project 03 data analysis of police.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5873e1f8",
   "metadata": {},
   "source": [
    "# Police Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2f868ee",
   "metadata": {},
   "source": [
    "In this project ,I am going to analyze police dataset using pandas dataframe to generate some insights .\n",
    "I have CSV file of police data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f45cf452",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e894838c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r\"C:\\Users\\utsha\\OneDrive\\Desktop\\Data analysis project\\dataset\\3. Police Data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5ceb22a8",
   "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>stop_date</th>\n",
       "      <th>stop_time</th>\n",
       "      <th>country_name</th>\n",
       "      <th>driver_gender</th>\n",
       "      <th>driver_age_raw</th>\n",
       "      <th>driver_age</th>\n",
       "      <th>driver_race</th>\n",
       "      <th>violation_raw</th>\n",
       "      <th>violation</th>\n",
       "      <th>search_conducted</th>\n",
       "      <th>search_type</th>\n",
       "      <th>stop_outcome</th>\n",
       "      <th>is_arrested</th>\n",
       "      <th>stop_duration</th>\n",
       "      <th>drugs_related_stop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/2/2005</td>\n",
       "      <td>1:55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/18/2005</td>\n",
       "      <td>8:15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/23/2005</td>\n",
       "      <td>23:15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/20/2005</td>\n",
       "      <td>17:15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>M</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arrest Driver</td>\n",
       "      <td>True</td>\n",
       "      <td>16-30 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time  country_name driver_gender  driver_age_raw  \\\n",
       "0   1/2/2005      1:55           NaN             M          1985.0   \n",
       "1  1/18/2005      8:15           NaN             M          1965.0   \n",
       "2  1/23/2005     23:15           NaN             M          1972.0   \n",
       "3  2/20/2005     17:15           NaN             M          1986.0   \n",
       "4  3/14/2005     10:00           NaN             F          1984.0   \n",
       "\n",
       "   driver_age driver_race     violation_raw violation  search_conducted  \\\n",
       "0        20.0       White          Speeding  Speeding             False   \n",
       "1        40.0       White          Speeding  Speeding             False   \n",
       "2        33.0       White          Speeding  Speeding             False   \n",
       "3        19.0       White  Call for Service     Other             False   \n",
       "4        21.0       White          Speeding  Speeding             False   \n",
       "\n",
       "  search_type   stop_outcome is_arrested stop_duration  drugs_related_stop  \n",
       "0         NaN       Citation       False      0-15 Min               False  \n",
       "1         NaN       Citation       False      0-15 Min               False  \n",
       "2         NaN       Citation       False      0-15 Min               False  \n",
       "3         NaN  Arrest Driver        True     16-30 Min               False  \n",
       "4         NaN       Citation       False      0-15 Min               False  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "017a906f",
   "metadata": {},
   "source": [
    "### 1.Remove the column that only contains the missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c9109a83",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 65535 entries, 0 to 65534\n",
      "Data columns (total 15 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   stop_date           65535 non-null  object \n",
      " 1   stop_time           65535 non-null  object \n",
      " 2   country_name        0 non-null      float64\n",
      " 3   driver_gender       61474 non-null  object \n",
      " 4   driver_age_raw      61481 non-null  float64\n",
      " 5   driver_age          61228 non-null  float64\n",
      " 6   driver_race         61475 non-null  object \n",
      " 7   violation_raw       61475 non-null  object \n",
      " 8   violation           61475 non-null  object \n",
      " 9   search_conducted    65535 non-null  bool   \n",
      " 10  search_type         2479 non-null   object \n",
      " 11  stop_outcome        61475 non-null  object \n",
      " 12  is_arrested         61475 non-null  object \n",
      " 13  stop_duration       61475 non-null  object \n",
      " 14  drugs_related_stop  65535 non-null  bool   \n",
      "dtypes: bool(2), float64(3), object(10)\n",
      "memory usage: 6.6+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "348aebd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "stop_date                 0\n",
       "stop_time                 0\n",
       "country_name          65535\n",
       "driver_gender          4061\n",
       "driver_age_raw         4054\n",
       "driver_age             4307\n",
       "driver_race            4060\n",
       "violation_raw          4060\n",
       "violation              4060\n",
       "search_conducted          0\n",
       "search_type           63056\n",
       "stop_outcome           4060\n",
       "is_arrested            4060\n",
       "stop_duration          4060\n",
       "drugs_related_stop        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d87e1b2",
   "metadata": {},
   "source": [
    "Here as we can see column 'country_name' has no value so we will remove it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2ac04e0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns = 'country_name',inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4a0b7378",
   "metadata": {},
   "outputs": [
    {
