y)\n",
    "x,y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 188 ms, sys: 156 ms, total: 344 ms\n",
      "Wall time: 142 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "x[1] = \"Arrested\"\n",
    "x[0] = \"Not Arrested\" \n",
    "plt.figure(figsize=(10,4))\n",
    "sns.barplot(x = x , y = y , palette = \"dark\")\n",
    "plt.xlabel(\"Arresting\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.11. Plot Arrested Rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 62.5 ms, sys: 31.2 ms, total: 93.8 ms\n",
      "Wall time: 83.8 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "plt.pie(y,\n",
    "        labels = x, \n",
    "        autopct = \"%0.2f%%\", # Show data in percentage with 2 decimal point\n",
    "        startangle = 90,\n",
    "        radius = 1.6\n",
    "         )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Very few crime reports (~27.80%) end up in an arrest.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.12. Arrested rate per crime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 531 ms, sys: 266 ms, total: 797 ms\n",
      "Wall time: 842 ms\n"
     ]
    },
    {
     "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>Primary Type</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>Arrest (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ARSON</td>\n",
       "      <td>0.119355</td>\n",
       "      <td>11.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ASSAULT</td>\n",
       "      <td>0.238999</td>\n",
       "      <td>23.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BATTERY</td>\n",
       "      <td>0.230938</td>\n",
       "      <td>23.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>0.055578</td>\n",
       "      <td>5.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CONCEALED CARRY LICENSE VIOLATION</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>85.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CRIM SEXUAL ASSAULT</td>\n",
       "      <td>0.144369</td>\n",
       "      <td>14.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CRIMINAL DAMAGE</td>\n",
       "      <td>0.068924</td>\n",
       "      <td>6.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CRIMINAL TRESPASS</td>\n",
       "      <td>0.725973</td>\n",
       "      <td>72.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DECEPTIVE PRACTICE</td>\n",
       "      <td>0.166694</td>\n",
       "      <td>16.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GAMBLING</td>\n",
       "      <td>0.991265</td>\n",
       "      <td>99.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>HOMICIDE</td>\n",
       "      <td>0.420349</td>\n",
       "      <td>42.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>HUMAN TRAFFICKING</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>10.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>INTERFERENCE WITH PUBLIC OFFICER</td>\n",
       "      <td>0.926465</td>\n",
       "      <td>92.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>INTIMIDATION</td>\n",
       "      <td>0.179622</td>\n",
       "      <td>17.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>KIDNAPPING</td>\n",
       "      <td>0.108527</td>\n",
       "      <td>10.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>LIQUOR LAW VIOLATION</td>\n",
       "      <td>0.986452</td>\n",
       "      <td>98.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>MOTOR VEHICLE THEFT</td>\n",
       "      <td>0.077481</td>\n",
       "      <td>7.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NARCOTICS</td>\n",
       "      <td>0.991368</td>\n",
       "      <td>99.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NON - CRIMINAL</td>\n",
       "      <td>0.157895</td>\n",
       "      <td>15.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NON-CRIMINAL</td>\n",
       "      <td>0.087500</td>\n",
       "      <td>8.75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Primary Type    Arrest  Arrest (%)\n",
       "0                               ARSON  0.119355       11.94\n",
       "1                             ASSAULT  0.238999       23.90\n",
