THE DATA INCUBATOR 2nd NOV 2019 test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy.stats import zscore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Arrest_Data_from_2010_to_Present.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Report ID</th>\n",
       "      <th>Arrest Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Area ID</th>\n",
       "      <th>Area Name</th>\n",
       "      <th>Reporting District</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex Code</th>\n",
       "      <th>Descent Code</th>\n",
       "      <th>Charge Group Code</th>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th>Arrest Type Code</th>\n",
       "      <th>Charge</th>\n",
       "      <th>Charge Description</th>\n",
       "      <th>Address</th>\n",
       "      <th>Cross Street</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4248313</td>\n",
       "      <td>02/24/2015</td>\n",
       "      <td>1310.0</td>\n",
       "      <td>20</td>\n",
       "      <td>Olympic</td>\n",
       "      <td>2022</td>\n",
       "      <td>37</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>5TH</td>\n",
       "      <td>WILTON</td>\n",
       "      <td>(34.0653, -118.314)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>191811472</td>\n",
       "      <td>05/03/2019</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>18</td>\n",
       "      <td>Southeast</td>\n",
       "      <td>1802</td>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "      <td>B</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>653.22 PC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91ST</td>\n",
       "      <td>FIGUEROA</td>\n",
       "      <td>(33.9543, -118.2827)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4254777</td>\n",
       "      <td>02/26/2015</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>19</td>\n",
       "      <td>Mission</td>\n",
       "      <td>1985</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Larceny</td>\n",
       "      <td>M</td>\n",
       "      <td>459.5PC</td>\n",
       "      <td>SHOPLIFTING</td>\n",
       "      <td>8300    VAN NUYS                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.2216, -118.4488)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5614161</td>\n",
       "      <td>04/29/2019</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>8</td>\n",
       "      <td>West LA</td>\n",
       "      <td>842</td>\n",
       "      <td>41</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>F</td>\n",
       "      <td>211PC</td>\n",
       "      <td>ROBBERY</td>\n",
       "      <td>11600    WILSHIRE                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.0508, -118.4592)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5615197</td>\n",
       "      <td>04/30/2019</td>\n",
       "      <td>615.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Hollywood</td>\n",
       "      <td>663</td>\n",
       "      <td>27</td>\n",
       "      <td>M</td>\n",
       "      <td>O</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>LA BREA</td>\n",
       "      <td>LEXINGTON</td>\n",
       "      <td>(34.0907, -118.3384)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Report ID Arrest Date    Time  Area ID  Area Name  Reporting District  Age  \\\n",
       "0    4248313  02/24/2015  1310.0       20    Olympic                2022   37   \n",
       "1  191811472  05/03/2019  1700.0       18  Southeast                1802   23   \n",
       "2    4254777  02/26/2015  2010.0       19    Mission                1985   22   \n",
       "3    5614161  04/29/2019  1040.0        8    West LA                 842   41   \n",
       "4    5615197  04/30/2019   615.0        6  Hollywood                 663   27   \n",
       "\n",
       "  Sex Code Descent Code  Charge Group Code Charge Group Description  \\\n",
       "0        M            H                5.0                 Burglary   \n",
       "1        F            B                NaN                      NaN   \n",
       "2        M            H                6.0                  Larceny   \n",
       "3        M            H                3.0                  Robbery   \n",
       "4        M            O                5.0                 Burglary   \n",
       "\n",
       "  Arrest Type Code     Charge Charge Description  \\\n",
       "0                F      459PC           BURGLARY   \n",
       "1                M  653.22 PC                NaN   \n",
       "2                M    459.5PC        SHOPLIFTING   \n",
       "3                F      211PC            ROBBERY   \n",
       "4                F      459PC           BURGLARY   \n",
       "\n",
       "                                    Address Cross Street              Location  \n",
       "0                                       5TH       WILTON   (34.0653, -118.314)  \n",