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       "      <td>23:15</td>\n",
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       "      <td>1972.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "      <td>2/20/2005</td>\n",
       "      <td>17:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arrest Driver</td>\n",
       "      <td>True</td>\n",
       "      <td>16-30 Min</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
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       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "      <td>1987.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
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       "      <td>12/6/2012</td>\n",
       "      <td>22:22</td>\n",
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       "      <td>1954.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
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       "      <td>Warning</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "      <td>12/6/2012</td>\n",
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       "      <td>1985.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Black</td>\n",
       "      <td>Equipment/Inspection Violation</td>\n",
       "      <td>Equipment</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>0:30</td>\n",
       "      <td>F</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "  </tbody>\n",
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       "<p>65535 rows × 14 columns</p>\n",
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      ],
      "text/plain": [
       "       stop_date stop_time driver_gender  driver_age_raw  driver_age  \\\n",
       "0       1/2/2005      1:55             M          1985.0        20.0   \n",
       "1      1/18/2005      8:15             M          1965.0        40.0   \n",
       "2      1/23/2005     23:15             M          1972.0        33.0   \n",
       "3      2/20/2005     17:15             M          1986.0        19.0   \n",
       "4      3/14/2005     10:00             F          1984.0        21.0   \n",
       "...          ...       ...           ...             ...         ...   \n",
       "65530  12/6/2012     17:54             F          1987.0        25.0   \n",
       "65531  12/6/2012     22:22             M          1954.0        58.0   \n",
       "65532  12/6/2012     23:20             M          1985.0        27.0   \n",
       "65533  12/7/2012      0:23           NaN             NaN         NaN   \n",
       "65534  12/7/2012      0:30             F          1985.0        27.0   \n",
       "\n",
       "      driver_race                   violation_raw  violation  \\\n",
       "0           White                        Speeding   Speeding   \n",
       "1           White                        Speeding   Speeding   \n",
       "2           White                        Speeding   Speeding   \n",
       "3           White                Call for Service      Other   \n",
       "4           White                        Speeding   Speeding   \n",
       "...           ...                             ...        ...   \n",
       "65530       White                        Speeding   Speeding   \n",
       "65531       White                        Speeding   Speeding   \n",
       "65532       Black  Equipment/Inspection Violation  Equipment   \n",
       "65533         NaN                             NaN        NaN   \n",
       "65534       White                        Speeding   Speeding   \n",
       "\n",
       "       search_conducted search_type   stop_outcome is_arrested stop_duration  \\\n",
       "0                 False         NaN       Citation       False      0-15 Min   \n",
       "1                 False         NaN       Citation       False      0-15 Min   \n",
       "2                 False         NaN       Citation       False      0-15 Min   \n",
       "3                 False         NaN  Arrest Driver        True     16-30 Min   \n",
       "4                 False         NaN       Citation       False      0-15 Min   \n",
       "...                 ...         ...            ...         ...           ...   \n",
       "65530             False         NaN       Citation       False      0-15 Min   \n",
       "65531             False         NaN        Warning       False      0-15 Min   \n",
       "65532             False         NaN       Citation       False      0-15 Min   \n",
       "65533             False         NaN            NaN         NaN           NaN   \n",
       "65534             False         NaN       Citation       False      0-15 Min   \n",
       "\n",
       "       drugs_related_stop  \n",
       "0                   False  \n",
       "1                   False  \n",
       "2                   False  \n",
       "3                   False  \n",
       "4                   False  \n",
       "...                   ...  \n",
       "65530               False  \n",
       "65531               False  \n",
       "65532               False  \n",
       "65533               False  \n",
       "65534               False  \n",
       "\n",
       "[65535 rows x 14 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a39d71b",
   "metadata": {},
   "source": [
    "### 2. For Speeding , were Men or Women stopped more often ? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3af168a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stop_date</th>\n",
       "      <th>stop_time</th>\n",
       "      <th>driver_gender</th>\n",
       "      <th>driver_age_raw</th>\n",
       "      <th>driver_age</th>\n",
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       "      <th>search_type</th>\n",
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       "      <th>drugs_related_stop</th>\n",
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       "      <td>1/23/2005</td>\n",
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       "      <td>33.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "      <td>2/20/2005</td>\n",
       "      <td>17:15</td>\n",
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       "      <td>1986.0</td>\n",
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       "      <td>Other</td>\n",
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       "      <td>True</td>\n",
       "      <td>16-30 Min</td>\n",
       "      <td>False</td>\n",
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       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time driver_gender  driver_age_raw  driver_age driver_race  \\\n",
       "0   1/2/2005      1:55             M          1985.0        20.0       White   \n",
       "1  1/18/2005      8:15             M          1965.0        40.0       White   \n",
       "2  1/23/2005     23:15             M          1972.0        33.0       White   \n",
       "3  2/20/2005     17:15             M          1986.0        19.0       White   \n",
       "4  3/14/2005     10:00             F          1984.0        21.0       White   \n",
       "\n",
       "      violation_raw violation  search_conducted search_type   stop_outcome  \\\n",
       "0          Speeding  Speeding             False         NaN       Citation   \n",
       "1          Speeding  Speeding             False         NaN       Citation   \n",
       "2          Speeding  Speeding             False         NaN       Citation   \n",
       "3  Call for Service     Other             False         NaN  Arrest Driver   \n",
       "4          Speeding  Speeding             False         NaN       Citation   \n",
       "\n",
       "  is_arrested stop_duration  drugs_related_stop  \n",
       "0       False      0-15 Min               False  \n",
       "1       False      0-15 Min               False  \n",
       "2       False      0-15 Min               False  \n",
       "3        True     16-30 Min               False  \n",
       "4       False      0-15 Min               False  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4467c236",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M    25517\n",
       "F    11686\n",
       "Name: driver_gender, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.violation == 'Speeding'].driver_gender.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeacb4d0",
   "metadata": {},
   "source": [
    "It seems like male are speeding more often"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c93adb92",
   "metadata": {},
   "source": [
    "### 3.Does gender affect who gets searched during a stop ?\n",
    "Question ( mapping + data-type casting )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9ce14724",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
       "      <td>16-30 Min</td>\n",
       "      <td>False</td>\n",
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       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time driver_gender  driver_age_raw  driver_age driver_race  \\\n",
       "0   1/2/2005      1:55             M          1985.0        20.0       White   \n",
       "1  1/18/2005      8:15             M          1965.0        40.0       White   \n",
       "2  1/23/2005     23:15             M          1972.0        33.0       White   \n",
       "3  2/20/2005     17:15             M          1986.0        19.0       White   \n",
       "4  3/14/2005     10:00             F          1984.0        21.0       White   \n",
       "\n",
       "      violation_raw violation  search_conducted search_type   stop_outcome  \\\n",
       "0          Speeding  Speeding             False         NaN       Citation   \n",
       "1          Speeding  Speeding             False         NaN       Citation   \n",
       "2          Speeding  Speeding             False         NaN       Citation   \n",
       "3  Call for Service     Other             False         NaN  Arrest Driver   \n",
       "4          Speeding  Speeding             False         NaN       Citation   \n",
       "\n",
       "  is_arrested stop_duration  drugs_related_stop  \n",
       "0       False      0-15 Min               False  \n",
       "1       False      0-15 Min               False  \n",
       "2       False      0-15 Min               False  \n",
       "3        True     16-30 Min               False  \n",
       "4       False      0-15 Min               False  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "82b462ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "driver_gender\n",
       "F     366\n",
       "M    2113\n",
       "Name: search_conducted, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('driver_gender').search_conducted.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ece8d618",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    63056\n",
       "True      2479\n",
       "Name: search_conducted, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.search_conducted.value_counts()  #checking how many times search was conducted"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60abd6b9",
   "metadata": {},
   "source": [
    "#### Search was conducted 2479 times out of which male were searched 2113 times."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a3194b2",
   "metadata": {},
   "source": [
    "So, male are searched more often"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61683bf5",
   "metadata": {},
   "source": [
    "### 4.What is the mean stop_duration ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3382d25a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
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       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arrest Driver</td>\n",
       "      <td>True</td>\n",
       "      <td>16-30 Min</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
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       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>0-15 Min</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time driver_gender  driver_age_raw  driver_age driver_race  \\\n",
