tp_sf_VALLEAU_ELIEN.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Prep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from datetime import datetime\n",
    "pd.set_option('max_columns', 100)\n",
    "from datetime import datetime\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.read_csv(\"train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>Descript</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>PdDistrict</th>\n",
       "      <th>Resolution</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>WARRANT ARREST</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>TRAFFIC VIOLATION ARREST</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>TRAFFIC VIOLATION ARREST</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>GRAND THEFT FROM LOCKED AUTO</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>NONE</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>GRAND THEFT FROM LOCKED AUTO</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>PARK</td>\n",
       "      <td>NONE</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Dates        Category                      Descript  \\\n",
       "0  2015-05-13 23:53:00        WARRANTS                WARRANT ARREST   \n",
       "1  2015-05-13 23:53:00  OTHER OFFENSES      TRAFFIC VIOLATION ARREST   \n",
       "2  2015-05-13 23:33:00  OTHER OFFENSES      TRAFFIC VIOLATION ARREST   \n",
       "3  2015-05-13 23:30:00   LARCENY/THEFT  GRAND THEFT FROM LOCKED AUTO   \n",
       "4  2015-05-13 23:30:00   LARCENY/THEFT  GRAND THEFT FROM LOCKED AUTO   \n",
       "\n",
       "   DayOfWeek PdDistrict      Resolution                    Address  \\\n",
       "0  Wednesday   NORTHERN  ARREST, BOOKED         OAK ST / LAGUNA ST   \n",
       "1  Wednesday   NORTHERN  ARREST, BOOKED         OAK ST / LAGUNA ST   \n",
       "2  Wednesday   NORTHERN  ARREST, BOOKED  VANNESS AV / GREENWICH ST   \n",
       "3  Wednesday   NORTHERN            NONE   1500 Block of LOMBARD ST   \n",
       "4  Wednesday       PARK            NONE  100 Block of BRODERICK ST   \n",
       "\n",
       "            X          Y  \n",
       "0 -122.425892  37.774599  \n",
       "1 -122.425892  37.774599  \n",
       "2 -122.424363  37.800414  \n",
       "3 -122.426995  37.800873  \n",
       "4 -122.438738  37.771541  "
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dates          object\n",
       "Category       object\n",
       "Descript       object\n",
       "DayOfWeek      object\n",
       "PdDistrict     object\n",
       "Resolution     object\n",
       "Address        object\n",
       "X             float64\n",
       "Y             float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1['Dates'] = df1['Dates'].astype('datetime64[ns]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropDescRes_df = df1.drop(columns=['Descript', 'Resolution'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>PdDistrict</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>PARK</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category  DayOfWeek PdDistrict  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS  Wednesday   NORTHERN   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES  Wednesday   NORTHERN   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES  Wednesday   NORTHERN   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT  Wednesday   NORTHERN   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT  Wednesday       PARK   \n",
       "\n",
       "                     Address           X          Y  \n",
       "0         OAK ST / LAGUNA ST -122.425892  37.774599  \n",
       "1         OAK ST / LAGUNA ST -122.425892  37.774599  \n",
       "2  VANNESS AV / GREENWICH ST -122.424363  37.800414  \n",
       "3   1500 Block of LOMBARD ST -122.426995  37.800873  \n",
       "4  100 Block of BRODERICK ST -122.438738  37.771541  "
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropDescRes_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recherche des NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Y             0.0 %\n",
       "X             0.0 %\n",
       "Address       0.0 %\n",
       "PdDistrict    0.0 %\n",
       "DayOfWeek     0.0 %\n",
       "Category      0.0 %\n",
       "Dates         0.0 %\n",
       "dtype: object"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_isna = dropDescRes_df.isna().sum().apply(lambda col:round(col/len(df1)*100, 2))\n",
    "df_isna.sort_values(ascending=False).apply(lambda col: str(col) + \" %\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['NORTHERN', 'PARK', 'INGLESIDE', 'BAYVIEW', 'RICHMOND', 'CENTRAL',\n",
       "       'TARAVAL', 'TENDERLOIN', 'MISSION', 'SOUTHERN'], dtype=object)"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropDescRes_df['PdDistrict'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DayOfWeek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [],
   "source": [
    "dropDescRes_df['WeekEnd']=dropDescRes_df['DayOfWeek'].apply(lambda val: 1 if val in [\"Friday\", \"Saturday\", \"Sunday\"] else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>PdDistrict</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>PARK</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category  DayOfWeek PdDistrict  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS  Wednesday   NORTHERN   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES  Wednesday   NORTHERN   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES  Wednesday   NORTHERN   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT  Wednesday   NORTHERN   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT  Wednesday       PARK   \n",
       "\n",
       "                     Address           X          Y  WeekEnd  \n",
       "0         OAK ST / LAGUNA ST -122.425892  37.774599        0  \n",
       "1         OAK ST / LAGUNA ST -122.425892  37.774599        0  \n",
       "2  VANNESS AV / GREENWICH ST -122.424363  37.800414        0  \n",
       "3   1500 Block of LOMBARD ST -122.426995  37.800873        0  \n",
       "4  100 Block of BRODERICK ST -122.438738  37.771541        0  "
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dropDescRes_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_cols_dayofweek = pd.get_dummies(dropDescRes_df['DayOfWeek'], dummy_na=False, prefix='Day_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "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>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  Day__Thursday  \\\n",
       "0            0            0              0            0              0   \n",
       "1            0            0              0            0              0   \n",
       "2            0            0              0            0              0   \n",
       "3            0            0              0            0              0   \n",
       "4            0            0              0            0              0   \n",
       "\n",
       "   Day__Tuesday  Day__Wednesday  \n",
       "0             0               1  \n",
       "1             0               1  \n",
       "2             0               1  \n",
       "3             0               1  \n",
       "4             0               1  "
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_cols_dayofweek.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_dayofweek = pd.concat([\n",
    "    dropDescRes_df.drop(columns=['DayOfWeek']),\n",
    "    ohe_cols_dayofweek\n",
    "], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>PdDistrict</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>NORTHERN</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>PARK</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category PdDistrict                    Address  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS   NORTHERN         OAK ST / LAGUNA ST   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES   NORTHERN         OAK ST / LAGUNA ST   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES   NORTHERN  VANNESS AV / GREENWICH ST   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT   NORTHERN   1500 Block of LOMBARD ST   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT       PARK  100 Block of BRODERICK ST   \n",
       "\n",
       "            X          Y  WeekEnd  Day__Friday  Day__Monday  Day__Saturday  \\\n",
       "0 -122.425892  37.774599        0            0            0              0   \n",
       "1 -122.425892  37.774599        0            0            0              0   \n",
       "2 -122.424363  37.800414        0            0            0              0   \n",
       "3 -122.426995  37.800873        0            0            0              0   \n",
       "4 -122.438738  37.771541        0            0            0              0   \n",
       "\n",
       "   Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \n",
       "0            0              0             0               1  \n",
       "1            0              0             0               1  \n",
       "2            0              0             0               1  \n",
       "3            0              0             0               1  \n",
       "4            0              0             0               1  "
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_dayofweek.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PdDistrict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SOUTHERN      157182\n",
       "MISSION       119908\n",
       "NORTHERN      105296\n",
       "BAYVIEW        89431\n",
       "CENTRAL        85460\n",
       "TENDERLOIN     81809\n",
       "INGLESIDE      78845\n",
       "TARAVAL        65596\n",
       "PARK           49313\n",
       "RICHMOND       45209\n",
       "Name: PdDistrict, dtype: int64"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_dayofweek['PdDistrict'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_cols_pddistrict = pd.get_dummies(ohe_df_dayofweek['PdDistrict'], dummy_na=False, prefix='Dis_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "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>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \n",
       "0          0              0              0             0                0  \n",
       "1          0              0              0             0                0  \n",
       "2          0              0              0             0                0  \n",
       "3          0              0              0             0                0  \n",
       "4          1              0              0             0                0  "
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_cols_pddistrict.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_PdDistrict = pd.concat([\n",
    "    ohe_df_dayofweek.drop(columns=['PdDistrict']),\n",
    "    ohe_cols_pddistrict\n",
    "], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category                    Address           X  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS         OAK ST / LAGUNA ST -122.425892   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738   \n",
       "\n",
       "           Y  WeekEnd  Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  \\\n",
       "0  37.774599        0            0            0              0            0   \n",
       "1  37.774599        0            0            0              0            0   \n",
       "2  37.800414        0            0            0              0            0   \n",
       "3  37.800873        0            0            0              0            0   \n",
       "4  37.771541        0            0            0              0            0   \n",
       "\n",
       "   Day__Thursday  Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  \\\n",
       "0              0             0               1             0             0   \n",
       "1              0             0               1             0             0   \n",
       "2              0             0               1             0             0   \n",
       "3              0             0               1             0             0   \n",
       "4              0             0               1             0             0   \n",
       "\n",
       "   Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  \\\n",
       "0               0             0              1          0              0   \n",
       "1               0             0              1          0              0   \n",
       "2               0             0              1          0              0   \n",
       "3               0             0              1          0              0   \n",
       "4               0             0              0          1              0   \n",
       "\n",
       "   Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \n",
       "0              0             0                0  \n",
       "1              0             0                0  \n",
       "2              0             0                0  \n",
       "3              0             0                0  \n",
       "4              0             0                0  "
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_PdDistrict.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Dates = ohe_df_PdDistrict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Dates['Year']=ohe_df_Dates['Dates'].dt.year\n",