       "1                                      91ST     FIGUEROA  (33.9543, -118.2827)  \n",
       "2   8300    VAN NUYS                     BL          NaN  (34.2216, -118.4488)  \n",
       "3  11600    WILSHIRE                     BL          NaN  (34.0508, -118.4592)  \n",
       "4                                   LA BREA    LEXINGTON  (34.0907, -118.3384)  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Arrest Date'] = pd.to_datetime(df['Arrest Date'],dayfirst=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Report ID</th>\n",
       "      <th>Arrest Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Area ID</th>\n",
       "      <th>Area Name</th>\n",
       "      <th>Reporting District</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex Code</th>\n",
       "      <th>Descent Code</th>\n",
       "      <th>Charge Group Code</th>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th>Arrest Type Code</th>\n",
       "      <th>Charge</th>\n",
       "      <th>Charge Description</th>\n",
       "      <th>Address</th>\n",
       "      <th>Cross Street</th>\n",
       "      <th>Location</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4248313</td>\n",
       "      <td>2015-02-24</td>\n",
       "      <td>1310.0</td>\n",
       "      <td>20</td>\n",
       "      <td>Olympic</td>\n",
       "      <td>2022</td>\n",
       "      <td>37</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>5TH</td>\n",
       "      <td>WILTON</td>\n",
       "      <td>(34.0653, -118.314)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>191811472</td>\n",
       "      <td>2019-05-03</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>18</td>\n",
       "      <td>Southeast</td>\n",
       "      <td>1802</td>\n",
       "      <td>23</td>\n",
       "      <td>F</td>\n",
       "      <td>B</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>653.22 PC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>91ST</td>\n",
       "      <td>FIGUEROA</td>\n",
       "      <td>(33.9543, -118.2827)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4254777</td>\n",
       "      <td>2015-02-26</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>19</td>\n",
       "      <td>Mission</td>\n",
       "      <td>1985</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Larceny</td>\n",
       "      <td>M</td>\n",
       "      <td>459.5PC</td>\n",
       "      <td>SHOPLIFTING</td>\n",
       "      <td>8300    VAN NUYS                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.2216, -118.4488)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5614161</td>\n",
       "      <td>2019-04-29</td>\n",
       "      <td>1040.0</td>\n",
       "      <td>8</td>\n",
       "      <td>West LA</td>\n",
       "      <td>842</td>\n",
       "      <td>41</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>F</td>\n",
       "      <td>211PC</td>\n",
       "      <td>ROBBERY</td>\n",
       "      <td>11600    WILSHIRE                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.0508, -118.4592)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5615197</td>\n",
       "      <td>2019-04-30</td>\n",
       "      <td>615.0</td>\n",
       "      <td>6</td>\n",
       "      <td>Hollywood</td>\n",
       "      <td>663</td>\n",
       "      <td>27</td>\n",
       "      <td>M</td>\n",
       "      <td>O</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>LA BREA</td>\n",
       "      <td>LEXINGTON</td>\n",
       "      <td>(34.0907, -118.3384)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Report ID Arrest Date    Time  Area ID  Area Name  Reporting District  Age  \\\n",
       "0    4248313  2015-02-24  1310.0       20    Olympic                2022   37   \n",
       "1  191811472  2019-05-03  1700.0       18  Southeast                1802   23   \n",
       "2    4254777  2015-02-26  2010.0       19    Mission                1985   22   \n",
       "3    5614161  2019-04-29  1040.0        8    West LA                 842   41   \n",
       "4    5615197  2019-04-30   615.0        6  Hollywood                 663   27   \n",
       "\n",
       "  Sex Code Descent Code  Charge Group Code Charge Group Description  \\\n",
       "0        M            H                5.0                 Burglary   \n",
       "1        F            B                NaN                      NaN   \n",
       "2        M            H                6.0                  Larceny   \n",
       "3        M            H                3.0                  Robbery   \n",
       "4        M            O                5.0                 Burglary   \n",
       "\n",
       "  Arrest Type Code     Charge Charge Description  \\\n",
       "0                F      459PC           BURGLARY   \n",
       "1                M  653.22 PC                NaN   \n",
       "2                M    459.5PC        SHOPLIFTING   \n",
       "3                F      211PC            ROBBERY   \n",