       "0   1/2/2005      1:55             M          1985.0        20.0       White   \n",
       "1  1/18/2005      8:15             M          1965.0        40.0       White   \n",
       "2  1/23/2005     23:15             M          1972.0        33.0       White   \n",
       "3  2/20/2005     17:15             M          1986.0        19.0       White   \n",
       "4  3/14/2005     10:00             F          1984.0        21.0       White   \n",
       "\n",
       "      violation_raw violation  search_conducted search_type   stop_outcome  \\\n",
       "0          Speeding  Speeding             False         NaN       Citation   \n",
       "1          Speeding  Speeding             False         NaN       Citation   \n",
       "2          Speeding  Speeding             False         NaN       Citation   \n",
       "3  Call for Service     Other             False         NaN  Arrest Driver   \n",
       "4          Speeding  Speeding             False         NaN       Citation   \n",
       "\n",
       "  is_arrested stop_duration  drugs_related_stop  \n",
       "0       False      0-15 Min               False  \n",
       "1       False      0-15 Min               False  \n",
       "2       False      0-15 Min               False  \n",
       "3        True     16-30 Min               False  \n",
       "4       False      0-15 Min               False  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "521dfa67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('O')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.stop_duration.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "58c109bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0-15 Min     47379\n",
       "16-30 Min    11448\n",
       "30+ Min       2647\n",
       "2                1\n",
       "Name: stop_duration, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.stop_duration.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6b2bd9ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['stop_duration'] = df['stop_duration'].map({'0-15 Min' : 7.5, '16-30 Min' : 23,'30+ Min' : 30 })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f26c6563",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>stop_date</th>\n",
       "      <th>stop_time</th>\n",
       "      <th>driver_gender</th>\n",
       "      <th>driver_age_raw</th>\n",
       "      <th>driver_age</th>\n",
       "      <th>driver_race</th>\n",
       "      <th>violation_raw</th>\n",
       "      <th>violation</th>\n",
       "      <th>search_conducted</th>\n",
       "      <th>search_type</th>\n",
       "      <th>stop_outcome</th>\n",
       "      <th>is_arrested</th>\n",
       "      <th>stop_duration</th>\n",
       "      <th>drugs_related_stop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/2/2005</td>\n",
       "      <td>1:55</td>\n",
       "      <td>M</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
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       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/18/2005</td>\n",
       "      <td>8:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
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       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/23/2005</td>\n",
       "      <td>23:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/20/2005</td>\n",
       "      <td>17:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arrest Driver</td>\n",
       "      <td>True</td>\n",
       "      <td>23.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time driver_gender  driver_age_raw  driver_age driver_race  \\\n",
       "0   1/2/2005      1:55             M          1985.0        20.0       White   \n",
       "1  1/18/2005      8:15             M          1965.0        40.0       White   \n",
       "2  1/23/2005     23:15             M          1972.0        33.0       White   \n",
       "3  2/20/2005     17:15             M          1986.0        19.0       White   \n",
       "4  3/14/2005     10:00             F          1984.0        21.0       White   \n",
       "\n",
       "      violation_raw violation  search_conducted search_type   stop_outcome  \\\n",
       "0          Speeding  Speeding             False         NaN       Citation   \n",
       "1          Speeding  Speeding             False         NaN       Citation   \n",
       "2          Speeding  Speeding             False         NaN       Citation   \n",
       "3  Call for Service     Other             False         NaN  Arrest Driver   \n",
       "4          Speeding  Speeding             False         NaN       Citation   \n",
       "\n",
       "  is_arrested  stop_duration  drugs_related_stop  \n",
       "0       False            7.5               False  \n",
       "1       False            7.5               False  \n",
       "2       False            7.5               False  \n",
       "3        True           23.0               False  \n",
       "4       False            7.5               False  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e5079e63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.355312815173894"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.stop_duration.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cebc3489",
   "metadata": {},
   "source": [
    "### The mean stop_duration is around 11 minute."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9666e2ec",
   "metadata": {},
   "source": [
    "### 5.Compare the age distributions for each violation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "59aa3dd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <td>Speeding</td>\n",
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       "      <td>False</td>\n",
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       "      <th>1</th>\n",
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       "      <td>8:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1965.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/23/2005</td>\n",