       "2                             BATTERY  0.230938       23.09\n",
       "3                            BURGLARY  0.055578        5.56\n",
       "4   CONCEALED CARRY LICENSE VIOLATION  0.857143       85.71\n",
       "5                 CRIM SEXUAL ASSAULT  0.144369       14.44\n",
       "6                     CRIMINAL DAMAGE  0.068924        6.89\n",
       "7                   CRIMINAL TRESPASS  0.725973       72.60\n",
       "8                  DECEPTIVE PRACTICE  0.166694       16.67\n",
       "9                            GAMBLING  0.991265       99.13\n",
       "10                           HOMICIDE  0.420349       42.03\n",
       "11                  HUMAN TRAFFICKING  0.100000       10.00\n",
       "12   INTERFERENCE WITH PUBLIC OFFICER  0.926465       92.65\n",
       "13                       INTIMIDATION  0.179622       17.96\n",
       "14                         KIDNAPPING  0.108527       10.85\n",
       "15               LIQUOR LAW VIOLATION  0.986452       98.65\n",
       "16                MOTOR VEHICLE THEFT  0.077481        7.75\n",
       "17                          NARCOTICS  0.991368       99.14\n",
       "18                     NON - CRIMINAL  0.157895       15.79\n",
       "19                       NON-CRIMINAL  0.087500        8.75"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "rate_per_crime = crimes_df.groupby('Primary Type')['Arrest'].mean().reset_index()\n",
    "rate_per_crime['Arrest (%)'] = rate_per_crime['Arrest'].round(4)*100\n",
    "rate_per_crime.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.28 s, sys: 406 ms, total: 1.69 s\n",
      "Wall time: 895 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "rate_per_crime = rate_per_crime.compute()\n",
    "rate_per_crime = rate_per_crime.sort_values(by='Arrest (%)', ascending=True).drop(['Arrest'], axis=1) # denotes column\n",
    "rate_per_crime.plot(x=\"Primary Type\", y=\"Arrest (%)\", kind='barh', figsize=(10,8), color='#16A778')\n",
    "plt.xlabel('Arrested Rate (%)')\n",
    "plt.ylabel('Crime Type')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Even if Theft is the most common crime in Chicago but Arrest rate is quite low comparatively.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.13. Plot crimes per day of the week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 797 ms, sys: 219 ms, total: 1.02 s\n",
      "Wall time: 705 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "crimes_df = crimes_df.compute()\n",
    "days = ['Monday','Tuesday','Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\n",
    "crimes_df2 = crimes_df.groupby([crimes_df.index.dayofweek]).size()\n",
    "crimes_df2.plot(kind='barh', figsize=(6,3), color='#132DA6')\n",
    "plt.title('All Chicago Crimes by Day of the Week (2005-2016)')\n",
    "plt.xlabel('Number of Crimes')\n",
    "plt.ylabel('Week Day')\n",
    "plt.yticks(np.arange(7), days)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**We can easily infer from the above graph that Fridays the criminal activities are at their highest. So, accordingly Police department can have more patrolling and preventive measures on Fridays to have a check on them.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.14. Plot crimes per month of the year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ntHPw0ksv4e7du0qf4bVr1xRF9+WXX8Zff/2luGRy7do1dOrUSfF9eppEIkHVw0IvXrxYbX5BQQFCQkLg6emJadOmKc2r77qezrums3BPSktLq9f/a80Zj9z12OHDh9GiRQvs378fCQkJSEhIQGJiIpycnOrdse7555/HuHHjMG/ePJw9exZlZWUoLS3F/v37ERMTU6+2DAwMEBAQgM8++wxZWVmorKzExYsXUVZWBplMBqlUCjMzM5SUlCAqKkrxvhYtWmDYsGH44osvUFJSgrS0NKXTswMHDsStW7ewd+9eVFRUIDExETdu3MCgQYOqxWBiYoJZs2YhIiIChw8fRklJCcrLy3HixAmsXr26XvmoauzYsYiJiVF0ECwqKsIvv/wCAEhJScHly5dRXl6O1q1bQyqVKh0pP23Pnj24ceMGSkpKsH79enh5eaFFixYAHu+4GBgYYNWqVbXuSDzN2NgY//d//1fjbX59+vRBq1atEBsbi/Lycpw9exZHjx5V/Af9LJ06dWrw+AaWlpawt7dHVFQUSktLce3aNezcuVPlvDp27IisrCyVbwEdNGgQbt26hYSEBJSXl6O8vBwpKSlIS0tTOeZntSGTydC+fXsYGRkhJSWl3pfJLCws8NxzzyElJUUxbc+ePVi7di22bdtW7YzYCy+8AFtbW2zatAmlpaU4dOgQ/vrrL3h5eQF4fIln586duHHjBgoLC7F582aMGTMGwOOzTefPn1f83mNjY5Gfnw8HB4caYysuLsakSZPg4OCg1FemSl3rAh737ygtLYUgCKioqEBpaSkqKysBAMOGDUNhYSHi4+NRWVmJAwcOICsrSymWpKQktY2hIHYs7nosPj4eb7zxBqysrGBubq749/bbbysKYH0sXrxYcerY2dkZQ4cOxaFDhzB48OB6x/bhhx+iZ8+eCAwMhIuLC9asWQO5XA5/f39YWVnBw8MDo0ePhp2dndL7lixZgqKiIvTv3x/z58/H6NGjFacfzczMEB0djW3btsHV1RWxsbGIjo5WXJJ4WkhICBYsWIAvv/wSbm5uGDRoEOLi4jB06NB656OKYcOGYfLkyZg7dy4cHBzg7e2N3377DcDj//AXL14MFxcXDB48GKampkq3+TzNz88PCxYsQP/+/VFWVlZtYB0/Pz9cv35dpVPyVV577TU899xz1aZLpVJER0fjt99+w+uvv46lS5di9erV6NGjh0rtzpw5EwsWLICTk1OtPc/rEhUVhfT0dHh4eGDmzJkICwtDv379VHrv66+/jpdeegnu7u5wdXV95vJt27bF1q1bkZiYCA8PD7i7u2PNmjX1Gh/iWW188skn2LBhA+zt7bFp0yaMHDlS5barjB07VmnHdt26dfj3338RGBioOE2+ZMkSxfyoqCikpqbC2dkZa9aswYYNGxS/iwEDBmDy5MmYMGECBg0aBGtra0XnRJlMhk8//RQuLi4YMGAATp48ia+++qrWI+1Dhw7hypUr+Pnnn2s8ZV/XugDg448/Rp8+fbBv3z5ER0ejT58+ijxNTU2xefNmfP3113ByckJMTAy+/PJLRR4pKSkwNjZ+ZqdfekwiVJ1/IWqCPv/8c+Tm5iIyMlLXoTQpCQkJ+PHHH/H999/rOhTSgLKyMvj7++Obb76ps+NlcxIWFobAwMA67wyh/2JxpyYlLS0N5eXlsLGxwZUrVzBlyhSsWLFCY0fb+qikpATvvPMOxo0bV+1+dSIigB3qqImRyWSYN28esrOz0bFjR4SEhGDIkCG6DqvJOHnyJMLCwuDm5qbUS5mI6Ek8ciciIhIZdqgjIiISGRZ3IiIikWFxJyIiEhlRdKjLz5dBLhdP14GOHdsiL6/2oUn1lRjzYk76Q4x5iTEnQJx5qSsnAwMJzMyePZyvKIq7XC6IqrgDEF0+VcSYF3PSH2LMS4w5AeLMS5s58bQ8ERGRyLC4ExERiQzvcyciaiYelpVAVlC/Z07ogrm5CXJyinQdhlqpKycDAwk6dmz7zOVEcc3dJbo37hXe0XUYRERNWsb8QsggrqJJNeNpeSIiIpHRWnGPjIyEp6cnbGxscP36dQBAfn4+pkyZAi8vL/j4+GDmzJl48OCBtkIiIiISJa0V9yFDhiAuLg7W1taKaRKJBJMnT8bBgwexd+9edOvWDWvWrNFWSERERKKkteLu5OQES0tLpWmmpqZwdXVVvLazs0NGRoa2QiIiIhKlJtOhTi6X4/vvv4enp6euQyEiEi1zcxNdh6ASfYmzPrSZU5Mp7suWLYOxsTHGjx+v61CIiERLH24x461wtdOrW+EiIyNx+/ZtREdHw8CAHfiJiIgaQ+fFPSoqCqmpqYiJiYFUKtV1OERERHpPa8V9+fLl+PXXX5Gbm4uJEyfC1NQU69atw5YtW/D8889j7NixAICuXbti06ZN2gqLiIhIdDj8LBFRM8HhZ3WnWV5zb6y8vGJRPR5QjF9sQJx5MSf9Ica8xJgTqQd7rxEREYkMizsREZHIsLgTERGJDIs7ERGRyLC4ExERiQyLOxERkciwuBMREYkMizsREZHIsLgTERGJDIs7ERGRyHBseSIiUgt1jV0vxmF1ObZ8A7hE98a9wju6DoOIqFnLmF8IGcRVlPWVVk7LR0ZGwtPTEzY2Nrh+/fozpxMREVHDaaW4DxkyBHFxcbC2tlZpOhERETWcVk7LOzk51Ws6ERERNZworrkTEVHTYG5u0qTaaUq0mROLOxERqY06eoSzt3ztVO0tz/vciYiIRIbFnYiISGS0UtyXL1+OAQMG4P79+5g4cSJGjx5d53QiIiJqOFGMUMdBbIiIdC9jfiGvudeCI9Q1wLnQVF2HQETU7D0sK9F1CPT/iaK45+UVQy7X+xMQCmLcawXEmRdz0h9izEuMOZF6sEMdERGRyLC4ExERiQyLOxERkciwuBMREYkMizsREZHIsLgTERGJDIs7ERGRyLC4ExERiQyLOxERkciIYmx5IiKiujwsK4GsoEJn6+fY8g3AB8cQEVFdMuYXQobmM1QvT8sTERGJjFaKe2RkJDw9PWFjY4Pr168rpt+8eRNvvvkmvLy88Oabb+LWrVvaCIeIiEjUtFLchwwZgri4OFhbWytN/+STTzBu3DgcPHgQ48aNw5IlS7QRDhERkahppbg7OTnB0tJSaVpeXh7+/PNPeHt7AwC8vb3x559/4sGDB9oIiYiISLR01qEuMzMTXbp0QYsWLQAALVq0QOfOnZGZmYkOHTroKiwiIhIpc3OTZrN+UfSWJyIiehZ13IrWUNq+FU5nveUtLS2RlZWFyspKAEBlZSWys7Ornb4nIiKi+tFZce/YsSNsbW2xb98+AMC+fftga2vLU/JERESNpJUR6pYvX45ff/0Vubm5MDMzg6mpKfbv34+0tDQsWLAAhYWFaNeuHSIjI/Hiiy/Wu30OYkNERHXJmF/YrE7Li2L4WRZ3IiKqC4s7ERGRyHBseT2Ul1cMuVw8+yjq+hI0NWLMiznpDzHmJcacAPHmpU0cW56IiEhkWNyJiIhEhsWdiIhIZFjciYiIRIbFnYiISGRY3ImIiESGxZ2IiEhkWNyJiIhEhsWdiIhIZDj8LBERiZauh52twuFnG4APjiEioppkzC+EDM1vKNsmcVr++PHjGDNmDHx8fDB+/HjcvXtX1yERERHpLZ0X94KCAnz44YeIiorC3r17ERQUhE8//VTXYREREektnRf327dvo1OnTnjhhRcAAAMHDsSpU6fw4MEDHUdGRESkn3Re3F944QXk5uYiJSUFALB3714AQGZmpi7DIiIi0ls671BnYmKCtWvX4rPPPkNpaSkGDBiAdu3aoUWLFroOjYiIRMDc3ETXIQDQbhw6L+4A0K9fP/Tr1w8AkJubi61bt+K5557TcVRERCQG6rgFrbG0fSuczk/LA0BOTg4AQC6XIyoqCmPHjoWxsbGOoyIiItJPTeLIfd26dbhw4QLKy8vRv39/hIeH6zokIiIivfXM4l5ZWYn4+Hj4+vpCKpVqJIgVK1ZopF0iIqLmSKXhZ52cnJCcnKyNeIiIiNSGw8/WYfDgwTh69Cg8PT0bHZgm5OUVQy4XzxD56voSNDVizIs56Q8x5iXGnADx5qVNKhX30tJSzJo1C/b29rCwsIBEIlHMW716tcaCIyIiovpTqbj37NkTPXv21HQsREREpAYqFfeZM2dqOg4iIiJSE5VvhSsrK8PNmzeRn5+PJ/vgubm5aSQwIiIiahiVintycjLmzJmDsrIyFBcXo23btpDJZLCwsMCRI0c0HSMRERHVg0oj1H322WeYPHkyzp07hzZt2uDcuXOYNm0axo0bp+n4iIiIqJ5UKu63bt3ChAkTlKZNnToV33zzjSZiIiIiokZQqbibmJiguLgYAGBubo4bN26gsLAQDx8+1GhwREREVH8qXXMfNmwYTpw4AR8fHwQEBGDChAkwNDSEl5eXpuMjIiKielKpuC9atEjx96RJk9C3b1/IZDJ4eHhoLDAiIiJqGJXGlq+SmZmJrKws2NnZaTAkIiIi/VPXOPZNcmz5jIwMzJ07F9euXYNEIsHFixdx4MABnDx5skk80c0lujfuFd7RdRhERNSMZcwvhAxNY0x8lTrULVmyBIMGDcKFCxdgaPh4f6B///44c+aMWoI4duwY/P394efnB19fX/z6669qaZeIiKg5UunI/cqVK4iJiYGBgYHioTEmJiYoKmr8HoogCJg/fz7i4uLQs2dPXLt2DW+99RaGDh0KAwOV9j2IiIjoCSpVz44dO+L27dtK027cuAFLS0v1BGFgoNhRKCoqQufOnVnYiYiIGkilI/eQkBCEhoZi6tSpqKiowL59+7BlyxZMmTKl0QFIJBKsW7cO06dPh7GxMWQyGWJiYhrdLhERkbaZm5s0aJ66qVTcAwMDYWpqih9//BGWlpZISEjA7NmzMXTo0EYHUFFRgS1btuDLL7+Eo6Mjzp8/jzlz5mD//v1o06ZNo9snIiLSltp6xDfJ3vKVlZUYOnSoWor5065evYrs7Gw4OjoCABwdHdG6dWukpaWhT58+al8fERGR2Kl0Ydvd