       "4                F      459PC           BURGLARY   \n",
       "\n",
       "                                    Address Cross Street              Location  \n",
       "0                                       5TH       WILTON   (34.0653, -118.314)  \n",
       "1                                      91ST     FIGUEROA  (33.9543, -118.2827)  \n",
       "2   8300    VAN NUYS                     BL          NaN  (34.2216, -118.4488)  \n",
       "3  11600    WILSHIRE                     BL          NaN  (34.0508, -118.4592)  \n",
       "4                                   LA BREA    LEXINGTON  (34.0907, -118.3384)  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['Arrest Date'] < (\"2019-01-01\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['year'] = df['Arrest Date'].apply(lambda date: date.year)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many bookings of arrestees were made in the area with the most arrests in 2018?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10951"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in2018 = df[df['year']==2018] \n",
    "in2018['Area ID'].value_counts().sort_values(ascending=False).max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What is the 95% quantile of the age of the arrestee in 2018? Only consider the following charge groups for your analysis:\n",
    "\n",
    "Vehicle Theft\n",
    "Robbery\n",
    "Burglary\n",
    "Receive Stolen Property"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "charges = df[['Charge Group Code', 'Charge Group Description', 'Charge Description']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "charge_names = ['Vehicle Theft','Robbery','Burglary','Receive Stolen Property']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Charge Group Code</th>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th>Charge Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>BURGLARY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>BURGLARY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>ROBBERY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>ROBBERY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>11.0</td>\n",
       "      <td>Receive Stolen Property</td>\n",
       "      <td>RECEIVING KNOWN STOLEN PROPERTY &gt;$950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>11.0</td>\n",
       "      <td>Receive Stolen Property</td>\n",
       "      <td>RECEIVING KNOWN STOLEN PROPERTY &gt;$950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Vehicle Theft</td>\n",
       "      <td>TAKE VEHICLE W/O OWNER'S CONSENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Vehicle Theft</td>\n",
       "      <td>TAKE VEHICLE W/O OWNER'S CONSENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Vehicle Theft</td>\n",
       "      <td>TAKE VEHICLE W/O OWNER'S CONSENT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>7.0</td>\n",
       "      <td>Vehicle Theft</td>\n",
       "      <td>TAKE VEHICLE W/O OWNER'S CONSENT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Charge Group Code Charge Group Description  \\\n",
       "0                  5.0                 Burglary   \n",
       "6                  5.0                 Burglary   \n",
       "7                  3.0                  Robbery   \n",
       "12                 3.0                  Robbery   \n",
       "162               11.0  Receive Stolen Property   \n",
       "164               11.0  Receive Stolen Property   \n",
       "178                7.0            Vehicle Theft   \n",
       "179                7.0            Vehicle Theft   \n",
       "180                7.0            Vehicle Theft   \n",
       "182                7.0            Vehicle Theft   \n",
       "\n",
       "                        Charge Description  \n",
       "0                                 BURGLARY  \n",
       "6                                 BURGLARY  \n",
       "7                                  ROBBERY  \n",
       "12                                 ROBBERY  \n",
       "162  RECEIVING KNOWN STOLEN PROPERTY >$950  \n",
       "164  RECEIVING KNOWN STOLEN PROPERTY >$950  \n",
       "178       TAKE VEHICLE W/O OWNER'S CONSENT  \n",
       "179       TAKE VEHICLE W/O OWNER'S CONSENT  \n",
       "180       TAKE VEHICLE W/O OWNER'S CONSENT  \n",
       "182       TAKE VEHICLE W/O OWNER'S CONSENT  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "charges[charges['Charge Group Description'].isin(charge_names)].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# quantileValues = dataFrame.quantile(.95);\n",
    "# print(\"95th percentile:\");\n",
    "# print(quantileValues);\n",
    "\n",
    "quantile95_age = in2018[in2018['Charge Group Description'].isin(charge_names)]['Age']\n",