       "      <td>23:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2/20/2005</td>\n",
       "      <td>17:15</td>\n",
       "      <td>M</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Call for Service</td>\n",
       "      <td>Other</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Arrest Driver</td>\n",
       "      <td>True</td>\n",
       "      <td>23.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3/14/2005</td>\n",
       "      <td>10:00</td>\n",
       "      <td>F</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>White</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>Speeding</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Citation</td>\n",
       "      <td>False</td>\n",
       "      <td>7.5</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   stop_date stop_time driver_gender  driver_age_raw  driver_age driver_race  \\\n",
       "0   1/2/2005      1:55             M          1985.0        20.0       White   \n",
       "1  1/18/2005      8:15             M          1965.0        40.0       White   \n",
       "2  1/23/2005     23:15             M          1972.0        33.0       White   \n",
       "3  2/20/2005     17:15             M          1986.0        19.0       White   \n",
       "4  3/14/2005     10:00             F          1984.0        21.0       White   \n",
       "\n",
       "      violation_raw violation  search_conducted search_type   stop_outcome  \\\n",
       "0          Speeding  Speeding             False         NaN       Citation   \n",
       "1          Speeding  Speeding             False         NaN       Citation   \n",
       "2          Speeding  Speeding             False         NaN       Citation   \n",
       "3  Call for Service     Other             False         NaN  Arrest Driver   \n",
       "4          Speeding  Speeding             False         NaN       Citation   \n",
       "\n",
       "  is_arrested  stop_duration  drugs_related_stop  \n",
       "0       False            7.5               False  \n",
       "1       False            7.5               False  \n",
       "2       False            7.5               False  \n",
       "3        True           23.0               False  \n",
       "4       False            7.5               False  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "fcd357c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "driver_age  violation          \n",
       "15.0        Moving violation        4\n",
       "            Speeding                1\n",
       "16.0        Speeding               18\n",
       "            Moving violation        6\n",
       "            Registration/plates     5\n",
       "                                   ..\n",
       "85.0        Moving violation        1\n",
       "86.0        Speeding                3\n",
       "            Moving violation        2\n",
       "            Other                   1\n",
       "88.0        Speeding                2\n",
       "Name: violation, Length: 333, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('driver_age').violation.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "504ca714",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
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       "    <tr>\n",
       "      <th>violation</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Equipment</th>\n",
       "      <td>6507.0</td>\n",
       "      <td>31.682957</td>\n",
       "      <td>11.380671</td>\n",
       "      <td>16.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moving violation</th>\n",
       "      <td>11876.0</td>\n",
       "      <td>36.736443</td>\n",
       "      <td>13.258350</td>\n",
       "      <td>15.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>3477.0</td>\n",
       "      <td>40.362381</td>\n",
       "      <td>12.754423</td>\n",
       "      <td>16.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>86.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Registration/plates</th>\n",
       "      <td>2240.0</td>\n",
       "      <td>32.656696</td>\n",
       "      <td>11.150780</td>\n",
       "      <td>16.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>74.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seat belt</th>\n",
       "      <td>3.0</td>\n",
       "      <td>30.333333</td>\n",
       "      <td>10.214369</td>\n",
       "      <td>23.0</td>\n",
       "      <td>24.5</td>\n",
       "      <td>26.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Speeding</th>\n",
       "      <td>37120.0</td>\n",
       "      <td>33.262581</td>\n",
       "      <td>12.615781</td>\n",
       "      <td>15.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       count       mean        std   min   25%   50%   75%  \\\n",
       "violation                                                                    \n",
       "Equipment             6507.0  31.682957  11.380671  16.0  23.0  28.0  39.0   \n",
       "Moving violation     11876.0  36.736443  13.258350  15.0  25.0  35.0  47.0   \n",
       "Other                 3477.0  40.362381  12.754423  16.0  30.0  41.0  50.0   \n",
       "Registration/plates   2240.0  32.656696  11.150780  16.0  24.0  30.0  40.0   \n",
       "Seat belt                3.0  30.333333  10.214369  23.0  24.5  26.0  34.0   \n",
       "Speeding             37120.0  33.262581  12.615781  15.0  23.0  30.0  42.0   \n",
       "\n",
       "                      max  \n",
       "violation                  \n",
       "Equipment            81.0  \n",
       "Moving violation     86.0  \n",
       "Other                86.0  \n",
       "Registration/plates  74.0  \n",
       "Seat belt            42.0  \n",
       "Speeding             88.0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('violation').driver_age.describe()"
   ]
  }
 ],
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