3R3Lly9Hamqq2gOwsLDA/fv38c8//wAA0tLSkJeXh+eee07t6yIiImoOVDpyj42NxZ49exAaGgoTExP4+fnBz89PLR3qzM3N8emnn2L27NmKnvgrV66Eqalpo9smIiJqjuo1Qp1cLsepU6ewZ88eHDt2DL169YKfnx9GjRoFY2NjTcZZJw5iQ0REupYxv7DJXHOvV3EHgPT0dOzevRvx8fEwMDCAhYUFrl69ioULF8Lf37+h8RIREem1pjT8rErFvaCgAL/88gt2796Nf/75ByNGjICfnx8cHBwAACkpKZg0aRKSkpIaHXhD5OUVQy6v1z5Kk6auL0FTI8a8mJP+EGNeYswJEGdeTbK3/MCBA+Hq6org4GAMHToUUqlUaX6fPn0wZMiQhkVKREREaqVScT98+DA6depU5zKrVq1SS0BERETUOCrdCveswk5ERERNBwdwJyIiEhkWdyIiIpFhcSciIhIZlYq7IAjYsWMHJkyYAB8fHwBAUlISEhMTNRocERER1Z9KxX39+vXYuXMn3nzzTWRmZgJ4PCZ8bGysRoMjIiKi+lOpuMfHxyM6OhqjR49WjP/etWtX3L17V6PBERERUf2p/MjXqmerVxV3mUym0/Hkn6TKaD36xtzcRNchaIQY82JO+kOMeYkxJ0A8edU1JK0mqTxC3WeffYaFCxcCeHwNfv369Rg8eLBGg1MVHxxDRERNUcb8Qsig/aF0VTot/9FHHyEnJweOjo4oKiqCvb09MjIyEB4erun4iIiIqJ5UOnJv27YtNm3ahLy8PKSnp8PS0hLm5uZqCeDevXuYMWOG4nVRURGKi4tx7tw5tbRPRETU3KhU3J9kZmaGR48eKTrTdevWrVEBdO3aFbt371a8XrFiBSorKxvVJhERUXOmUnH/7bffsGjRIuTk5ChNl0gkuHr1qtqCKSsrw969e7F161a1tUlERNTcqFTcIyIiMH36dIwZMwatWrXSWDBHjx5Fly5d8Oqrr2psHURERNpU1fNfm3cAqFTcCwsLMXbsWMVtcJqya9cuBAQEaHQdRERE2pSTUwRzcxPk5DS+17yBgUSl279V6i0fEBCAXbt2NTqoumRlZSEpKUkxvC0RERE1TK1H7uPGjVMcqQuCgO3bt+Orr76q9mz3uLg4tQQSHx+PgQMHwszMTC3tERERNVe1FvegoKA6X6tbfHw8Fi1apNF1EBERNQe1FvcxY8Yo/r58+TL69u1bbZmUlBS1BXLw4EG1tUVERNScSQRBEJ61kIODAy5cuFBtuouLCwebISIiqkXV2PLa7lBXZ295uVwOQRCU/lW5c+cOWrRo0ehA1SEvrxhy+TP3UfSGur4ETY0Y82JO+kOMeYkxJ0C8eWlTncW9V69eik51vXr1UppnYGCA0NBQzUVGREREDVJncT9y5AgEQUBwcDC+++47xXSJRIIOHTpodEAbIiIiapg6i7u1tTUA4NixY1oJhoiIiBpPpUFsiIiISH+wuBMREYlMrcW9oKBAm3EQERGRmtRa3AcPHqz4+91339VGLERERKQGtRb31q1b4/r166isrERKSgoEQYBcLq/2j4iIiJqWWnvLz5gxA0FBQSgrKwNQ/T53QRAgkUhw9epVzUZIRERE9VLn8LMVFRXIzc3FyJEjsW/fPkVBf1LV7XJERERiUTVsrLpoe/hZlcaWv3XrFp5//vlGB6UpLtG9ca/wjq7DICIikciYX6jWIXCb1NjyVaytrbFhwwYkJCQgJycHnTt3hp+fH0JDQyGVShsdbGlpKVauXInff/8dRkZGsLOzw7JlyxrdLhERUXOkUnH//PPPkZKSgoiICFhZWSEjIwNffvkliouLsXDhwkYH8fnnn8PIyAgHDx6ERCJBbm5uo9skIiJqrlQq7gcOHMDu3bthZmYGAHjxxRfRq1cv+Pn5Nbq4y2QyJCQk4MSJE4rr+Z06dWpUm0RERM2ZSiPU1XZZXoXL9c909+5dmJqa4osvvsAbb7yB4OBgJCcnN7pdIiKi5kqlI/cRI0Zg2rRpmDFjBqysrJCeno7Nmzdj5MiRjQ6gsrISd+/eRa9evfDhhx/i8uXLCA0NxaFDh9C27bM7DRAREWmCublJk26vLioV9w8++ACbN29GREQEsrOz0aVLF4waNQrTp09vdACWlpYwNDSEt7c3AKBv374wMzPDzZs38dprrzW6fSIiooYQfW95qVSK2bNnY/bs2Y0O7GkdOnSAq6srTp8+DXd3d9y8eRN5eXno3r272tdFRETUHKhU3DVt6dKlWLhwISIjI2FoaIjVq1ejXbt2ug6LiIhILzWJ4t6tWzds375d12EQERGJgkoj1BERETUn+j78bJM4cm+svLxiyOXi2UdR15egqRFjXsxJf4gxLzHmBIg3L21SubifOnUKV69excOHD5Wma6KTHRERETWcSsU9IiICv/zyC1xdXdG6dWtNx0RERESNoFJx37dvH3bv3g1LS0tNx0NERESNpNLws2ZmZjAx0d7IOkRERNRwtR653717V/H3xIkTER4ejvfee6/aQ126deumueiIiIio3mot7sOGDYNEIlF6OMzx48eVlpFIJLh69arGgiMiIqL6q7W4X7t2TZtxEBERkZqodM19+fLlNU5fsWKFWoMhIiKixlOpuP/88881Tt+zZ49agyEiIqLGq/NWuJ07dwJ4/Mz1qr+r3L17F6amphoLjIiIiBqmzrHlg4ODAQDnz5+Ho6Pjf98kkaBTp06YMGEC7OzsNB4kERGRrqhjnHltjy2v0oNj1q5di/fff7/RQWmKS3Rv3Cu8o+swiIhIhDLmFza6MDfJB8dUFfa8vLxqY8ur4z53T09PSKVSGBkZAQDCw8Ph4eHR6HaJiIiaI5WK+8mTJ7Fw4ULk5OQoTVfnfe4bNmxAz5491dIWERFRc6ZScV+6dCmmT5+OMWPGoFWrVpqOiYiIiBpBpeJeWFiIsWPHQiKRaCyQ8PBwCIIAR0dHzJ07F+3atdPYuoiIiOrD3Lzxz1dRRxuqUqlDXWRkJHr06IHAwECNBJGZmQlLS0uUlZVhxYoVkMlkWLNmjcrvZ4c6IiLSFNF2qLt8+TK2b9+Or776qtqDY+Li4hoW4ROqHiUrlUoxbtw4TJs2rdFtEhERNVcqFfegoCAEBQVpJICHDx+isrISJiYmEAQBiYmJsLW11ci6iIiImgOVivuYMWM0FkBeXh7CwsJQWVkJuVyOHj164JNPPtHY+oiIiMROpeIOALt27cLu3buRlZWFLl26wM/PDwEBAY0OoFu3bkhISGh0O0RERPSYSsV98+bNSEhIQEhICKysrJCRkYHY2FhkZ2c3ievj50JTdR0CERGJ1MOyEl2HUG8q9Zb39PTE9u3bYW1trZiWnp6O8ePH49ixYxoNUBV5ecWQy5+Zht5QV6/KpkaMeTEn/SHGvMSYEyDOvLTdW16lR76WlJSgQ4cOStNMTU3x6NGjhkVHREREGqNScffw8EB4eDj++ecfPHr0CGlpaViwYAHc3d01HR8RERHVk0rFfcmSJWjTpg18fX1hb28Pf39/tG7dGh9//LGm4yMiIqJ6UqlDXdu2bbF69WqsWrUK+fn5MDMzg4GBSvsFREREpGV1FveMjIwap9+/f1/xt5WVlXojIiIiokaps7h7enoqHhZTU6d6dT7ylYiIiNSjzuL+yiuv4NGjRxgzZgx8fX3RuXNnbcVFREREDVRncU9ISMD169cRHx+Pt956Cz169ICfnx+GDx/O57oTERE1Uc/sFdezZ098+OGHOHr0KN59910cP34c7u7u+OOPP7QRHxEREdWTymPL37p1C0lJSbh06RJsbW3Rrl07TcZVL6qM1qNvzM1NdB2CRogxL+akP8SYlxhzAv6b18OyEsgKKnQcjf6ps7j/+++/2L9/P+Lj4yGTyeDn54fvvvuuyfWQd4nujXuFd3QdBhERqVnG/ELIIK6haLWhzuLu4eGBrl27ws/PD3379gUA3L59G7dv31Ys4+bmptkIiYiIqF7qLO7m5uYoLS3Fjh07sGPHjmrzJRIJjhw5orZgvvjiC2zcuBF79+5Fz5491dYuERFRc1JncT969Ki24sAff/yBS5cuKT15joiIiOqvSYwhW1ZWhoiICHz66ae6DoWIiEjvqdxbXpPWr18PX19fdO3aVdehEBFREyOWOwK0mYfOi/vFixeRmpqK8PBwXYdCRERNUE6O/veWNzc3UUseBgYSlW7/1vlp+aSkJKSlpWHIkCHw9PTE/fv3MWnSJJw6dUrXoREREeklnR+5T506FVOnTlW89vT0RHR0NHvLExERNZDOj9yJiIhIvXR+5P40bd5+R0REJEYSoaYHtRMRETUBYhlbXtsd6prckXtD5OUVQy4Xzz6Kur4ETY0Y82JO+kOMeYkxJ0C8eWkTr7kTERGJDIs7ERGRyLC4ExERiQyLOxERkciwuBMREYkMizsREZHIsLgTERGJDIs7ERGRyLC4ExERiQyHnyUioiZJLEPPAhx+tkFconvjXuEdXYdBRERqlDG/EDJwGNqGaBLFffr06bh37x4MDAxgbGyMjz/+GLa2troOi4iISC81ieIeGRkJExMTAMDhw4excOFCxMfH6zgqIiIi/dQkOtRVFXYAKC4uhkQi0WE0RERE+q1JHLkDwKJFi3D69GkIgoDY2Fhdh0NERKS3mlxv+YSEBOzfvx9fffWVyu9hhzoiIvHJmF+o6xD0VpM5cq/i7++PJUuWID8/H2ZmZroOh4iIdEgdt481Bdq+FU7n19xlMhkyMzMVr48ePYr27dvD1NRUd0ERERHpMZ0fuZeUlGD27NkoKSmBgYEB2rdvj+joaHaqIyIiaiCdF/dOnTphx44dug6DiIhINJpchzoiIiKAw8/WpFkNP5uXVwy5XDz7KOr6EjQ1YsyLOekPMeYlxpwA8ealTTrvUEdERETqxeJOREQkMizuREREIsPiTkREJDIs7kRERCLD4k5ERCQyLO5EREQiw+JOREQkMizuREREIsPiTkREJDKiGH5WlXF29Y25uYmuQ9AIMebFnPRHU85LTOOok+6Jori7RPfGvcI7ug6DiKjBMuYXQgaOp07qofPinp+fj/nz5+POnTuQSqXo3r07IiIi0KFDB12HRkREpJd0fs1dIpFg8uTJOHjwIPbu3Ytu3bphzZo1ug6LiIhIb+m8uJuamsLV1VXx2s7ODhkZGTqMiIiISL/p/LT8k+RyOb7//nt4enrqOhQiIq1rSIe/ptxJsDHEmJc2c2pSxX3ZsmUwNjbG+PHjdR0KEZHW5eTUr0OdublJvd+jD8SYl7pyMjCQqHSHWJMp7pGRkbh9+zaio6NhYKDzqwVERER6q0kU96ioKKSmpiImJgZSqVTX4RAREek1nRf3v//+G1u2bMHzzz+PsWPHAgC6du2KTZs26TgyIiIi/aTz4v7yyy/jr7/+0nUYREREoqHz4q4O50JTdR0CEVGjPCwr0XUIJCKiKO55ecWQywVdh6E2YuwpCogzL+akP8SaF1FN2C2diIhIZFjciYiIRIbFnYiISGRY3ImIiESGxZ2IiEhkWNyJiIhEhsWdiIhIZFjciYiIRIbFnYiISGQkgiCIZ2g3IiLSqodlJZAVVKi1TTGOJthsn+feGC7RvXGv8I6uwyAianYy5hdCBnEVYjHgaXkiIiKR0Xlxj4yMhKenJ2xsbHD9+nVdh0NERKT3dF7chwwZgri4OFhbW+s6FCIiIlHQ+TV3JycnXYdAREQkKjov7kREpN/MzU30ok1d02ZOLO5ERNQo6r5tjbfC1U7VW+F0fs2diIiI1IvFnYiISGR0XtyXL1+OAQMG4P79+5g4cSJGjx6t65CIiIj0ms6vuS9evBiLFy/WdRhERESiofPirg7nQlN1HQIRUbP0sKxE1yFQDURR3PPyiiGXi+f5N2LsKQqIMy/mpD/EmJcYcyL10Pk1dyIiIlIvFnciIiKREcVpeQMDia5DUDsx5gSIMy/mpD/EmJcYcwLEmZc6clK1DYkgCOK5WE1EREQ8LU9ERCQ2LO5EREQiw+JOREQkMizuREREIsPiTkREJDIs7kRERCLD4k5ERCQyLO5EREQiw+JOREQkMnpb3G/evIk333wTXl5eePPNN3Hr1i1dh6Tg6emJESNGwM/PD35+fjh58iQA4NKlS/D19YWXlxdCQkKQl5eneI8m5jVWZGQkPD09YWNjg+vXryum1/XZa3ueunKqbZsBTX+75efnY8qUKfDy8oKPjw9mzpyJBw8e6CR2beVlY2MDHx8fxfb666+/FO87evQoRowYgWHDhmHOnDkoKSnR6Lz6mj59Onx9feHv749x48bh6tWrAPT7d1VXXvr826ryxRdfKP2foRe/K0FPBQcHCwkJCYIgCEJCQoIQHBys44j+a/DgwcJff/2lNK2yslIYOnSokJSUJAiCIGzatElYsGCBxuapQ1JSkpCRkVEtn7o+e23PU1dONW0zQdCP7Zafny/85z//UbxetWqV8NFHH2k9dm3lJQiC0LNnT6G4uLjae4qLi4V+/foJN2/eFARBEBYuXChs3LhRY/MaorCwUPH3oUOHBH9/f0EQ9Pt3VVde+vzbEgRBSE1NFSZNmqTIQ19+V3pZ3HNzcwVHR0ehoqJCEARBqKioEBwdHYW8vDwdR/ZYTV/my5cvC6NHj1a8zsvLE+zs7DQ2T1P51PXZa3ueunKq6XUVfdxuBw4cEN555x2tx66tvASh9uKemJgoTJ06VfE6JSVFGDVqlMbmNVZ8fLwwZswY0fyuns5LEPT7t1VaWir8z//8j3D37l1FHvryu9LLp8JlZmaiS5cuaNGiBQCgRYsW6Ny5MzIzM9GhQwcdR/dYeHg4BEGAo6Mj5s6di8zMTFhZWSnmd+jQAXK5HP/++69G5pmammokr7o+e0EQtDpP3dv66W3Wrl07vdtucrkc33//PTw9PbUeu7byqhIcHIzKykoMGDAAYWFhkEql1WKwsrJCZmYmAGhkXkMtWrQIp0+fhiAIiI2NFc3v6um8qujrb2v9+vXw9fVF165dFdP05Xelt9fcm7K4uDjs2bMHu3btgiAIiIiI0HVI9Axi2WbLli2DsbExxo8fr+tQ1OrpvI4fP46ff/4ZcXFxuHHjBjZt2qTjCOtnxYoVOH78ON5//32sXr1a1+GoTU156etv6+LFi0hNTcW4ceN0HUqD6GVxt7S0RFZWFiorKwEAlZWVyM7OhqWlpY4je6wqDqlUinHjxuHChQuwtLRERkaGYpkHDx7AwMAApqamGpmnydxq++y1PU/deQHK26xqur5st8jISNy+fRvr1q2DgYGB1mPXVl7Af7dX27ZtERQUVOv2ysjIUCyriXmN5e/vj7Nnz8LCwkJUv6uqvPLz8/X2t5WUlIS0tDQMGTIEnp6euH//PiZNmoTbt2/rxe9KL4t7x44dYWtri3379gEA9u3bB1tb2yZxSv7hw4coKioCAAiCgMTERNja2qJ379549OgRkpOTAQA//PADRowYAQAamacpdX322p6nLrVtM0Az20YT2y0qKgqpqanYtGkTpFKpTmLXVl4FBQV49OgRAKCiogIHDx5UbC8PDw9cuXJF0fP7hx9+wMiRIzU2r75kMpnSKf2jR4+iffv2ev+7qi0vIyMjvf1tTZ06FadOncLRo0dx9OhRWFhYYOvWrZg8ebJ+/K6eeVW+ibpx44YQGBgoDB8+XAgMDBTS0tJ0HZIgCIJw584dwc/PT/D29hZGjRolhIWFCVlZWYIgCML58+cFb29vYdiwYcK7774r5OTkKN6niXmNtWzZMsHDw0OwtbUV+vXrp+hEVNdnr+156siprm0mCE1/u12/fl3o2bOnMHz4cMHX11fw9fUVpk+frpPYtZHXhQsXBG9vb8HHx0cYOXKksHDhQqXOdYcOHRKGDx8uDB06VAgLCxNkMplG59VHTk6OEBQUJHh7ewu+vr5CcHCwkJqaKgiCfv+uastL339bT3qyY6A+/K4kgiAIDdqtISIioiZJL0/LExERUe1Y3ImIiESGxZ2IiEhkWNyJiIhEhsWdiIhIZFjciURowYIFWLt2rU7WLQgCPvroIzg7OyMwMLDR7Y0ePRpnz55VQ2REzYdeji1PpG88PT1RUlKCI0eOwNjYGADw008/Yc+ePdi+fbuOo1Ov8+fP4/Tp0zhx4oQi18bYv3+/GqIial545E6kJXK5HN9++62uw6i3qiFKVZWeng5ra+tGF/aKiopGvZ+oOWNxJ9KSSZMm4euvv0ZhYWG1effu3YONjY1SQQsODsZPP/0EAPj5558xduxYrFy5Ek5OThgyZAguXLiAn3/+GQMHDoSbmxvi4+OV2szPz8fEiRNhb2+P8ePHIz09XTEvLS0NEydOhIuLC7y8vJCYmKiYt2DBAnzyySeYMmUK7OzsajwlnpWVhdDQULi4uGDYsGHYsWMHgMdnIxYvXoxLly7B3t4eGzZsqPGz2LFjB0aOHAl7e3uMGjUKf/zxB4DHZzhiYmLg4+MDOzs7VFRUwNPTE2fOnAEAbNy4EbNmzUJ4eDjs7e3h4+ODmzdvYsuWLXBzc8PAgQNx6tQpxXqKioqwcOFCuLu7w8PDA2vXrlXsrNy+fRvjx4+Ho6MjXF1dMWfOnNo3HpGeYXEn0pLevXvDxcUFW7dubdD7U1JSYGNjg7Nnz8Lb2xtz587FlStXcOjQIXz++eeIiIiATCZTLL93715Mnz4dZ8+exSuvvILw8HAAj8fSDwkJgbe3N86cOYO1a9di6dKluHHjhuK9+/btQ2hoKC5cuABHR8dqscydOxcWFhY4efIkNmzYgKioKPz+++8ICgrC0qVLYWdnh4sXL2LWrFnV3vvLL79g48aNiIyMxIULF7B582alh2Ds378fMTExSE5OhqFh9SuHx44dg5+fH5KSkmBra4tJkyZBLpfjt99+w4wZM7BkyRLFsgsWLIChoSF+/fVXJCQk4PTp04odpvXr16N///5ISkrCb7/9Jron6VHzxuJOpEWzZs3Cd999hwcPHtT7vV27dkVAQABatGiBUaNGITMzEzNmzIBUKoW7uzukUinu3LmjWH7QoEFwdnaGVCrF+++/j0uXLiEzMxPHjx+HtbU1AgICYGhoiF69esHLywsHDhxQvHfIkCFwdHSEgYEBjIyMlOLIzMzEhQsXEB4eDiMjI9ja2iIoKAi7d+9WKY+dO3di8uTJ6NOnDyQSCbp37w5ra2vF/ODgYFhaWqJVq1Y1vt/JyQkeHh4wNDTEiBEjkJ+fj6lTp6Jly5YYNWoU0tPTUVhYiNzcXJw4cQILFy6EsbExOnbsiHfffVdxDd/Q0BAZGRnIzs6GkZERnJycVN4WRE0dO9QRaVHPnj0xaNAgxMTEoEePHvV6b8eOHRV/VxW+Tp06KaYZGRkpHblbWFgo/m7Tpg3at2+P7OxspKenIyUlRamYVVZWwtfXV/G6rkd/Zmdno3379mjbtq1impWVFVJTU1XKIzMzE88991yt85/12NGnPwczMzO0aNFC8Rp4fHYiOzsbFRUVcHd3Vywvl8sV7X/wwQdYv349AgMD0b59e0ycOFEtvfuJmgIWdyItmzVrFsaMGYOQkBDFtKrOZ48ePVIUzZycnEat5/79+4q/ZTIZCgoK0LlzZ1haWsLZ2Rnbtm1rULudO3dGQUEBiouLFbFmZmaiS5cuKr3f0tJS6QzD0yQSSYPiepqFhQWkUin+85//1Hh639zcHMuXLwcAJCcnY+LEiXB2dkb37t3Vsn4iXeJpeSIt6969O0aNGqV0C1yHDh3QpUsX7N69G5WVldi5cyfu3r3bqPWcOHECycnJKCsrw/r169G3b19YWlpi0KBBuHXrFhISElBeXo7y8nKkpKQgLS1NpXYtLS1hb2+PqKgolJaW4tq1a9i5c6fSkX9dAgMD8fXXXyM1NRWCIOD27dtKnf3UpXPnzujfvz9WrVqF4uJiyOVy3LlzB+fOnQPw+Np/1Q5Q+/btIZFIYGDA/xJJHPhNJtKBGTNm4OHDh0rTli1bhq1bt8LV1RU3btyAvb19o9bh7e2NTZs2wdXVFX/88Qc+//xzAEDbtm2xdetWJCYmwsPDA+7u7lizZg3KyspUbjsqKgrp6enw8PDAzJkzERYWhn79+qn03pEjRyI0NBTz5s2Dg4MDZsyYgYKCggbl+CyrV69GeXk5Ro0aBWdnZ8yaNUtxRuTKlSsICgqCvb09pk2bhkWLFqFbt24aiYNI2/g8dyIiIpHhkTsREZHIsLgTERGJDIs7ERGRyLC4ExERiQyLOxERkciwuBMREYkMizsREZHIsLgTERGJDIs7ERGRyPw/LyeKHWmG2/sAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 797 ms, sys: 234 ms, total: 1.03 s\n",
      "Wall time: 727 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "crimes_df.groupby([crimes_df.index.month]).size().plot(kind='barh', figsize=(8,5), color='#19890D')\n",
    "plt.title('All Chicago Crimes by Month of the Year (2005-2016)')\n",
    "plt.xlabel('Number of crimes')\n",
    "plt.ylabel('Month of the year')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**We can see clearly in the graph that the peak of the crimes is during summer(July) across all these years.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.15. Sum of all crimes through the years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11,4))\n",
    "crimes_df.resample('D').size().rolling(365).sum().plot()\n",
    "plt.title('Sum of all crimes from 2005-2016')\n",
    "plt.ylabel('Number of crimes')\n",
    "plt.xlabel('Year')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Number of crimes reported has declined over the period of 10 year from 2006 to 2016.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.16. Mapping Theft Crime Locations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>Primary Type</th>\n",
       "      <th>Description</th>\n",
       "      <th>Location Description</th>\n",
       "      <th>Arrest</th>\n",
       "      <th>Community Area</th>\n",
       "      <th>Year</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT:$300 &amp;UNDER</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.874125711</td>\n",
       "      <td>-87.743684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT: OVER $300</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.782646487</td>\n",
       "      <td>-87.636096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT: OVER $300</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.743592217</td>\n",
       "      <td>-87.628425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT: OVER $300</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.771199121</td>\n",
       "      <td>-87.637302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>THEFT</td>\n",
       "      <td>FINANCIAL ID THEFT: OVER $300</td>\n",