    "quantile95_age.quantile(0.95)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are differences between the average age of an arrestee for the various charge groups. Are these differences statistically significant? For this question, calculate the Z-score of the average age for each charge group. Report the largest absolute value among the calculated Z-scores.\n",
    "\n",
    "Only consider data for 2018\n",
    "\n",
    "Do not consider \"Pre-Delinquency\" and \"Non-Criminal Detention\" as these charge groups are reserved for minors\n",
    "\n",
    "Exclude any arrests where the charge group description is not known"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Miscellaneous Other Violations    17023\n",
       "Narcotic Drug Laws                10697\n",
       "Aggravated Assault                 9231\n",
       "Driving Under Influence            8918\n",
       "Other Assaults                     7907\n",
       "Larceny                            5129\n",
       "Drunkeness                         3769\n",
       "Moving Traffic Violations          3565\n",
       "Liquor Laws                        3481\n",
       "Weapon (carry/poss)                3396\n",
       "Vehicle Theft                      3257\n",
       "Prostitution/Allied                2970\n",
       "Robbery                            2787\n",
       "Disorderly Conduct                 2536\n",
       "Burglary                           1958\n",
       "Sex (except rape/prst)             1179\n",
       "Fraud/Embezzlement                 1061\n",
       "Against Family/Child                923\n",
       "Receive Stolen Property             455\n",
       "Forgery/Counterfeit                 415\n",
       "Rape                                315\n",
       "Homicide                            274\n",
       "Non-Criminal Detention              198\n",
       "Gambling                            175\n",
       "Disturbing the Peace                 98\n",
       "Pre-Delinquency                      72\n",
       "Federal Offenses                     25\n",
       "Name: Charge Group Description, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "in2018['Charge Group Description'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_serious_2018 = in2018[in2018['Charge Group Description']!= 'Non-Criminal Detention']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_serious_2018 = df_serious_2018[df_serious_2018['Charge Group Description']!= 'Pre-Delinquency']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_serious_2018 = df_serious_2018[df_serious_2018['Charge Group Description']!= \"NaN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Miscellaneous Other Violations    17023\n",
       "Narcotic Drug Laws                10697\n",
       "Aggravated Assault                 9231\n",
       "Driving Under Influence            8918\n",
       "Other Assaults                     7907\n",
       "Larceny                            5129\n",
       "Drunkeness                         3769\n",
       "Moving Traffic Violations          3565\n",
       "Liquor Laws                        3481\n",
       "Weapon (carry/poss)                3396\n",
       "Vehicle Theft                      3257\n",
       "Prostitution/Allied                2970\n",
       "Robbery                            2787\n",
       "Disorderly Conduct                 2536\n",
       "Burglary                           1958\n",
       "Sex (except rape/prst)             1179\n",
       "Fraud/Embezzlement                 1061\n",
       "Against Family/Child                923\n",
       "Receive Stolen Property             455\n",
       "Forgery/Counterfeit                 415\n",
       "Rape                                315\n",
       "Homicide                            274\n",
       "Gambling                            175\n",
       "Disturbing the Peace                 98\n",
       "Federal Offenses                     25\n",
       "Name: Charge Group Description, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_serious_2018['Charge Group Description'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "avg_age_df = pd.DataFrame(df_serious_2018.groupby(['Charge Group Description'])['Age'].mean())\n",
    "#avg_age_df['z_score'] = avg_age_df.apply(zscore)\n",
    "#avg_age_df['z_score_abs'] = avg_age_df['z_score'].apply(lambda score: abs(score))\n",
    "#print(\"the largest abs value among z scores: {}\" .format(avg_age_df['z_score_abs'].max()))"
   ]
  },
  {
   "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>Age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Against Family/Child</th>\n",
       "      <td>35.539545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aggravated Assault</th>\n",
       "      <td>34.434622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burglary</th>\n",
       "      <td>30.391216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Disorderly Conduct</th>\n",
       "      <td>41.229890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Disturbing the Peace</th>\n",