    "ohe_df_Dates['Month']=ohe_df_Dates['Dates'].dt.month\n",
    "ohe_df_Dates['Hour']=ohe_df_Dates['Dates'].dt.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category                    Address           X  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS         OAK ST / LAGUNA ST -122.425892   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738   \n",
       "\n",
       "           Y  WeekEnd  Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  \\\n",
       "0  37.774599        0            0            0              0            0   \n",
       "1  37.774599        0            0            0              0            0   \n",
       "2  37.800414        0            0            0              0            0   \n",
       "3  37.800873        0            0            0              0            0   \n",
       "4  37.771541        0            0            0              0            0   \n",
       "\n",
       "   Day__Thursday  Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  \\\n",
       "0              0             0               1             0             0   \n",
       "1              0             0               1             0             0   \n",
       "2              0             0               1             0             0   \n",
       "3              0             0               1             0             0   \n",
       "4              0             0               1             0             0   \n",
       "\n",
       "   Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  \\\n",
       "0               0             0              1          0              0   \n",
       "1               0             0              1          0              0   \n",
       "2               0             0              1          0              0   \n",
       "3               0             0              1          0              0   \n",
       "4               0             0              0          1              0   \n",
       "\n",
       "   Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  \n",
       "0              0             0                0  2015      5    23  \n",
       "1              0             0                0  2015      5    23  \n",
       "2              0             0                0  2015      5    23  \n",
       "3              0             0                0  2015      5    23  \n",
       "4              0             0                0  2015      5    23  "
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Dates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Dates['Spring'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(4, 7) else 0)\n",
    "ohe_df_Dates['Summer'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(7, 10) else 0)\n",
    "ohe_df_Dates['Autumn'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(10, 1) else 0)\n",
    "ohe_df_Dates['Winter'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(1, 4) else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "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>Dates</th>\n",
       "      <th>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-05-13 23:53:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-05-13 23:33:00</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-05-13 23:30:00</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Dates        Category                    Address           X  \\\n",
       "0 2015-05-13 23:53:00        WARRANTS         OAK ST / LAGUNA ST -122.425892   \n",
       "1 2015-05-13 23:53:00  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892   \n",
       "2 2015-05-13 23:33:00  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363   \n",
       "3 2015-05-13 23:30:00   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995   \n",
       "4 2015-05-13 23:30:00   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738   \n",
       "\n",
       "           Y  WeekEnd  Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  \\\n",
       "0  37.774599        0            0            0              0            0   \n",
       "1  37.774599        0            0            0              0            0   \n",
       "2  37.800414        0            0            0              0            0   \n",
       "3  37.800873        0            0            0              0            0   \n",
       "4  37.771541        0            0            0              0            0   \n",
       "\n",
       "   Day__Thursday  Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  \\\n",
       "0              0             0               1             0             0   \n",
       "1              0             0               1             0             0   \n",
       "2              0             0               1             0             0   \n",
       "3              0             0               1             0             0   \n",
       "4              0             0               1             0             0   \n",
       "\n",
       "   Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  \\\n",
       "0               0             0              1          0              0   \n",
       "1               0             0              1          0              0   \n",
       "2               0             0              1          0              0   \n",
       "3               0             0              1          0              0   \n",
       "4               0             0              0          1              0   \n",
       "\n",
       "   Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  Spring  \\\n",
       "0              0             0                0  2015      5    23       1   \n",
       "1              0             0                0  2015      5    23       1   \n",
       "2              0             0                0  2015      5    23       1   \n",
       "3              0             0                0  2015      5    23       1   \n",
       "4              0             0                0  2015      5    23       1   \n",
       "\n",
       "   Summer  Autumn  Winter  \n",
       "0       0       0       0  \n",
       "1       0       0       0  \n",
       "2       0       0       0  \n",
       "3       0       0       0  \n",
       "4       0       0       0  "
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Dates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Dates.drop(columns=['Dates'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "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>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category                    Address           X          Y  WeekEnd  \\\n",
       "0        WARRANTS         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "1  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "2  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363  37.800414        0   \n",
       "3   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995  37.800873        0   \n",
       "4   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738  37.771541        0   \n",
       "\n",
       "   Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  Day__Thursday  \\\n",
       "0            0            0              0            0              0   \n",
       "1            0            0              0            0              0   \n",
       "2            0            0              0            0              0   \n",
       "3            0            0              0            0              0   \n",
       "4            0            0              0            0              0   \n",
       "\n",
       "   Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  \\\n",
       "0             0               1             0             0               0   \n",
       "1             0               1             0             0               0   \n",
       "2             0               1             0             0               0   \n",
       "3             0               1             0             0               0   \n",
       "4             0               1             0             0               0   \n",
       "\n",
       "   Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  \\\n",
       "0             0              1          0              0              0   \n",
       "1             0              1          0              0              0   \n",
       "2             0              1          0              0              0   \n",
       "3             0              1          0              0              0   \n",
       "4             0              0          1              0              0   \n",
       "\n",
       "   Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  Spring  Summer  Autumn  \\\n",
       "0             0                0  2015      5    23       1       0       0   \n",
       "1             0                0  2015      5    23       1       0       0   \n",
       "2             0                0  2015      5    23       1       0       0   \n",
       "3             0                0  2015      5    23       1       0       0   \n",
       "4             0                0  2015      5    23       1       0       0   \n",
       "\n",
       "   Winter  \n",
       "0       0  \n",
       "1       0  \n",
       "2       0  \n",
       "3       0  \n",
       "4       0  "
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Dates.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recherche de l'évolution du nombre de crime en fonction des années / mois / heures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\elien\\Anaconda3\\envs\\majeure-ml-env\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19323c4a438>"
      ]
     },
     "execution_count": 264,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(ohe_df_Dates['Year'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1931fe748d0>"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(ohe_df_Dates['Month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1931fee6da0>"
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(ohe_df_Dates['Hour'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Catégorisation des heures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Dates['Night'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(0, 6) else 0)\n",
    "ohe_df_Dates['Morning'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(6, 12) else 0)\n",
    "ohe_df_Dates['Afternoon'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(12, 18) else 0)\n",
    "ohe_df_Dates['Evening'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(18, 24) else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "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>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category                    Address           X          Y  WeekEnd  \\\n",
       "0        WARRANTS         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "1  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "2  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363  37.800414        0   \n",
       "3   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995  37.800873        0   \n",
       "4   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738  37.771541        0   \n",
       "\n",
       "   Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  Day__Thursday  \\\n",
       "0            0            0              0            0              0   \n",
       "1            0            0              0            0              0   \n",
       "2            0            0              0            0              0   \n",
       "3            0            0              0            0              0   \n",
       "4            0            0              0            0              0   \n",
       "\n",
       "   Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  \\\n",
       "0             0               1             0             0               0   \n",
       "1             0               1             0             0               0   \n",
       "2             0               1             0             0               0   \n",
       "3             0               1             0             0               0   \n",
       "4             0               1             0             0               0   \n",
       "\n",
       "   Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  \\\n",
       "0             0              1          0              0              0   \n",
       "1             0              1          0              0              0   \n",
       "2             0              1          0              0              0   \n",
       "3             0              1          0              0              0   \n",
       "4             0              0          1              0              0   \n",
       "\n",
       "   Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  Spring  Summer  Autumn  \\\n",
       "0             0                0  2015      5    23       1       0       0   \n",
       "1             0                0  2015      5    23       1       0       0   \n",
       "2             0                0  2015      5    23       1       0       0   \n",