       "      <td>RESIDENCE</td>\n",
       "      <td>False</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>41.843074007</td>\n",
       "      <td>-87.631807</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Primary Type                     Description Location Description  \\\n",
       "Date                                                                           \n",
       "2005-01-01        THEFT  FINANCIAL ID THEFT:$300 &UNDER            RESIDENCE   \n",
       "2005-01-01        THEFT   FINANCIAL ID THEFT: OVER $300            RESIDENCE   \n",
       "2005-01-01        THEFT   FINANCIAL ID THEFT: OVER $300            RESIDENCE   \n",
       "2005-01-01        THEFT   FINANCIAL ID THEFT: OVER $300            RESIDENCE   \n",
       "2005-01-01        THEFT   FINANCIAL ID THEFT: OVER $300            RESIDENCE   \n",
       "\n",
       "            Arrest  Community Area    Year      Latitude  Longitude  \n",
       "Date                                                                 \n",
       "2005-01-01   False            25.0  2005.0  41.874125711 -87.743684  \n",
       "2005-01-01   False            68.0  2005.0  41.782646487 -87.636096  \n",
       "2005-01-01   False            44.0  2005.0  41.743592217 -87.628425  \n",
       "2005-01-01   False            68.0  2005.0  41.771199121 -87.637302  \n",
       "2005-01-01   False            34.0  2005.0  41.843074007 -87.631807  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Theft_Crimes = crimes_df.drop(columns=['Block', 'Domestic', 'Beat', 'District', 'Ward', 'FBI Code'], axis = 1)\n",
    "Theft_Crimes = Theft_Crimes[Theft_Crimes[\"Primary Type\"] == \"THEFT\"]\n",
    "Theft_Crimes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Community Area</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>41.970514812</td>\n",
       "      <td>-87.836651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>42.004480111</td>\n",
       "      <td>-87.664305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>41.996928759</td>\n",
       "      <td>-87.687417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>41.967860872</td>\n",
       "      <td>-87.674146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>41.979480037</td>\n",
       "      <td>-87.697539</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Latitude  Longitude\n",
       "Community Area                         \n",
       "0.0             41.970514812 -87.836651\n",
       "1.0             42.004480111 -87.664305\n",
       "2.0             41.996928759 -87.687417\n",
       "3.0             41.967860872 -87.674146\n",
       "4.0             41.979480037 -87.697539"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locations = Theft_Crimes.groupby('Community Area').first()\n",
    "new_locations = locations.loc[:, ['Latitude', 'Longitude']]\n",
    "new_locations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fc10e076b80>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MapOfChicago = folium.Map(location=[41.881832, -87.623177], zoom_start=11)\n",
    "i=0\n",
    "for index, row in new_locations.iterrows():\n",
    "    folium.Marker(location = [row['Latitude'], row['Longitude']]).add_to(MapOfChicago)\n",
    "\n",
    "MapOfChicago"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Theft is prevalent across entire Chicago.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.17. Summary: Overall number of cases per Year x Months using Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>Number of cases</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Year-Month</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-31</th>\n",
       "      <td>33249</td>\n",
       "      <td>1</td>\n",
       "      <td>2005</td>\n",
       "      <td>2005-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-02-28</th>\n",
       "      <td>31559</td>\n",
       "      <td>2</td>\n",
       "      <td>2005</td>\n",
       "      <td>2005-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-03-31</th>\n",
       "      <td>36449</td>\n",
       "      <td>3</td>\n",
       "      <td>2005</td>\n",