       "      <td>39.010204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Driving Under Influence</th>\n",
       "      <td>34.953353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drunkeness</th>\n",
       "      <td>43.905015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Federal Offenses</th>\n",
       "      <td>34.080000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forgery/Counterfeit</th>\n",
       "      <td>34.265060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fraud/Embezzlement</th>\n",
       "      <td>35.615457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gambling</th>\n",
       "      <td>41.308571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Homicide</th>\n",
       "      <td>30.470803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Larceny</th>\n",
       "      <td>33.776565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Liquor Laws</th>\n",
       "      <td>42.483482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miscellaneous Other Violations</th>\n",
       "      <td>35.537684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moving Traffic Violations</th>\n",
       "      <td>33.874614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Narcotic Drug Laws</th>\n",
       "      <td>36.303356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other Assaults</th>\n",
       "      <td>34.091311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prostitution/Allied</th>\n",
       "      <td>30.006061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rape</th>\n",
       "      <td>35.168254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Receive Stolen Property</th>\n",
       "      <td>31.791209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robbery</th>\n",
       "      <td>27.182992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sex (except rape/prst)</th>\n",
       "      <td>37.029686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vehicle Theft</th>\n",
       "      <td>29.821615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Weapon (carry/poss)</th>\n",
       "      <td>30.174323</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Age\n",
       "Charge Group Description                 \n",
       "Against Family/Child            35.539545\n",
       "Aggravated Assault              34.434622\n",
       "Burglary                        30.391216\n",
       "Disorderly Conduct              41.229890\n",
       "Disturbing the Peace            39.010204\n",
       "Driving Under Influence         34.953353\n",
       "Drunkeness                      43.905015\n",
       "Federal Offenses                34.080000\n",
       "Forgery/Counterfeit             34.265060\n",
       "Fraud/Embezzlement              35.615457\n",
       "Gambling                        41.308571\n",
       "Homicide                        30.470803\n",
       "Larceny                         33.776565\n",
       "Liquor Laws                     42.483482\n",
       "Miscellaneous Other Violations  35.537684\n",
       "Moving Traffic Violations       33.874614\n",
       "Narcotic Drug Laws              36.303356\n",
       "Other Assaults                  34.091311\n",
       "Prostitution/Allied             30.006061\n",
       "Rape                            35.168254\n",
       "Receive Stolen Property         31.791209\n",
       "Robbery                         27.182992\n",
       "Sex (except rape/prst)          37.029686\n",
       "Vehicle Theft                   29.821615\n",
       "Weapon (carry/poss)             30.174323"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_age_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_age_df['z_score'] = avg_age_df.apply(zscore)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_age_df['z_score_abs'] = avg_age_df['z_score'].apply(lambda score: abs(score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the largest abs value among z scores: 2.1717481576567237\n"
     ]
    }
   ],
   "source": [
    "print(\"the largest abs value among z scores: {}\" .format(avg_age_df['z_score_abs'].max()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Felony arrest incidents have been dropping over the years. Using a trend line (linear estimation) for the data from 2010 and 2018 (inclusive), what is the projected number of felony arrests in 2019? Round to the nearest integer. Note, the data set includes arrests for misdemeanor, felonies, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>Report ID</th>\n",
       "      <th>Arrest Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Area ID</th>\n",
       "      <th>Area Name</th>\n",
       "      <th>Reporting District</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex Code</th>\n",
       "      <th>Descent Code</th>\n",
       "      <th>Charge Group Code</th>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th>Arrest Type Code</th>\n",