       "3             0                0  2015      5    23       1       0       0   \n",
       "4             0                0  2015      5    23       1       0       0   \n",
       "\n",
       "   Winter  Night  Morning  Afternoon  Evening  \n",
       "0       0      0        0          0        1  \n",
       "1       0      0        0          0        1  \n",
       "2       0      0        0          0        1  \n",
       "3       0      0        0          0        1  \n",
       "4       0      0        0          0        1  "
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Dates.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Address"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Address = ohe_df_Dates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recherche des adresses les plus présentes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['ST', 'AV', 'of', 'WY', 'BL', 'DR', 'JR', 'HY', 'TR', 'PL', 'RD',\n",
       "       'LA', 'AL', 'CT', 'CR', 'LN', 'OF', 'PZ', 'DE', 'MC', 'MT', 'RW',\n",
       "       'LE', 'US', 'PT', 'EL'], dtype=object)"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Address['Address'].str.extract(r'(\\b\\w{2}\\b)')[0].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800 Block of BRYANT ST                  26533\n",
       "800 Block of MARKET ST                   6581\n",
       "2000 Block of MISSION ST                 5097\n",
       "1000 Block of POTRERO AV                 4063\n",
       "900 Block of MARKET ST                   3251\n",
       "0 Block of TURK ST                       3228\n",
       "0 Block of 6TH ST                        2884\n",
       "300 Block of ELLIS ST                    2703\n",
       "400 Block of ELLIS ST                    2590\n",
       "16TH ST / MISSION ST                     2504\n",
       "1000 Block of MARKET ST                  2489\n",
       "1100 Block of MARKET ST                  2319\n",
       "2000 Block of MARKET ST                  2168\n",
       "100 Block of OFARRELL ST                 2140\n",
       "700 Block of MARKET ST                   2081\n",
       "3200 Block of 20TH AV                    2035\n",
       "100 Block of 6TH ST                      1887\n",
       "500 Block of JOHNFKENNEDY DR             1824\n",
       "TURK ST / TAYLOR ST                      1810\n",
       "200 Block of TURK ST                     1800\n",
       "0 Block of PHELAN AV                     1791\n",
       "0 Block of UNITEDNATIONS PZ              1789\n",
       "0 Block of POWELL ST                     1717\n",
       "100 Block of EDDY ST                     1681\n",
       "1400 Block of PHELPS ST                  1629\n",
       "300 Block of EDDY ST                     1589\n",
       "100 Block of GOLDEN GATE AV              1353\n",
       "100 Block of POWELL ST                   1333\n",
       "200 Block of INTERSTATE80 HY             1316\n",
       "MISSION ST / 16TH ST                     1300\n",
       "                                        ...  \n",
       "1600 Block of JOHN F KENNEDY DR             1\n",
       "KEARNY ST / THE EMBARCADERO NORTH ST        1\n",
       "FORESTSIDE AV / ULLOA ST                    1\n",
       "ENCANTO AV / TERRAVISTA AV                  1\n",
       "FOOTE AV / ALEMANY BL                       1\n",
       "OCEAN AV / SAN FERNANDO WY                  1\n",
       "EDDY ST / POWELL ST                         1\n",
       "PACHECO ST / GREAT HWY                      1\n",
       "NORIEGA ST / 38TH AV                        1\n",
       "35TH AV / SLOAT BL                          1\n",
       "BENNINGTON ST / NEWMAN ST                   1\n",
       "THE EMBARCADERO NORTH ST / KEARNY ST        1\n",
       "1100 Block of NORTH POINT ST                1\n",
       "TARAVAL ST / LOWER GREAT HY                 1\n",
       "CABRILLO ST / GREAT HY                      1\n",
       "GRANDVIEW AV / 21ST ST                      1\n",
       "DUNCAN ST / DOLORES ST                      1\n",
       "HARDING RD / SKYLINE BLVD HY                1\n",
       "DIVISADERO ST / BROADWAY ST                 1\n",
       "SANTAYNEZ AV / CAYUGA AV                    1\n",
       "CALIFORNIA ST / CUSHMAN ST                  1\n",
       "22ND ST / ARKANSAS ST                       1\n",
       "33RD AV / PACHECO ST                        1\n",
       "2800 Block of RIVERA ST                     1\n",
       "MASON ST / JOHN ST                          1\n",
       "PERU AV / FELTON ST                         1\n",
       "MCALLISTER ST / CHARLES J BRENHAM ST        1\n",
       "NIAGARA AV / TARA ST                        1\n",
       "LAPU LAPU ST / RIZAL ST                     1\n",
       "MILTON I ROSS ST / INNES AV                 1\n",
       "Name: Address, Length: 23228, dtype: int64"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Address['Address'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "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>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category                    Address           X          Y  WeekEnd  \\\n",
       "0        WARRANTS         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "1  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "2  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363  37.800414        0   \n",
       "3   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995  37.800873        0   \n",
       "4   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738  37.771541        0   \n",
       "\n",
       "   Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  Day__Thursday  \\\n",
       "0            0            0              0            0              0   \n",
       "1            0            0              0            0              0   \n",
       "2            0            0              0            0              0   \n",
       "3            0            0              0            0              0   \n",
       "4            0            0              0            0              0   \n",
       "\n",
       "   Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  \\\n",
       "0             0               1             0             0               0   \n",
       "1             0               1             0             0               0   \n",
       "2             0               1             0             0               0   \n",
       "3             0               1             0             0               0   \n",
       "4             0               1             0             0               0   \n",
       "\n",
       "   Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  \\\n",
       "0             0              1          0              0              0   \n",
       "1             0              1          0              0              0   \n",
       "2             0              1          0              0              0   \n",
       "3             0              1          0              0              0   \n",
       "4             0              0          1              0              0   \n",
       "\n",
       "   Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  Spring  Summer  Autumn  \\\n",
       "0             0                0  2015      5    23       1       0       0   \n",
       "1             0                0  2015      5    23       1       0       0   \n",
       "2             0                0  2015      5    23       1       0       0   \n",
       "3             0                0  2015      5    23       1       0       0   \n",
       "4             0                0  2015      5    23       1       0       0   \n",
       "\n",
       "   Winter  Night  Morning  Afternoon  Evening  \n",
       "0       0      0        0          0        1  \n",
       "1       0      0        0          0        1  \n",
       "2       0      0        0          0        1  \n",
       "3       0      0        0          0        1  \n",
       "4       0      0        0          0        1  "
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Address.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Catégorisation des adresses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Address['isBlock'] = ohe_df_Address['Address'].apply(lambda val: 1 if \"Block\" in val else 0)\n",
    "ohe_df_Address['isST'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" ST\" in val else 0)\n",
    "ohe_df_Address['isAV'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" AV\" in val else 0)\n",
    "ohe_df_Address['Intersection'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" / \" in val else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "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>Category</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>OAK ST / LAGUNA ST</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>VANNESS AV / GREENWICH ST</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>1500 Block of LOMBARD ST</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>100 Block of BRODERICK ST</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category                    Address           X          Y  WeekEnd  \\\n",
       "0        WARRANTS         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "1  OTHER OFFENSES         OAK ST / LAGUNA ST -122.425892  37.774599        0   \n",
       "2  OTHER OFFENSES  VANNESS AV / GREENWICH ST -122.424363  37.800414        0   \n",
       "3   LARCENY/THEFT   1500 Block of LOMBARD ST -122.426995  37.800873        0   \n",
       "4   LARCENY/THEFT  100 Block of BRODERICK ST -122.438738  37.771541        0   \n",
       "\n",
       "   Day__Friday  Day__Monday  Day__Saturday  Day__Sunday  Day__Thursday  \\\n",
       "0            0            0              0            0              0   \n",
       "1            0            0              0            0              0   \n",
       "2            0            0              0            0              0   \n",
       "3            0            0              0            0              0   \n",
       "4            0            0              0            0              0   \n",
       "\n",
       "   Day__Tuesday  Day__Wednesday  Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  \\\n",
       "0             0               1             0             0               0   \n",
       "1             0               1             0             0               0   \n",
       "2             0               1             0             0               0   \n",
       "3             0               1             0             0               0   \n",
       "4             0               1             0             0               0   \n",
       "\n",
       "   Dis__MISSION  Dis__NORTHERN  Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  \\\n",
       "0             0              1          0              0              0   \n",
       "1             0              1          0              0              0   \n",
       "2             0              1          0              0              0   \n",
       "3             0              1          0              0              0   \n",
       "4             0              0          1              0              0   \n",
       "\n",
       "   Dis__TARAVAL  Dis__TENDERLOIN  Year  Month  Hour  Spring  Summer  Autumn  \\\n",
       "0             0                0  2015      5    23       1       0       0   \n",
       "1             0                0  2015      5    23       1       0       0   \n",
       "2             0                0  2015      5    23       1       0       0   \n",
       "3             0                0  2015      5    23       1       0       0   \n",
       "4             0                0  2015      5    23       1       0       0   \n",
       "\n",
       "   Winter  Night  Morning  Afternoon  Evening  isBlock  isST  isAV  \\\n",
       "0       0      0        0          0        1        0     1     0   \n",
       "1       0      0        0          0        1        0     1     0   \n",
       "2       0      0        0          0        1        0     1     1   \n",
       "3       0      0        0          0        1        1     1     0   \n",
       "4       0      0        0          0        1        1     1     0   \n",
       "\n",
       "   Intersection  \n",
       "0             1  \n",
       "1             1  \n",
       "2             1  \n",
       "3             0  \n",
       "4             0  "
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Address.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Address.drop(columns=['Address'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Coordinates = ohe_df_Address"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "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>Category</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0        WARRANTS -122.425892  37.774599        0            0            0   \n",
       "1  OTHER OFFENSES -122.425892  37.774599        0            0            0   \n",
       "2  OTHER OFFENSES -122.424363  37.800414        0            0            0   \n",
       "3   LARCENY/THEFT -122.426995  37.800873        0            0            0   \n",