       "      <td>2005-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-04-30</th>\n",
       "      <td>38453</td>\n",
       "      <td>4</td>\n",
       "      <td>2005</td>\n",
       "      <td>2005-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-05-31</th>\n",
       "      <td>40137</td>\n",
       "      <td>5</td>\n",
       "      <td>2005</td>\n",
       "      <td>2005-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Number of cases Month  Year Year-Month\n",
       "Date                                              \n",
       "2005-01-31            33249     1  2005    2005-01\n",
       "2005-02-28            31559     2  2005    2005-02\n",
       "2005-03-31            36449     3  2005    2005-03\n",
       "2005-04-30            38453     4  2005    2005-04\n",
       "2005-05-31            40137     5  2005    2005-05"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crimes_df2 = pd.DataFrame(crimes_df.resample(\"M\").size(), columns=[\"Number of cases\"])\n",
    "crimes_df2[\"Month\"] = crimes_df2.index.month.astype(str)\n",
    "crimes_df2[\"Year\"] = crimes_df2.index.year.astype(str)\n",
    "crimes_df2[\"Year-Month\"] = crimes_df2[\"Year\"].str.cat(crimes_df2[\"Month\"].str.zfill(2), sep=\"-\")\n",
    "crimes_df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "crimes_df3 = crimes_df2[[\"Month\", \"Year\", \"Number of cases\"]]\n",
    "crimes_df3 = crimes_df3.pivot(\"Month\", \"Year\", \"Number of cases\").fillna(0).astype(int)\n",
    "crimes_df3.index = crimes_df3.index.astype(int)\n",
    "crimes_df3 = crimes_df3.sort_index()\n",
    "crimes_df3.index = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']\n",
    "plt.figure(figsize=(20, 10))\n",
    "_ = sns.heatmap(\n",
    "    crimes_df3,\n",
    "    annot=True,\n",
    "    fmt=\"d\",\n",
    "    linewidths=0.5,\n",
    "    cmap=\"Blues\",\n",
    ").set_title('Number of crimes in Chicago per Year x Months')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The years between 2005 and 2008 were a tough time**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 8. Conclusion:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Theft is the most common crime in Chicago. Most of the theft reported cases are with '$500 and under' description.\n",
    "* Top 10 types of crimes are Theft, Battery, Criminal damage, Narcotics, Burglary, Other Offense, Assault, Motor Vehicle Theft , Robbery and Deceptive Practice\n",
    "* The most common crime location is Chicago streets.\n",
    "* We see the highest crimes reported in 2005.\n",
    "* Austin is the highest crime community area in Chicago as per our analysis.\n",
    "* Very few crime reports (~27.80%) end up in an arrest. But we found that in Narcotics related crimes, the arrest rate is very high almost 100%.\n",
    "* Even if Theft is the most common crime in Chicago but Arrest rate is quite low comparatively.\n",
    "* We can easily infer from the above graph that Fridays the criminal activities are at their highest. So, accordingly Police department can have more patrolling and preventive measures on Fridays to have   a check on them.\n",
    "* We can see clearly in the graph that the peak of the crimes is during summer(July) across all these years.\n",
    "* Number of crimes reported has declined over the period of 10 year from 2006 to 2016.\n",
    "* The years between 2005 and 2008 were a tough time in Chicago considering the criminal activities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "created_in_deepnote_cell": true,
    "deepnote_cell_type": "markdown",
    "tags": []
   },
   "source": [
    "<a style='text-decoration:none;line-height:16px;display:flex;color:#5B5B62;padding:10px;justify-content:end;' href='https://deepnote.com?utm_source=created-in-deepnote-cell&projectId=6ab987db-b709-4ef7-9bee-384a40c4b1c2' target=\"_blank\">\n",
    "<img alt='Created in deepnote.com' style='display:inline;max-height:16px;margin:0px;margin-right:7.5px;' src='data:image/svg+xml;base64,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' > </img>\n",
    "Created in <span style='font-weight:600;margin-left:4px;'>Deepnote</span></a>"
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