       "      <th>Charge</th>\n",
       "      <th>Charge Description</th>\n",
       "      <th>Address</th>\n",
       "      <th>Cross Street</th>\n",
       "      <th>Location</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4248313</td>\n",
       "      <td>2015-02-24</td>\n",
       "      <td>1310.0</td>\n",
       "      <td>20</td>\n",
       "      <td>Olympic</td>\n",
       "      <td>2022</td>\n",
       "      <td>37</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>5TH</td>\n",
       "      <td>WILTON</td>\n",
       "      <td>(34.0653, -118.314)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4254777</td>\n",
       "      <td>2015-02-26</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>19</td>\n",
       "      <td>Mission</td>\n",
       "      <td>1985</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Larceny</td>\n",
       "      <td>M</td>\n",
       "      <td>459.5PC</td>\n",
       "      <td>SHOPLIFTING</td>\n",
       "      <td>8300    VAN NUYS                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.2216, -118.4488)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4256466</td>\n",
       "      <td>2015-02-28</td>\n",
       "      <td>1430.0</td>\n",
       "      <td>18</td>\n",
       "      <td>Southeast</td>\n",
       "      <td>1824</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>103RD</td>\n",
       "      <td>HICKORY</td>\n",
       "      <td>(33.947, -118.2594)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4256564</td>\n",
       "      <td>2015-02-28</td>\n",
       "      <td>1715.0</td>\n",
       "      <td>10</td>\n",
       "      <td>West Valley</td>\n",
       "      <td>1039</td>\n",
       "      <td>16</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>F</td>\n",
       "      <td>211PC</td>\n",
       "      <td>ROBBERY</td>\n",
       "      <td>VANOWEN</td>\n",
       "      <td>WOODLEY</td>\n",
       "      <td>(34.1939, -118.4836)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4256815</td>\n",
       "      <td>2015-03-01</td>\n",
       "      <td>110.0</td>\n",
       "      <td>17</td>\n",
       "      <td>Devonshire</td>\n",
       "      <td>1794</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Other Assaults</td>\n",
       "      <td>M</td>\n",
       "      <td>243(A)PC</td>\n",
       "      <td>BATTERY ON PERSON</td>\n",
       "      <td>VANALDEN</td>\n",
       "      <td>BRYANT</td>\n",
       "      <td>(34.2251, -118.5372)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Report ID Arrest Date    Time  Area ID    Area Name  Reporting District  \\\n",
       "0     4248313  2015-02-24  1310.0       20      Olympic                2022   \n",
       "2     4254777  2015-02-26  2010.0       19      Mission                1985   \n",
       "6     4256466  2015-02-28  1430.0       18    Southeast                1824   \n",
       "7     4256564  2015-02-28  1715.0       10  West Valley                1039   \n",
       "10    4256815  2015-03-01   110.0       17   Devonshire                1794   \n",
       "\n",
       "    Age Sex Code Descent Code  Charge Group Code Charge Group Description  \\\n",
       "0    37        M            H                5.0                 Burglary   \n",
       "2    22        M            H                6.0                  Larceny   \n",
       "6    22        M            B                5.0                 Burglary   \n",
       "7    16        M            H                3.0                  Robbery   \n",
       "10   22        M            H                8.0           Other Assaults   \n",
       "\n",
       "   Arrest Type Code    Charge Charge Description  \\\n",
       "0                 F     459PC           BURGLARY   \n",
       "2                 M   459.5PC        SHOPLIFTING   \n",
       "6                 F     459PC           BURGLARY   \n",
       "7                 F     211PC            ROBBERY   \n",
       "10                M  243(A)PC  BATTERY ON PERSON   \n",
       "\n",
       "                                    Address Cross Street  \\\n",
       "0                                       5TH       WILTON   \n",
       "2   8300    VAN NUYS                     BL          NaN   \n",
       "6                                     103RD      HICKORY   \n",
       "7                                   VANOWEN      WOODLEY   \n",
       "10                                 VANALDEN       BRYANT   \n",
       "\n",
       "                Location  year  \n",
       "0    (34.0653, -118.314)  2015  \n",
       "2   (34.2216, -118.4488)  2015  \n",
       "6    (33.947, -118.2594)  2015  \n",
       "7   (34.1939, -118.4836)  2015  \n",
       "10  (34.2251, -118.5372)  2015  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DRUNK DRIVING ALCOHOL/DRUGS                   92554\n",
       "DRINKING IN PUBLIC                            92402\n",