       "4   LARCENY/THEFT -122.438738  37.771541        0            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            0              0             0               1   \n",
       "1              0            0              0             0               1   \n",
       "2              0            0              0             0               1   \n",
       "3              0            0              0             0               1   \n",
       "4              0            0              0             0               1   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          1              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Spring  Summer  Autumn  Winter  Night  Morning  \\\n",
       "0  2015      5    23       1       0       0       0      0        0   \n",
       "1  2015      5    23       1       0       0       0      0        0   \n",
       "2  2015      5    23       1       0       0       0      0        0   \n",
       "3  2015      5    23       1       0       0       0      0        0   \n",
       "4  2015      5    23       1       0       0       0      0        0   \n",
       "\n",
       "   Afternoon  Evening  isBlock  isST  isAV  Intersection  \n",
       "0          0        1        0     1     0             1  \n",
       "1          0        1        0     1     0             1  \n",
       "2          0        1        0     1     1             1  \n",
       "3          0        1        1     1     0             0  \n",
       "4          0        1        1     1     0             0  "
      ]
     },
     "execution_count": 277,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-122.403405    26354\n",
       "-122.419658     4449\n",
       "-122.406539     3891\n",
       "-122.407634     3170\n",
       "-122.419672     3006\n",
       "-122.409854     2533\n",
       "-122.406521     2329\n",
       "-122.466205     2182\n",
       "-122.475647     2019\n",
       "-122.426956     1991\n",
       "-122.407244     1954\n",
       "-122.452290     1696\n",
       "-122.413564     1658\n",
       "-122.410769     1626\n",
       "-122.394439     1622\n",
       "-122.411071     1609\n",
       "-122.410294     1605\n",
       "-122.413609     1491\n",
       "-122.414056     1452\n",
       "-122.411966     1439\n",
       "-122.407845     1380\n",
       "-122.412515     1326\n",
       "-122.365565     1300\n",
       "-122.409530     1269\n",
       "-122.411988     1264\n",
       "-122.412784     1179\n",
       "-122.414312     1177\n",
       "-122.413238     1164\n",
       "-122.406605     1151\n",
       "-122.408068     1144\n",
       "               ...  \n",
       "-122.456671        1\n",
       "-122.399982        1\n",
       "-122.445038        1\n",
       "-122.467613        1\n",
       "-122.453170        1\n",
       "-122.413466        1\n",
       "-122.501462        1\n",
       "-122.412888        1\n",
       "-122.414593        1\n",
       "-122.442204        1\n",
       "-122.464349        1\n",
       "-122.469545        1\n",
       "-122.404394        1\n",
       "-122.442996        1\n",
       "-122.493090        1\n",
       "-122.443360        1\n",
       "-122.404337        1\n",
       "-122.483990        1\n",
       "-122.439836        1\n",
       "-122.471139        1\n",
       "-122.468881        1\n",
       "-122.509226        1\n",
       "-122.415019        1\n",
       "-122.427695        1\n",
       "-122.393541        1\n",
       "-122.405107        1\n",
       "-122.500331        1\n",
       "-122.437897        1\n",
       "-122.508198        1\n",
       "-122.448020        1\n",
       "Name: X, Length: 34243, dtype: int64"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates['X'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37.775421    26354\n",
       "37.764221     4449\n",
       "37.756486     3891\n",
       "37.784189     3170\n",
       "37.765050     3006\n",
       "37.783386     2533\n",
       "37.785063     2329\n",
       "37.772541     2182\n",
       "37.728528     2019\n",
       "37.769247     1991\n",
       "37.786565     1954\n",
       "37.725693     1696\n",
       "37.779514     1658\n",
       "37.783215     1626\n",
       "37.736444     1622\n",
       "37.781751     1609\n",
       "37.782231     1605\n",
       "37.784697     1491\n",
       "37.782793     1452\n",
       "37.784914     1439\n",
       "37.785094     1380\n",
       "37.780478     1326\n",
       "37.809671     1300\n",
       "37.765718     1269\n",
       "37.785023     1264\n",
       "37.784866     1179\n",
       "37.779834     1177\n",
       "37.782843     1164\n",
       "37.757158     1151\n",
       "37.783992     1144\n",
       "             ...  \n",
       "37.765034        1\n",
       "37.778050        1\n",
       "37.745911        1\n",
       "37.726854        1\n",
       "37.736367        1\n",
       "37.747507        1\n",
       "37.721781        1\n",
       "37.728684        1\n",
       "37.755403        1\n",
       "37.731817        1\n",
       "37.777723        1\n",
       "37.749207        1\n",
       "37.778564        1\n",
       "37.790325        1\n",
       "37.781051        1\n",
       "37.759219        1\n",
       "37.709569        1\n",
       "37.771415        1\n",
       "37.793120        1\n",
       "37.776959        1\n",
       "37.761187        1\n",
       "37.783588        1\n",
       "37.794860        1\n",
       "37.734886        1\n",
       "37.732695        1\n",
       "37.744559        1\n",
       "37.764637        1\n",
       "37.725094        1\n",
       "37.738072        1\n",
       "37.768380        1\n",
       "Name: Y, Length: 34243, dtype: int64"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates['Y'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# x = long / y = lat\n",
    "# xCenterSF = -122.431297\n",
    "# yCenterSF = 37.773972\n",
    "xPoliceSF = -122.412900\n",
    "yPoliceSF = 37.783670\n",
    "\n",
    "# distance entre 2 coordonnées X Y en mètres\n",
    "def distanceBetweenM(lat1, lon1, lat2, lon2):\n",
    "    dLat = np.radians(lat2-lat1)\n",
    "    dLon = np.radians(lon2-lon1)\n",
    "\n",
    "    lat1 = np.radians(lat1)\n",
    "    lat2 = np.radians(lat2)\n",
    "\n",
    "    a = np.sin(dLat/2)**2 + np.sin(dLon/2)**2 * np.cos(lat1) * np.cos(lat2)\n",
    "    c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1-a))\n",
    "    return c * 6371 * 1000\n",
    "\n",
    "ohe_df_Coordinates['distanceSFCenterM'] = distanceBetweenM(yPoliceSF, xPoliceSF, ohe_df_Coordinates['Y'], ohe_df_Coordinates['X'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "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>Category</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>distanceSFCenterM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2116.882324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2278.818639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2641.114951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0        WARRANTS -122.425892  37.774599        0            0            0   \n",
       "1  OTHER OFFENSES -122.425892  37.774599        0            0            0   \n",
       "2  OTHER OFFENSES -122.424363  37.800414        0            0            0   \n",
       "3   LARCENY/THEFT -122.426995  37.800873        0            0            0   \n",
       "4   LARCENY/THEFT -122.438738  37.771541        0            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            0              0             0               1   \n",
       "1              0            0              0             0               1   \n",
       "2              0            0              0             0               1   \n",
       "3              0            0              0             0               1   \n",
       "4              0            0              0             0               1   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          1              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Spring  Summer  Autumn  Winter  Night  Morning  \\\n",
       "0  2015      5    23       1       0       0       0      0        0   \n",
       "1  2015      5    23       1       0       0       0      0        0   \n",
       "2  2015      5    23       1       0       0       0      0        0   \n",
       "3  2015      5    23       1       0       0       0      0        0   \n",
       "4  2015      5    23       1       0       0       0      0        0   \n",
       "\n",
       "   Afternoon  Evening  isBlock  isST  isAV  Intersection  distanceSFCenterM  \n",
       "0          0        1        0     1     0             1        1523.529192  \n",
       "1          0        1        0     1     0             1        1523.529192  \n",
       "2          0        1        0     1     1             1        2116.882324  \n",
       "3          0        1        1     1     0             0        2278.818639  \n",
       "4          0        1        1     1     0             0        2641.114951  "
      ]
     },
     "execution_count": 281,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1240.071818    26354\n",
       "2242.771357     4449\n",
       "3073.950529     3891\n",
       "466.408943      3170\n",
       "2154.286105     3006\n",
       "269.561748      2533\n",
       "581.590541      2329\n",
       "4845.499824     2182\n",
       "8247.750041     2019\n",
       "2024.376228     1991\n",
       "592.159470      1954\n",
       "7317.926195     1696\n",
       "465.793552      1658\n",
       "194.021826      1626\n",
       "5496.359614     1622\n",
       "267.114533      1609\n",
       "279.440278      1605\n",
       "130.093884      1491\n",
       "140.830741      1452\n",
       "160.872596      1439\n",
       "471.589416      1380\n",
       "356.568285      1326\n",
       "5065.226129     1300\n",
       "2017.979209     1269\n",
       "170.444690      1264\n",
       "133.344686      1179\n",
       "444.241834      1177\n",
       "96.621065       1164\n",
       "2999.472038     1151\n",
       "426.111955      1144\n",
       "               ...  \n",
       "6326.544275        1\n",
       "5221.962834        1\n",
       "8102.468969        1\n",
       "3980.118045        1\n",
       "1008.083585        1\n",
       "3595.167976        1\n",
       "7762.961772        1\n",
       "2883.692818        1\n",
       "1753.675011        1\n",
       "4228.729523        1\n",
       "3830.586492        1\n",
       "8248.410725        1\n",
       "6984.994360        1\n",
       "1342.705071        1\n",
       "6881.871763        1\n",
       "2704.100320        1\n",
       "7836.046905        1\n",
       "8171.131607        1\n",
       "1931.758108        1\n",
       "9768.018002        1\n",
       "7609.568469        1\n",
       "6007.672334        1\n",
       "8900.603149        1\n",
       "1706.961845        1\n",
       "7567.177400        1\n",
       "5664.554488        1\n",
       "4377.813658        1\n",
       "5717.115148        1\n",
       "1803.399718        1\n",
       "3348.666663        1\n",
       "Name: distanceSFCenterM, Length: 34243, dtype: int64"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates['distanceSFCenterM'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146,\n",
       " 18.480301196930146]"
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(list(ohe_df_Coordinates['distanceSFCenterM']))[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 5806190.983998071,\n",
       " 10730.16985504247,\n",
       " 10730.16985504247,\n",
       " 10730.16985504247]"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(list(ohe_df_Coordinates['distanceSFCenterM']), reverse=True)[:70]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mise en place de catégories en fonction de la distance. 5806190m semble aberrant, mise à l'écart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohe_df_Coordinates['3km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if val <= 3000 else 0)\n",
    "ohe_df_Coordinates['5km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 3000) & (val<= 5000) else 0)\n",
    "ohe_df_Coordinates['7km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 5000) & (val<= 7000) else 0)\n",
    "ohe_df_Coordinates['9km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 7000) & (val<= 10800) else 0)\n",
    "ohe_df_Coordinates['errCoor']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if val > 10800 else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "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>Category</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>distanceSFCenterM</th>\n",
       "      <th>3km</th>\n",
       "      <th>5km</th>\n",
       "      <th>7km</th>\n",
       "      <th>9km</th>\n",
       "      <th>errCoor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2116.882324</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2278.818639</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2641.114951</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0        WARRANTS -122.425892  37.774599        0            0            0   \n",
       "1  OTHER OFFENSES -122.425892  37.774599        0            0            0   \n",