       "CORPORAL INJURY ON SPOUSE/COHABITANT/ETC      42644\n",
       "POSSESSION CONTROLLED SUBSTANCE               42115\n",
       "FTA AFTER WRITTEN PROMISE                     30740\n",
       "POSSESSION NARCOTIC CONTROLLED SUBSTANCE      29308\n",
       "SIT/LIE/SLEEP SIDEWALK OR STREET              25463\n",
       "PROSTITUTION                                  25326\n",
       "OPEN ALCOHOLIC BEV IN PUBLIC PARK/PLACE       25033\n",
       "LOS ANGELES MUNICIPAL CODE                    24132\n",
       "GRAND THEFT (OVER $400)                       22913\n",
       "BURGLARY                                      20926\n",
       "ROBBERY                                       20093\n",
       "ADW, NOT FIREARM, W/GBI                       19803\n",
       "BATTERY ON PERSON                             16562\n",
       "BATT EX-SPOUSE/FIANCEE/PERSN W/DATING REL     16394\n",
       "VIOLATION OF PAROLE:FELONY                    15998\n",
       "TAKE VEHICLE W/O OWNER'S CONSENT              13937\n",
       "CURFEW - JUV ONLY                             12393\n",
       "FTA/TRAFFIC WARRANT                           11379\n",
       "SHOPLIFTING                                   10934\n",
       "TRUANCY                                       10785\n",
       "DRIVE W/LIC SUSPEND/REVOKE 4 OTHER REASON     10681\n",
       "TRANSPORT/SELL/ETC CONTROLLED SUBSTANCE        9943\n",
       "FLASH INCARCERATION                            9923\n",
       "DRINKING ALCOHOL                               9284\n",
       "CRIMINAL THREATS                               9225\n",
       "POSS ALCH BEV ON POSTED PREM                   8791\n",
       "DRINKING IN PUBLIC***                          8704\n",
       "ILLEGAL POSSESSION OF SHOPPING CART            8248\n",
       "                                              ...  \n",
       "TAMPER W/UTILITY PROPERTY                         1\n",
       "BRING/POSS F/ARM IN CRTRM/CRTHSE/CRT BLDG         1\n",
       "REAREST: ELEC MONITOR PROB                        1\n",
       "WEAR HEADSET/COVERS BOTH EARS                     1\n",
       "COND BUSINESS AFTR PERMIT SUSPEND/REVOK           1\n",
       "ATTEMPT GRAND THEFT                               1\n",
       "MED ASSIST: FRAUDULENT/FALSE INFO OBT AID         1\n",
       "FURNISH GOOD/SERVICES ON CREDIT CARD+$400         1\n",
       "USE OTHER'S NAME/LETTER TO NEWSPAPER              1\n",
       "ATTEMPT POSSESS CONTROLLED SUBSTANCE              1\n",
       "ATTEMPT TAMPERING W/VEHICLE                       1\n",
       "CAUSE INJURY/DEATH OF GUIDE/ETC DOG               1\n",
       "COMPOUND/CONCEAL FELONY NOT CAPITL OFFENS         1\n",
       "THEFT OF ARTICLE REPRESENT TRADE SECRETS          1\n",
       "DRIVING ON CENTER DIVIDER                         1\n",
       "UNLAWFUL 911 CALLS                                1\n",
       "SELLING WITHOUT PERMIT                            1\n",
       "ATTEMPT TO DESTROY PROPERTY $1000-                1\n",
       "MONTEBELLO MUNICIPAL CODE                         1\n",
       "BRING DRUGS INTO PRISON                           1\n",
       "MFG/SELL/GIVE/POSS ETC LIPSTICK CASE KNIFE        1\n",
       "TAMPER/REMOVE/DISPLACE/INJURE OR DESTROY          1\n",
       "GIV DANG DRUG/ETC:NO PRSC                         1\n",
       "ARCADE W/O PERMIT                                 1\n",
       "DESTROY EVID/OWNERSHIP OF WRECK PROPERTY          1\n",
       "POSS DEADLY WEAPON W/INT COMMIT ASSAULT           1\n",
       "POSS/ETC OBSCENE MATT:CHILD UNDER 14              1\n",
       "ATTEMPTED AGGRAVATED ARSON                        1\n",
       "ATTEMPT -THEFT: APPROPRIATE LOST PROPERTY         1\n",
       "OWN DOG TRAIN TO FIGHT/ATTACK-INJ CAUSE           1\n",
       "Name: Charge Description, Length: 2315, dtype: int64"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Charge Description'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "between2010_2018 = df[(df['year'] >= 2010) & (df['year']<=2018)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>Report ID</th>\n",
       "      <th>Arrest Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>Area ID</th>\n",
       "      <th>Area Name</th>\n",
       "      <th>Reporting District</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex Code</th>\n",
       "      <th>Descent Code</th>\n",
       "      <th>Charge Group Code</th>\n",
       "      <th>Charge Group Description</th>\n",
       "      <th>Arrest Type Code</th>\n",
       "      <th>Charge</th>\n",
       "      <th>Charge Description</th>\n",
       "      <th>Address</th>\n",
       "      <th>Cross Street</th>\n",
       "      <th>Location</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4248313</td>\n",
       "      <td>2015-02-24</td>\n",
       "      <td>1310.0</td>\n",
       "      <td>20</td>\n",
       "      <td>Olympic</td>\n",
       "      <td>2022</td>\n",
       "      <td>37</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>5TH</td>\n",
       "      <td>WILTON</td>\n",
       "      <td>(34.0653, -118.314)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4254777</td>\n",
       "      <td>2015-02-26</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>19</td>\n",
       "      <td>Mission</td>\n",
       "      <td>1985</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Larceny</td>\n",
       "      <td>M</td>\n",
       "      <td>459.5PC</td>\n",
       "      <td>SHOPLIFTING</td>\n",
       "      <td>8300    VAN NUYS                     BL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(34.2216, -118.4488)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4256466</td>\n",
       "      <td>2015-02-28</td>\n",
       "      <td>1430.0</td>\n",
       "      <td>18</td>\n",
       "      <td>Southeast</td>\n",
       "      <td>1824</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>B</td>\n",
       "      <td>5.0</td>\n",
       "      <td>Burglary</td>\n",
       "      <td>F</td>\n",
       "      <td>459PC</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>103RD</td>\n",
       "      <td>HICKORY</td>\n",
       "      <td>(33.947, -118.2594)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4256564</td>\n",
       "      <td>2015-02-28</td>\n",
       "      <td>1715.0</td>\n",
       "      <td>10</td>\n",
       "      <td>West Valley</td>\n",
       "      <td>1039</td>\n",
       "      <td>16</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Robbery</td>\n",
       "      <td>F</td>\n",
       "      <td>211PC</td>\n",
       "      <td>ROBBERY</td>\n",
       "      <td>VANOWEN</td>\n",
       "      <td>WOODLEY</td>\n",
       "      <td>(34.1939, -118.4836)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4256815</td>\n",
       "      <td>2015-03-01</td>\n",
       "      <td>110.0</td>\n",
       "      <td>17</td>\n",
       "      <td>Devonshire</td>\n",
       "      <td>1794</td>\n",
       "      <td>22</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>8.0</td>\n",
       "      <td>Other Assaults</td>\n",
       "      <td>M</td>\n",
       "      <td>243(A)PC</td>\n",
       "      <td>BATTERY ON PERSON</td>\n",
       "      <td>VANALDEN</td>\n",
       "      <td>BRYANT</td>\n",
       "      <td>(34.2251, -118.5372)</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Report ID Arrest Date    Time  Area ID    Area Name  Reporting District  \\\n",
       "0     4248313  2015-02-24  1310.0       20      Olympic                2022   \n",
       "2     4254777  2015-02-26  2010.0       19      Mission                1985   \n",
       "6     4256466  2015-02-28  1430.0       18    Southeast                1824   \n",
       "7     4256564  2015-02-28  1715.0       10  West Valley                1039   \n",
       "10    4256815  2015-03-01   110.0       17   Devonshire                1794   \n",
       "\n",
       "    Age Sex Code Descent Code  Charge Group Code Charge Group Description  \\\n",
       "0    37        M            H                5.0                 Burglary   \n",
       "2    22        M            H                6.0                  Larceny   \n",
       "6    22        M            B                5.0                 Burglary   \n",
       "7    16        M            H                3.0                  Robbery   \n",
       "10   22        M            H                8.0           Other Assaults   \n",
       "\n",
       "   Arrest Type Code    Charge Charge Description  \\\n",
       "0                 F     459PC           BURGLARY   \n",
       "2                 M   459.5PC        SHOPLIFTING   \n",
       "6                 F     459PC           BURGLARY   \n",
       "7                 F     211PC            ROBBERY   \n",
       "10                M  243(A)PC  BATTERY ON PERSON   \n",
       "\n",
       "                                    Address Cross Street  \\\n",
       "0                                       5TH       WILTON   \n",
       "2   8300    VAN NUYS                     BL          NaN   \n",
       "6                                     103RD      HICKORY   \n",
       "7                                   VANOWEN      WOODLEY   \n",
       "10                                 VANALDEN       BRYANT   \n",
       "\n",
       "                Location  year  \n",
       "0    (34.0653, -118.314)  2015  \n",
       "2   (34.2216, -118.4488)  2015  \n",
       "6    (33.947, -118.2594)  2015  \n",
       "7   (34.1939, -118.4836)  2015  \n",
       "10  (34.2251, -118.5372)  2015  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "between2010_2018.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1231627, 18)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "between2010_2018.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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