       "2  OTHER OFFENSES -122.424363  37.800414        0            0            0   \n",
       "3   LARCENY/THEFT -122.426995  37.800873        0            0            0   \n",
       "4   LARCENY/THEFT -122.438738  37.771541        0            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            0              0             0               1   \n",
       "1              0            0              0             0               1   \n",
       "2              0            0              0             0               1   \n",
       "3              0            0              0             0               1   \n",
       "4              0            0              0             0               1   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          1              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Spring  Summer  Autumn  Winter  Night  Morning  \\\n",
       "0  2015      5    23       1       0       0       0      0        0   \n",
       "1  2015      5    23       1       0       0       0      0        0   \n",
       "2  2015      5    23       1       0       0       0      0        0   \n",
       "3  2015      5    23       1       0       0       0      0        0   \n",
       "4  2015      5    23       1       0       0       0      0        0   \n",
       "\n",
       "   Afternoon  Evening  isBlock  isST  isAV  Intersection  distanceSFCenterM  \\\n",
       "0          0        1        0     1     0             1        1523.529192   \n",
       "1          0        1        0     1     0             1        1523.529192   \n",
       "2          0        1        0     1     1             1        2116.882324   \n",
       "3          0        1        1     1     0             0        2278.818639   \n",
       "4          0        1        1     1     0             0        2641.114951   \n",
       "\n",
       "   3km  5km  7km  9km  errCoor  \n",
       "0    1    0    0    0        0  \n",
       "1    1    0    0    0        0  \n",
       "2    1    0    0    0        0  \n",
       "3    1    0    0    0        0  \n",
       "4    1    0    0    0        0  "
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rotation des axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rotate_origin_only(x, y, radians):\n",
    "    \"\"\"Only rotate a point around the origin (0, 0).\"\"\"\n",
    "    xx = x * math.cos(radians) + y * math.sin(radians)\n",
    "    yy = -x * math.sin(radians) + y * math.cos(radians)\n",
    "\n",
    "    return xx, yy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(-98.64965005489718, 81.74895430287103)\n",
      "(-87.1353089001277, 93.92594385177026)\n",
      "(-59.856422150240896, 113.27777236924607)\n",
      "(-28.498419148229765, 124.90990790012768)\n",
      "---------------------------------------------\n",
      "(-98.64118369389588, 81.77338937597088)\n",
      "(-87.1237255529701, 93.94906479756895)\n",
      "(-59.839249354953, 113.29710749707083)\n",
      "(-28.476827202431068, 124.92413955297009)\n"
     ]
    }
   ],
   "source": [
    "x = -122.424363\n",
    "y = 37.774599\n",
    "print(rotate_origin_only(x, y, math.radians(22.5)))\n",
    "print(rotate_origin_only(x, y, math.radians(30)))\n",
    "print(rotate_origin_only(x, y, math.radians(45)))\n",
    "print(rotate_origin_only(x, y, math.radians(60)))\n",
    "print(\"---------------------------------------------\")\n",
    "x = -122.425892\n",
    "y = 37.800414\n",
    "print(rotate_origin_only(x, y, math.radians(22.5)))\n",
    "print(rotate_origin_only(x, y, math.radians(30)))\n",
    "print(rotate_origin_only(x, y, math.radians(45)))\n",
    "print(rotate_origin_only(x, y, math.radians(60)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = ohe_df_Coordinates['X']\n",
    "y = ohe_df_Coordinates['Y']\n",
    "ohe_df_Coordinates['Xr22dot5'] = rotate_origin_only(x, y, math.radians(22.5))[0]\n",
    "ohe_df_Coordinates['Yr22dot5'] = rotate_origin_only(x, y, math.radians(22.5))[1]\n",
    "ohe_df_Coordinates['Xr30'] = rotate_origin_only(x, y, math.radians(30))[0]\n",
    "ohe_df_Coordinates['Yr30'] = rotate_origin_only(x, y, math.radians(30))[1]\n",
    "ohe_df_Coordinates['Xr45'] = rotate_origin_only(x, y, math.radians(45))[0]\n",
    "ohe_df_Coordinates['Yr45'] = rotate_origin_only(x, y, math.radians(45))[1]\n",
    "ohe_df_Coordinates['Xr60'] = rotate_origin_only(x, y, math.radians(60))[0]\n",
    "ohe_df_Coordinates['Yr60'] = rotate_origin_only(x, y, math.radians(60))[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "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>Category</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>distanceSFCenterM</th>\n",
       "      <th>3km</th>\n",
       "      <th>5km</th>\n",
       "      <th>7km</th>\n",
       "      <th>9km</th>\n",
       "      <th>errCoor</th>\n",
       "      <th>Xr22dot5</th>\n",
       "      <th>Yr22dot5</th>\n",
       "      <th>Xr30</th>\n",
       "      <th>Yr30</th>\n",
       "      <th>Xr45</th>\n",
       "      <th>Yr45</th>\n",
       "      <th>Xr60</th>\n",
       "      <th>Yr60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.651063</td>\n",
       "      <td>81.749539</td>\n",
       "      <td>-87.136633</td>\n",
       "      <td>93.926708</td>\n",
       "      <td>-59.857503</td>\n",
       "      <td>113.278853</td>\n",
       "      <td>-28.499184</td>\n",
       "      <td>124.911232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.651063</td>\n",
       "      <td>81.749539</td>\n",
       "      <td>-87.136633</td>\n",
       "      <td>93.926708</td>\n",
       "      <td>-59.857503</td>\n",
       "      <td>113.278853</td>\n",
       "      <td>-28.499184</td>\n",
       "      <td>124.911232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2116.882324</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.639771</td>\n",
       "      <td>81.772805</td>\n",
       "      <td>-87.122401</td>\n",
       "      <td>93.948301</td>\n",
       "      <td>-59.838168</td>\n",
       "      <td>113.296027</td>\n",
       "      <td>-28.476062</td>\n",
       "      <td>124.922816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2278.818639</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.642028</td>\n",
       "      <td>81.774235</td>\n",
       "      <td>-87.124452</td>\n",
       "      <td>93.950014</td>\n",
       "      <td>-59.839705</td>\n",
       "      <td>113.298212</td>\n",
       "      <td>-28.476982</td>\n",
       "      <td>124.925324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2641.114951</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.664101</td>\n",
       "      <td>81.751630</td>\n",
       "      <td>-87.149287</td>\n",
       "      <td>93.930483</td>\n",
       "      <td>-59.868749</td>\n",
       "      <td>113.285775</td>\n",
       "      <td>-28.508255</td>\n",
       "      <td>124.920828</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0        WARRANTS -122.425892  37.774599        0            0            0   \n",
       "1  OTHER OFFENSES -122.425892  37.774599        0            0            0   \n",
       "2  OTHER OFFENSES -122.424363  37.800414        0            0            0   \n",
       "3   LARCENY/THEFT -122.426995  37.800873        0            0            0   \n",
       "4   LARCENY/THEFT -122.438738  37.771541        0            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            0              0             0               1   \n",
       "1              0            0              0             0               1   \n",
       "2              0            0              0             0               1   \n",
       "3              0            0              0             0               1   \n",
       "4              0            0              0             0               1   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          1              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Spring  Summer  Autumn  Winter  Night  Morning  \\\n",
       "0  2015      5    23       1       0       0       0      0        0   \n",
       "1  2015      5    23       1       0       0       0      0        0   \n",
       "2  2015      5    23       1       0       0       0      0        0   \n",
       "3  2015      5    23       1       0       0       0      0        0   \n",
       "4  2015      5    23       1       0       0       0      0        0   \n",
       "\n",
       "   Afternoon  Evening  isBlock  isST  isAV  Intersection  distanceSFCenterM  \\\n",
       "0          0        1        0     1     0             1        1523.529192   \n",
       "1          0        1        0     1     0             1        1523.529192   \n",
       "2          0        1        0     1     1             1        2116.882324   \n",
       "3          0        1        1     1     0             0        2278.818639   \n",
       "4          0        1        1     1     0             0        2641.114951   \n",
       "\n",
       "   3km  5km  7km  9km  errCoor   Xr22dot5   Yr22dot5       Xr30       Yr30  \\\n",
       "0    1    0    0    0        0 -98.651063  81.749539 -87.136633  93.926708   \n",
       "1    1    0    0    0        0 -98.651063  81.749539 -87.136633  93.926708   \n",
       "2    1    0    0    0        0 -98.639771  81.772805 -87.122401  93.948301   \n",
       "3    1    0    0    0        0 -98.642028  81.774235 -87.124452  93.950014   \n",
       "4    1    0    0    0        0 -98.664101  81.751630 -87.149287  93.930483   \n",
       "\n",
       "        Xr45        Yr45       Xr60        Yr60  \n",
       "0 -59.857503  113.278853 -28.499184  124.911232  \n",
       "1 -59.857503  113.278853 -28.499184  124.911232  \n",
       "2 -59.838168  113.296027 -28.476062  124.922816  \n",
       "3 -59.839705  113.298212 -28.476982  124.925324  \n",
       "4 -59.868749  113.285775 -28.508255  124.920828  "
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe_df_Coordinates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sf_crime_preparation(df, delete=True):\n",
    "    df['Dates'] = df['Dates'].astype('datetime64[ns]')\n",
    "    if delete:\n",
    "        dropDescRes_df = df.drop(columns=['Descript', 'Resolution'])\n",
    "    else:\n",
    "        dropDescRes_df = df\n",
    "        \n",
    "    dropDescRes_df['WeekEnd']=dropDescRes_df['DayOfWeek'].apply(lambda val: 1 if val in [\"Friday\", \"Saturday\", \"Sunday\"] else 0)\n",
    "    ohe_cols_dayofweek = pd.get_dummies(dropDescRes_df['DayOfWeek'], dummy_na=False, prefix='Day_')\n",
    "    ohe_df_dayofweek = pd.concat([\n",
    "        dropDescRes_df.drop(columns=['DayOfWeek']),\n",
    "        ohe_cols_dayofweek\n",
    "    ], axis=1)\n",
    "    \n",
    "    ohe_cols_pddistrict = pd.get_dummies(ohe_df_dayofweek['PdDistrict'], dummy_na=False, prefix='Dis_')\n",
    "    ohe_df_PdDistrict = pd.concat([\n",
    "        ohe_df_dayofweek.drop(columns=['PdDistrict']),\n",
    "        ohe_cols_pddistrict\n",
    "    ], axis=1)\n",
    "    \n",
    "    ohe_df_Dates = ohe_df_PdDistrict\n",
    "    ohe_df_Dates['Year']=ohe_df_Dates['Dates'].dt.year\n",
    "    ohe_df_Dates['Month']=ohe_df_Dates['Dates'].dt.month\n",
    "    ohe_df_Dates['Hour']=ohe_df_Dates['Dates'].dt.hour\n",
    "    ohe_df_Dates.drop(columns=['Dates'], inplace=True)\n",
    "    ohe_df_Dates['Night'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(0, 6) else 0)\n",
    "    ohe_df_Dates['Morning'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(6, 12) else 0)\n",
    "    ohe_df_Dates['Afternoon'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(12, 18) else 0)\n",
    "    ohe_df_Dates['Evening'] = ohe_df_Dates['Hour'].apply(lambda val: 1 if val in range(18, 24) else 0)\n",
    "    ohe_df_Dates['Spring'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(4, 7) else 0)\n",
    "    ohe_df_Dates['Summer'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(7, 10) else 0)\n",
    "    ohe_df_Dates['Autumn'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(10, 1) else 0)\n",
    "    ohe_df_Dates['Winter'] = ohe_df_Dates['Month'].apply(lambda val: 1 if val in range(1, 4) else 0)\n",
    "    \n",
    "    ohe_df_Address = ohe_df_Dates\n",
    "    ohe_df_Address['isBlock'] = ohe_df_Address['Address'].apply(lambda val: 1 if \"Block\" in val else 0)\n",
    "    ohe_df_Address['isST'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" ST\" in val else 0)\n",
    "    ohe_df_Address['isAV'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" AV\" in val else 0)\n",
    "    ohe_df_Address['Intersection'] = ohe_df_Address['Address'].apply(lambda val: 1 if \" / \" in val else 0)\n",
    "    ohe_df_Address.drop(columns=['Address'], inplace=True)\n",
    "    \n",
    "    ohe_df_Coordinates = ohe_df_Address\n",
    "    xPoliceSF = -122.412900\n",
    "    yPoliceSF = 37.783670\n",
    "    def distanceBetweenM(lat1, lon1, lat2, lon2):\n",
    "        dLat = np.radians(lat2-lat1)\n",
    "        dLon = np.radians(lon2-lon1)\n",
    "        lat1 = np.radians(lat1)\n",
    "        lat2 = np.radians(lat2)\n",
    "        a = np.sin(dLat/2)**2 + np.sin(dLon/2)**2 * np.cos(lat1) * np.cos(lat2)\n",
    "        c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1-a))\n",
    "        return c * 6371 * 1000\n",
    "    ohe_df_Coordinates['distanceSFCenterM'] = distanceBetweenM(yPoliceSF, xPoliceSF, ohe_df_Coordinates['Y'], ohe_df_Coordinates['X'])\n",
    "    ohe_df_Coordinates['3km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if val <= 3000 else 0)\n",
    "    ohe_df_Coordinates['5km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 3000) & (val<= 5000) else 0)\n",
    "    ohe_df_Coordinates['7km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 5000) & (val<= 7000) else 0)\n",
    "    ohe_df_Coordinates['9km']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if (val > 7000) & (val<= 10800) else 0)\n",
    "    ohe_df_Coordinates['errCoor']=ohe_df_Coordinates['distanceSFCenterM'].apply(lambda val: 1 if val > 10800 else 0)\n",
    "    def rotate_origin_only(x, y, radians):\n",
    "        xx = x * math.cos(radians) + y * math.sin(radians)\n",
    "        yy = -x * math.sin(radians) + y * math.cos(radians)\n",
    "        return xx, yy\n",
    "    x = ohe_df_Coordinates['X']\n",
    "    y = ohe_df_Coordinates['Y']\n",
    "    ohe_df_Coordinates['Xr22dot5'] = rotate_origin_only(x, y, math.radians(22.5))[0]\n",
    "    ohe_df_Coordinates['Yr22dot5'] = rotate_origin_only(x, y, math.radians(22.5))[1]\n",
    "    ohe_df_Coordinates['Xr30'] = rotate_origin_only(x, y, math.radians(30))[0]\n",
    "    ohe_df_Coordinates['Yr30'] = rotate_origin_only(x, y, math.radians(30))[1]\n",
    "    ohe_df_Coordinates['Xr45'] = rotate_origin_only(x, y, math.radians(45))[0]\n",
    "    ohe_df_Coordinates['Yr45'] = rotate_origin_only(x, y, math.radians(45))[1]\n",
    "    ohe_df_Coordinates['Xr60'] = rotate_origin_only(x, y, math.radians(60))[0]\n",
    "    ohe_df_Coordinates['Yr60'] = rotate_origin_only(x, y, math.radians(60))[1]\n",
    "    ohe_df_Coordinates['Xr80'] = rotate_origin_only(x, y, math.radians(80))[0]\n",
    "    ohe_df_Coordinates['Yr80'] = rotate_origin_only(x, y, math.radians(80))[1]\n",
    "    \n",
    "    return ohe_df_Coordinates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TRAIN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score, f1_score, log_loss\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.naive_bayes import GaussianNB \n",
    "from sklearn.svm import SVC\n",
    "from xgboost import XGBClassifier\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from scipy.stats import uniform, norm, randint\n",
    "from sklearn import linear_model, datasets\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import  cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = sf_crime_preparation(df1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "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>Category</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>distanceSFCenterM</th>\n",
       "      <th>3km</th>\n",
       "      <th>5km</th>\n",
       "      <th>7km</th>\n",
       "      <th>9km</th>\n",
       "      <th>errCoor</th>\n",
       "      <th>Xr22dot5</th>\n",
       "      <th>Yr22dot5</th>\n",
       "      <th>Xr30</th>\n",
       "      <th>Yr30</th>\n",
       "      <th>Xr45</th>\n",
       "      <th>Yr45</th>\n",
       "      <th>Xr60</th>\n",
       "      <th>Yr60</th>\n",
       "      <th>Xr80</th>\n",
       "      <th>Yr80</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.651063</td>\n",
       "      <td>81.749539</td>\n",
       "      <td>-87.136633</td>\n",
       "      <td>93.926708</td>\n",
       "      <td>-59.857503</td>\n",
       "      <td>113.278853</td>\n",
       "      <td>-28.499184</td>\n",
       "      <td>124.911232</td>\n",
       "      <td>15.941685</td>\n",
       "      <td>127.125457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.425892</td>\n",
       "      <td>37.774599</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1523.529192</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.651063</td>\n",
       "      <td>81.749539</td>\n",
       "      <td>-87.136633</td>\n",
       "      <td>93.926708</td>\n",
       "      <td>-59.857503</td>\n",
       "      <td>113.278853</td>\n",
       "      <td>-28.499184</td>\n",
       "      <td>124.911232</td>\n",
       "      <td>15.941685</td>\n",
       "      <td>127.125457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>-122.424363</td>\n",
       "      <td>37.800414</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2116.882324</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.639771</td>\n",
       "      <td>81.772805</td>\n",
       "      <td>-87.122401</td>\n",
       "      <td>93.948301</td>\n",
       "      <td>-59.838168</td>\n",
       "      <td>113.296027</td>\n",
       "      <td>-28.476062</td>\n",
       "      <td>124.922816</td>\n",
       "      <td>15.967374</td>\n",
       "      <td>127.128435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.426995</td>\n",
       "      <td>37.800873</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2278.818639</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.642028</td>\n",
       "      <td>81.774235</td>\n",
       "      <td>-87.124452</td>\n",
       "      <td>93.950014</td>\n",
       "      <td>-59.839705</td>\n",
       "      <td>113.298212</td>\n",
       "      <td>-28.476982</td>\n",
       "      <td>124.925324</td>\n",
       "      <td>15.967368</td>\n",
       "      <td>127.131107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>-122.438738</td>\n",
       "      <td>37.771541</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2641.114951</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.664101</td>\n",
       "      <td>81.751630</td>\n",
       "      <td>-87.149287</td>\n",
       "      <td>93.930483</td>\n",
       "      <td>-59.868749</td>\n",
       "      <td>113.285775</td>\n",
       "      <td>-28.508255</td>\n",
       "      <td>124.920828</td>\n",
       "      <td>15.936443</td>\n",
       "      <td>127.137577</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Category           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0        WARRANTS -122.425892  37.774599        0            0            0   \n",
       "1  OTHER OFFENSES -122.425892  37.774599        0            0            0   \n",
       "2  OTHER OFFENSES -122.424363  37.800414        0            0            0   \n",
       "3   LARCENY/THEFT -122.426995  37.800873        0            0            0   \n",
       "4   LARCENY/THEFT -122.438738  37.771541        0            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            0              0             0               1   \n",
       "1              0            0              0             0               1   \n",
       "2              0            0              0             0               1   \n",
       "3              0            0              0             0               1   \n",
       "4              0            0              0             0               1   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             0             0               0             0              1   \n",
       "1             0             0               0             0              1   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               0             0              1   \n",
       "4             0             0               0             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          1              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Night  Morning  Afternoon  Evening  Spring  Summer  \\\n",
       "0  2015      5    23      0        0          0        1       1       0   \n",
       "1  2015      5    23      0        0          0        1       1       0   \n",
       "2  2015      5    23      0        0          0        1       1       0   \n",
       "3  2015      5    23      0        0          0        1       1       0   \n",
       "4  2015      5    23      0        0          0        1       1       0   \n",
       "\n",
       "   Autumn  Winter  isBlock  isST  isAV  Intersection  distanceSFCenterM  3km  \\\n",
       "0       0       0        0     1     0             1        1523.529192    1   \n",
       "1       0       0        0     1     0             1        1523.529192    1   \n",
       "2       0       0        0     1     1             1        2116.882324    1   \n",
       "3       0       0        1     1     0             0        2278.818639    1   \n",
       "4       0       0        1     1     0             0        2641.114951    1   \n",
       "\n",
       "   5km  7km  9km  errCoor   Xr22dot5   Yr22dot5       Xr30       Yr30  \\\n",
       "0    0    0    0        0 -98.651063  81.749539 -87.136633  93.926708   \n",
       "1    0    0    0        0 -98.651063  81.749539 -87.136633  93.926708   \n",
       "2    0    0    0        0 -98.639771  81.772805 -87.122401  93.948301   \n",
       "3    0    0    0        0 -98.642028  81.774235 -87.124452  93.950014   \n",
       "4    0    0    0        0 -98.664101  81.751630 -87.149287  93.930483   \n",
       "\n",
       "        Xr45        Yr45       Xr60        Yr60       Xr80        Yr80  \n",
       "0 -59.857503  113.278853 -28.499184  124.911232  15.941685  127.125457  \n",
       "1 -59.857503  113.278853 -28.499184  124.911232  15.941685  127.125457  \n",
       "2 -59.838168  113.296027 -28.476062  124.922816  15.967374  127.128435  \n",
       "3 -59.839705  113.298212 -28.476982  124.925324  15.967368  127.131107  \n",
       "4 -59.868749  113.285775 -28.508255  124.920828  15.936443  127.137577  "
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = train_df.drop(columns=['Category'])\n",
    "Y = train_df['Category']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_names = np.sort(Y.unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Création du model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "# modelRegLin = LogisticRegression(solver='liblinear', n_jobs=-1) \n",
    "\n",
    "# modelArbreDec = DecisionTreeClassifier(max_depth=7)  \n",
    "\n",
    "# modelBayes = GaussianNB()                    \n",
    "\n",
    "# modelSvm = SVC(gamma='auto', C=0.4)\n",
    "\n",
    "# modelKnn = KNeighborsClassifier(n_jobs=-1, leaf_size=3)                      \n",
    "\n",
    "#grid search pour knn\n",
    "# params = {'n_neighbors':[5,6,7,8,9,10],\n",
    "#          'leaf_size':[1,2,3,5],\n",
    "#          'weights':['uniform', 'distance'],\n",
    "#          'algorithm':['auto', 'ball_tree','kd_tree','brute'],\n",
    "#          'n_jobs':[-1]}\n",
    "# modelKnn1 = KNeighborsClassifier(n_jobs=-1)                      \n",
    "# modelKnn = GridSearchCV(modelKnn1, param_grid=params, n_jobs=1)\n",
    "\n",
    "modelRandomForest = RandomForestClassifier(n_jobs=-1, n_estimators=150, max_depth=13) # score kaggle : 2.36553\n",
    "\n",
    "# modelXGboost = XGBClassifier(n_jobs=-1, learning_rate=1.0, max_depth=6, max_delta_step=1, n_estimators=45) # score kaggle : 2.36231\n",
    "\n",
    "# random search pour xgboost\n",
    "# modelXGboost1 = XGBClassifier()\n",
    "# hyperparametersXG = dict(n_estimators=randint(50, 200), max_depth=randint(1, 10))\n",
    "# modelXGboost = RandomizedSearchCV(modelXGboost1, hyperparametersXG, random_state=1, n_iter=10, cv=5, verbose=0, n_jobs=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split du jeu de données"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Début : 2018-11-30 14:57:34.445648\n",
      "RandomForest 0.29049923482775436\n",
      "Temps : 0:07:04.298133\n"
     ]
    }
   ],
   "source": [
    "timestampBeg = datetime.now()\n",
    "print(\"Début : \" + str(timestampBeg))\n",
    "\n",
    "# print(\"Regression Linéaire \" + str(np.mean(cross_val_score(modelRegLin, X_train, Y_train, cv=5, n_jobs=-1))))    #0.229\n",
    "# print(\"Arbre de décisions \" + str(np.mean(cross_val_score(modelArbreDec, X_train, Y_train, cv=5, n_jobs=-1))))   #0.2440\n",
    "# print(\"Bayes \" + str(np.mean(cross_val_score(modelBayes, X_train, Y_train, cv=5, n_jobs=-1))))                   #0.0248\n",
    "# print(\"SVM-SVC \" + str(np.mean(cross_val_score(modelSvm, X_train, Y_train, cv=5, n_jobs=-1))))                   #out of memory\n",
    "# print(\"KNN \" + str(np.mean(cross_val_score(modelKnn, X_train, Y_train, cv=5, n_jobs=-1))))                       #0.18/0.219\n",
    "print(\"RandomForest \" + str(np.mean(cross_val_score(modelRandomForest, X_train, Y_train, cv=5, n_jobs=-1))))       #0.2904\n",
    "# print(\"XGboost \" + str(np.mean(cross_val_score(modelXGboost, X_train, Y_train, cv=5, n_jobs=-1))))               #0.295\n",
    "\n",
    "timestampEnd = datetime.now()\n",
    "print(\"Temps : \" + str(timestampEnd - timestampBeg))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Entrainement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temps : 0:01:43.086946\n"
     ]
    }
   ],
   "source": [
    "timestampBeg = datetime.now()\n",
    "\n",
    "\n",
    "# modelRegLin.fit(X_train, Y_train)\n",
    "# modelArbreDec.fit(X_train, Y_train)\n",
    "# modelBayes.fit(X_train, Y_train)\n",
    "# modelSvm.fit(X_train, Y_train)\n",
    "# modelKnn.fit(X_train, Y_train)\n",
    "modelRandomForest.fit(X_train, Y_train)\n",
    "# modelXGboost.fit(X_train.values, Y_train.values)\n",
    "\n",
    "\n",
    "timestampEnd = datetime.now()\n",
    "print(\"Temps : \" + str(timestampEnd - timestampBeg))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calcul de l'accuracy en train et test (but = prévenir l'under/over fitting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest\n",
      "Train Accuracy : 0.31485865676592556%\n",
      "Test Accuracy : 0.2926541768691988%\n",
      "--------------------------------------------------------\n",
      "Temps : 0:00:30.533559\n"
     ]
    }
   ],
   "source": [
    "timestampBeg = datetime.now()\n",
    "\n",
    "# print(\"Regression Linéaire\")\n",
    "# train_predicted = modelRegLin.predict(X_train)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelRegLin.predict(X_test)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "# print(\"Arbre de décisionse\")\n",
    "# train_predicted = modelArbreDec.predict(X_train)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelArbreDec.predict(X_test)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "# print(\"Bayes\")\n",
    "# train_predicted = modelBayes.predict(X_train)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelBayes.predict(X_test)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "# print(\"SVM-SVC\")\n",
    "# train_predicted = modelSvm.predict(X_train)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelSvm.predict(X_test)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "# print(\"KNN\")\n",
    "# train_predicted = modelKnn.predict(X_train)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelKnn.predict(X_test)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "print(\"Random Forest\")\n",
    "train_predicted = modelRandomForest.predict(X_train)\n",
    "print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "test_predicted = modelRandomForest.predict(X_test)\n",
    "print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "print(\"--------------------------------------------------------\")\n",
    "\n",
    "# print(\"XGBoost\")\n",
    "# train_predicted = modelXGboost.predict(X_train.values)\n",
    "# print(\"Train Accuracy : \" + str(accuracy_score(Y_train, train_predicted)) + \"%\")\n",
    "# test_predicted = modelXGboost.predict(X_test.values)\n",
    "# print(\"Test Accuracy : \" + str(accuracy_score(Y_test, test_predicted)) + \"%\")\n",
    "# print(\"--------------------------------------------------------\")\n",
    "\n",
    "\n",
    "timestampEnd = datetime.now()\n",
    "print(\"Temps : \" + str(timestampEnd - timestampBeg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [],
   "source": [
    "modelToSubmit = modelRandomForest\n",
    "\n",
    "#Entrainement sur l'ensembre des données : pas de changement notoire \n",
    "#modelToSubmit.fit(X, Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calcul score log loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LogLoss : 2.230809006878982\n"
     ]
    }
   ],
   "source": [
    "train_predictedProba = modelToSubmit.predict_proba(X)\n",
    "# train_predictedProba = modelToSubmit.predict_proba(X.values)  #pour xgboost\n",
    "print(\"LogLoss : \" + str(log_loss(Y, train_predictedProba)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw_test_df = pd.read_csv(\"test.csv\")\n",
    "test_df= sf_crime_preparation(raw_test_df, False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "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>Id</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>WeekEnd</th>\n",
       "      <th>Day__Friday</th>\n",
       "      <th>Day__Monday</th>\n",
       "      <th>Day__Saturday</th>\n",
       "      <th>Day__Sunday</th>\n",
       "      <th>Day__Thursday</th>\n",
       "      <th>Day__Tuesday</th>\n",
       "      <th>Day__Wednesday</th>\n",
       "      <th>Dis__BAYVIEW</th>\n",
       "      <th>Dis__CENTRAL</th>\n",
       "      <th>Dis__INGLESIDE</th>\n",
       "      <th>Dis__MISSION</th>\n",
       "      <th>Dis__NORTHERN</th>\n",
       "      <th>Dis__PARK</th>\n",
       "      <th>Dis__RICHMOND</th>\n",
       "      <th>Dis__SOUTHERN</th>\n",
       "      <th>Dis__TARAVAL</th>\n",
       "      <th>Dis__TENDERLOIN</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Night</th>\n",
       "      <th>Morning</th>\n",
       "      <th>Afternoon</th>\n",
       "      <th>Evening</th>\n",
       "      <th>Spring</th>\n",
       "      <th>Summer</th>\n",
       "      <th>Autumn</th>\n",
       "      <th>Winter</th>\n",
       "      <th>isBlock</th>\n",
       "      <th>isST</th>\n",
       "      <th>isAV</th>\n",
       "      <th>Intersection</th>\n",
       "      <th>distanceSFCenterM</th>\n",
       "      <th>3km</th>\n",
       "      <th>5km</th>\n",
       "      <th>7km</th>\n",
       "      <th>9km</th>\n",
       "      <th>errCoor</th>\n",
       "      <th>Xr22dot5</th>\n",
       "      <th>Yr22dot5</th>\n",
       "      <th>Xr30</th>\n",
       "      <th>Yr30</th>\n",
       "      <th>Xr45</th>\n",
       "      <th>Yr45</th>\n",
       "      <th>Xr60</th>\n",
       "      <th>Yr60</th>\n",
       "      <th>Xr80</th>\n",
       "      <th>Yr80</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>-122.399588</td>\n",
       "      <td>37.735051</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5531.400019</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.641895</td>\n",
       "      <td>81.702936</td>\n",
       "      <td>-87.133627</td>\n",
       "      <td>93.879307</td>\n",
       "      <td>-59.866868</td>\n",
       "      <td>113.232289</td>\n",
       "      <td>-28.520281</td>\n",
       "      <td>124.868678</td>\n",
       "      <td>15.907305</td>\n",
       "      <td>127.092686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>-122.391523</td>\n",
       "      <td>37.732432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5999.304384</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.635446</td>\n",
       "      <td>81.697430</td>\n",
       "      <td>-87.127952</td>\n",
       "      <td>93.873006</td>\n",
       "      <td>-59.863017</td>\n",
       "      <td>113.224735</td>\n",
       "      <td>-28.518516</td>\n",
       "      <td>124.860384</td>\n",
       "      <td>15.906127</td>\n",
       "      <td>127.084289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>-122.426002</td>\n",
       "      <td>37.792212</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1492.599061</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.644424</td>\n",
       "      <td>81.765854</td>\n",
       "      <td>-87.127922</td>\n",
       "      <td>93.942017</td>\n",
       "      <td>-59.845126</td>\n",
       "      <td>113.291386</td>\n",
       "      <td>-28.483985</td>\n",
       "      <td>124.920134</td>\n",
       "      <td>15.959012</td>\n",
       "      <td>127.128625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>-122.437394</td>\n",
       "      <td>37.721412</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7249.969449</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.682043</td>\n",
       "      <td>81.704803</td>\n",
       "      <td>-87.173188</td>\n",
       "      <td>93.886398</td>\n",
       "      <td>-59.903245</td>\n",
       "      <td>113.249378</td>\n",
       "      <td>-28.550996</td>\n",
       "      <td>124.894600</td>\n",
       "      <td>15.887309</td>\n",
       "      <td>127.127549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>-122.437394</td>\n",
       "      <td>37.721412</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7249.969449</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-98.682043</td>\n",
       "      <td>81.704803</td>\n",
       "      <td>-87.173188</td>\n",
       "      <td>93.886398</td>\n",
       "      <td>-59.903245</td>\n",
       "      <td>113.249378</td>\n",
       "      <td>-28.550996</td>\n",
       "      <td>124.894600</td>\n",
       "      <td>15.887309</td>\n",
       "      <td>127.127549</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id           X          Y  WeekEnd  Day__Friday  Day__Monday  \\\n",
       "0   0 -122.399588  37.735051        1            0            0   \n",
       "1   1 -122.391523  37.732432        1            0            0   \n",
       "2   2 -122.426002  37.792212        1            0            0   \n",
       "3   3 -122.437394  37.721412        1            0            0   \n",
       "4   4 -122.437394  37.721412        1            0            0   \n",
       "\n",
       "   Day__Saturday  Day__Sunday  Day__Thursday  Day__Tuesday  Day__Wednesday  \\\n",
       "0              0            1              0             0               0   \n",
       "1              0            1              0             0               0   \n",
       "2              0            1              0             0               0   \n",
       "3              0            1              0             0               0   \n",
       "4              0            1              0             0               0   \n",
       "\n",
       "   Dis__BAYVIEW  Dis__CENTRAL  Dis__INGLESIDE  Dis__MISSION  Dis__NORTHERN  \\\n",
       "0             1             0               0             0              0   \n",
       "1             1             0               0             0              0   \n",
       "2             0             0               0             0              1   \n",
       "3             0             0               1             0              0   \n",
       "4             0             0               1             0              0   \n",
       "\n",
       "   Dis__PARK  Dis__RICHMOND  Dis__SOUTHERN  Dis__TARAVAL  Dis__TENDERLOIN  \\\n",
       "0          0              0              0             0                0   \n",
       "1          0              0              0             0                0   \n",
       "2          0              0              0             0                0   \n",
       "3          0              0              0             0                0   \n",
       "4          0              0              0             0                0   \n",
       "\n",
       "   Year  Month  Hour  Night  Morning  Afternoon  Evening  Spring  Summer  \\\n",
       "0  2015      5    23      0        0          0        1       1       0   \n",
       "1  2015      5    23      0        0          0        1       1       0   \n",
       "2  2015      5    23      0        0          0        1       1       0   \n",
       "3  2015      5    23      0        0          0        1       1       0   \n",
       "4  2015      5    23      0        0          0        1       1       0   \n",
       "\n",
       "   Autumn  Winter  isBlock  isST  isAV  Intersection  distanceSFCenterM  3km  \\\n",
       "0       0       0        1     0     1             0        5531.400019    0   \n",
       "1       0       0        0     1     1             1        5999.304384    0   \n",
       "2       0       0        1     1     0             0        1492.599061    1   \n",
       "3       0       0        1     1     0             0        7249.969449    0   \n",
       "4       0       0        1     1     0             0        7249.969449    0   \n",
       "\n",
       "   5km  7km  9km  errCoor   Xr22dot5   Yr22dot5       Xr30       Yr30  \\\n",
       "0    0    1    0        0 -98.641895  81.702936 -87.133627  93.879307   \n",
       "1    0    1    0        0 -98.635446  81.697430 -87.127952  93.873006   \n",
       "2    0    0    0        0 -98.644424  81.765854 -87.127922  93.942017   \n",
       "3    0    0    1        0 -98.682043  81.704803 -87.173188  93.886398   \n",
       "4    0    0    1        0 -98.682043  81.704803 -87.173188  93.886398   \n",
       "\n",
       "        Xr45        Yr45       Xr60        Yr60       Xr80        Yr80  \n",
       "0 -59.866868  113.232289 -28.520281  124.868678  15.907305  127.092686  \n",
       "1 -59.863017  113.224735 -28.518516  124.860384  15.906127  127.084289  \n",
       "2 -59.845126  113.291386 -28.483985  124.920134  15.959012  127.128625  \n",
       "3 -59.903245  113.249378 -28.550996  124.894600  15.887309  127.127549  \n",
       "4 -59.903245  113.249378 -28.550996  124.894600  15.887309  127.127549  "
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Extraction de la colonne ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "out_id_df = test_df.drop(columns=['Id'])\n",
    "id_test_df = test_df['Id']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prédiction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_predictedProba = modelToSubmit.predict_proba(out_id_df)\n",
    "# test_predictedProba = modelToSubmit.predict_proba(out_id_df.values) #pour xGboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pred = pd.DataFrame(data=test_predictedProba, columns=cat_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "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>ARSON</th>\n",
       "      <th>ASSAULT</th>\n",
       "      <th>BAD CHECKS</th>\n",
       "      <th>BRIBERY</th>\n",
       "      <th>BURGLARY</th>\n",
       "      <th>DISORDERLY CONDUCT</th>\n",
       "      <th>DRIVING UNDER THE INFLUENCE</th>\n",
       "      <th>DRUG/NARCOTIC</th>\n",
       "      <th>DRUNKENNESS</th>\n",
       "      <th>EMBEZZLEMENT</th>\n",
       "      <th>EXTORTION</th>\n",
       "      <th>FAMILY OFFENSES</th>\n",
       "      <th>FORGERY/COUNTERFEITING</th>\n",
       "      <th>FRAUD</th>\n",
       "      <th>GAMBLING</th>\n",
       "      <th>KIDNAPPING</th>\n",
       "      <th>LARCENY/THEFT</th>\n",
       "      <th>LIQUOR LAWS</th>\n",
       "      <th>LOITERING</th>\n",
       "      <th>MISSING PERSON</th>\n",
       "      <th>NON-CRIMINAL</th>\n",
       "      <th>OTHER OFFENSES</th>\n",
       "      <th>PORNOGRAPHY/OBSCENE MAT</th>\n",
       "      <th>PROSTITUTION</th>\n",
       "      <th>RECOVERED VEHICLE</th>\n",
       "      <th>ROBBERY</th>\n",
       "      <th>RUNAWAY</th>\n",
       "      <th>SECONDARY CODES</th>\n",
       "      <th>SEX OFFENSES FORCIBLE</th>\n",
       "      <th>SEX OFFENSES NON FORCIBLE</th>\n",
       "      <th>STOLEN PROPERTY</th>\n",
       "      <th>SUICIDE</th>\n",
       "      <th>SUSPICIOUS OCC</th>\n",
       "      <th>TREA</th>\n",
       "      <th>TRESPASS</th>\n",
       "      <th>VANDALISM</th>\n",
       "      <th>VEHICLE THEFT</th>\n",
       "      <th>WARRANTS</th>\n",
       "      <th>WEAPON LAWS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.003107</td>\n",
       "      <td>0.144157</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>0.001706</td>\n",
       "      <td>0.030331</td>\n",
       "      <td>0.002546</td>\n",
       "      <td>0.003918</td>\n",
       "      <td>0.017006</td>\n",
       "      <td>0.004563</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.006222</td>\n",
       "      <td>0.016794</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.003389</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.000419</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.054715</td>\n",
       "      <td>0.083569</td>\n",
       "      <td>0.090857</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.007242</td>\n",
       "      <td>0.034805</td>\n",
       "      <td>0.004955</td>\n",
       "      <td>0.022612</td>\n",
       "      <td>0.005478</td>\n",
       "      <td>0.001134</td>\n",
       "      <td>0.003702</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.063798</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.007423</td>\n",
       "      <td>0.085186</td>\n",
       "      <td>0.134364</td>\n",
       "      <td>0.024847</td>\n",
       "      <td>0.016825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000842</td>\n",
       "      <td>0.073329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.000740</td>\n",
       "      <td>0.001878</td>\n",
       "      <td>0.006253</td>\n",
       "      <td>0.087575</td>\n",
       "      <td>0.002095</td>\n",
       "      <td>0.000397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.004584</td>\n",
       "      <td>0.003500</td>\n",
       "      <td>0.001513</td>\n",
       "      <td>0.001294</td>\n",
       "      <td>0.046992</td>\n",
       "      <td>0.003739</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.005207</td>\n",
       "      <td>0.048157</td>\n",
       "      <td>0.427854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.001750</td>\n",
       "      <td>0.047212</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.008198</td>\n",
       "      <td>0.002711</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003141</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032183</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000603</td>\n",
       "      <td>0.022824</td>\n",
       "      <td>0.056735</td>\n",
       "      <td>0.084867</td>\n",
       "      <td>0.023232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.001961</td>\n",
       "      <td>0.061367</td>\n",
       "      <td>0.000601</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.134061</td>\n",
       "      <td>0.001181</td>\n",
       "      <td>0.001502</td>\n",
       "      <td>0.011651</td>\n",
       "      <td>0.003122</td>\n",
       "      <td>0.000806</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.009051</td>\n",
       "      <td>0.015790</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.002461</td>\n",
       "      <td>0.325578</td>\n",
       "      <td>0.000776</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.016525</td>\n",
       "      <td>0.085564</td>\n",
       "      <td>0.058313</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.004047</td>\n",
       "      <td>0.002307</td>\n",
       "      <td>0.012616</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.010519</td>\n",
       "      <td>0.004212</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.006079</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>0.033189</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.070182</td>\n",
       "      <td>0.097074</td>\n",
       "      <td>0.015747</td>\n",
       "      <td>0.003091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.001676</td>\n",
       "      <td>0.136586</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.037153</td>\n",
       "      <td>0.004208</td>\n",
       "      <td>0.002448</td>\n",
       "      <td>0.043413</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>0.000415</td>\n",
       "      <td>0.001078</td>\n",
       "      <td>0.009510</td>\n",
       "      <td>0.010549</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.004686</td>\n",
       "      <td>0.119217</td>\n",
       "      <td>0.004272</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.042090</td>\n",
       "      <td>0.077238</td>\n",
       "      <td>0.116001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.006095</td>\n",
       "      <td>0.042958</td>\n",
       "      <td>0.004916</td>\n",
       "      <td>0.019638</td>\n",
       "      <td>0.005816</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.008383</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>0.041175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004344</td>\n",
       "      <td>0.083787</td>\n",
       "      <td>0.107747</td>\n",
       "      <td>0.038953</td>\n",
       "      <td>0.017185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.001676</td>\n",
       "      <td>0.136586</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.037153</td>\n",
       "      <td>0.004208</td>\n",
       "      <td>0.002448</td>\n",
       "      <td>0.043413</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>0.000415</td>\n",
       "      <td>0.001078</td>\n",
       "      <td>0.009510</td>\n",
       "      <td>0.010549</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.004686</td>\n",
       "      <td>0.119217</td>\n",
       "      <td>0.004272</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.042090</td>\n",
       "      <td>0.077238</td>\n",
       "      <td>0.116001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.006095</td>\n",
       "      <td>0.042958</td>\n",
       "      <td>0.004916</td>\n",
       "      <td>0.019638</td>\n",
       "      <td>0.005816</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.008383</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>0.041175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004344</td>\n",
       "      <td>0.083787</td>\n",
       "      <td>0.107747</td>\n",
       "      <td>0.038953</td>\n",
       "      <td>0.017185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ARSON   ASSAULT  BAD CHECKS   BRIBERY  BURGLARY  DISORDERLY CONDUCT  \\\n",
       "0  0.003107  0.144157    0.000240  0.001706  0.030331            0.002546   \n",
       "1  0.000842  0.073329    0.000000  0.000117  0.000740            0.001878   \n",
       "2  0.001961  0.061367    0.000601  0.000150  0.134061            0.001181   \n",
       "3  0.001676  0.136586    0.000312  0.000463  0.037153            0.004208   \n",
       "4  0.001676  0.136586    0.000312  0.000463  0.037153            0.004208   \n",
       "\n",
       "   DRIVING UNDER THE INFLUENCE  DRUG/NARCOTIC  DRUNKENNESS  EMBEZZLEMENT  \\\n",
       "0                     0.003918       0.017006     0.004563      0.002051   \n",
       "1                     0.006253       0.087575     0.002095      0.000397   \n",
       "2                     0.001502       0.011651     0.003122      0.000806   \n",
       "3                     0.002448       0.043413     0.004985      0.000453   \n",
       "4                     0.002448       0.043413     0.004985      0.000453   \n",
       "\n",
       "   EXTORTION  FAMILY OFFENSES  FORGERY/COUNTERFEITING     FRAUD  GAMBLING  \\\n",
       "0   0.000132         0.001660                0.006222  0.016794  0.000012   \n",
       "1   0.000000         0.000039                0.004584  0.003500  0.001513   \n",
       "2   0.000210         0.000097                0.009051  0.015790  0.000221   \n",
       "3   0.000415         0.001078                0.009510  0.010549  0.000770   \n",
       "4   0.000415         0.001078                0.009510  0.010549  0.000770   \n",
       "\n",
       "   KIDNAPPING  LARCENY/THEFT  LIQUOR LAWS  LOITERING  MISSING PERSON  \\\n",
       "0    0.003389       0.118949     0.000419   0.000050        0.054715   \n",
       "1    0.001294       0.046992     0.003739   0.000405        0.005207   \n",
       "2    0.002461       0.325578     0.000776   0.000158        0.016525   \n",
       "3    0.004686       0.119217     0.004272   0.000236        0.042090   \n",
       "4    0.004686       0.119217     0.004272   0.000236        0.042090   \n",
       "\n",
       "   NON-CRIMINAL  OTHER OFFENSES  PORNOGRAPHY/OBSCENE MAT  PROSTITUTION  \\\n",
       "0      0.083569        0.090857                 0.000000      0.000104   \n",
       "1      0.048157        0.427854                 0.000000      0.000027   \n",
       "2      0.085564        0.058313                 0.000002      0.004047   \n",
       "3      0.077238        0.116001                 0.000000      0.000336   \n",
       "4      0.077238        0.116001                 0.000000      0.000336   \n",
       "\n",
       "   RECOVERED VEHICLE   ROBBERY   RUNAWAY  SECONDARY CODES  \\\n",
       "0           0.007242  0.034805  0.004955         0.022612   \n",
       "1           0.001750  0.047212  0.000007         0.008198   \n",
       "2           0.002307  0.012616  0.000163         0.010519   \n",
       "3           0.006095  0.042958  0.004916         0.019638   \n",
       "4           0.006095  0.042958  0.004916         0.019638   \n",
       "\n",
       "   SEX OFFENSES FORCIBLE  SEX OFFENSES NON FORCIBLE  STOLEN PROPERTY  \\\n",
       "0               0.005478                   0.001134         0.003702   \n",
       "1               0.002711                   0.000000         0.003141   \n",
       "2               0.004212                   0.000009         0.006079   \n",
       "3               0.005816                   0.000319         0.008383   \n",
       "4               0.005816                   0.000319         0.008383   \n",
       "\n",
       "    SUICIDE  SUSPICIOUS OCC      TREA  TRESPASS  VANDALISM  VEHICLE THEFT  \\\n",
       "0  0.001129        0.063798  0.000004  0.007423   0.085186       0.134364   \n",
       "1  0.000000        0.032183  0.000000  0.000603   0.022824       0.056735   \n",
       "2  0.000213        0.033189  0.000000  0.009406   0.070182       0.097074   \n",
       "3  0.000588        0.041175  0.000000  0.004344   0.083787       0.107747   \n",
       "4  0.000588        0.041175  0.000000  0.004344   0.083787       0.107747   \n",
       "\n",
       "   WARRANTS  WEAPON LAWS  \n",
       "0  0.024847     0.016825  \n",
       "1  0.084867     0.023232  \n",
       "2  0.015747     0.003091  \n",
       "3  0.038953     0.017185  \n",
       "4  0.038953     0.017185  "
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_pred.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Concaténation des prédictions et de l'ID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "submission_df = pd.concat([\n",
    "        id_test_df, \n",
    "        df_pred\n",
    "    ], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "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>Id</th>\n",
       "      <th>ARSON</th>\n",
       "      <th>ASSAULT</th>\n",
       "      <th>BAD CHECKS</th>\n",
       "      <th>BRIBERY</th>\n",
       "      <th>BURGLARY</th>\n",
       "      <th>DISORDERLY CONDUCT</th>\n",
       "      <th>DRIVING UNDER THE INFLUENCE</th>\n",
       "      <th>DRUG/NARCOTIC</th>\n",
       "      <th>DRUNKENNESS</th>\n",
       "      <th>EMBEZZLEMENT</th>\n",
       "      <th>EXTORTION</th>\n",
       "      <th>FAMILY OFFENSES</th>\n",
       "      <th>FORGERY/COUNTERFEITING</th>\n",
       "      <th>FRAUD</th>\n",
       "      <th>GAMBLING</th>\n",
       "      <th>KIDNAPPING</th>\n",
       "      <th>LARCENY/THEFT</th>\n",
       "      <th>LIQUOR LAWS</th>\n",
       "      <th>LOITERING</th>\n",
       "      <th>MISSING PERSON</th>\n",
       "      <th>NON-CRIMINAL</th>\n",
       "      <th>OTHER OFFENSES</th>\n",
       "      <th>PORNOGRAPHY/OBSCENE MAT</th>\n",
       "      <th>PROSTITUTION</th>\n",
       "      <th>RECOVERED VEHICLE</th>\n",
       "      <th>ROBBERY</th>\n",
       "      <th>RUNAWAY</th>\n",
       "      <th>SECONDARY CODES</th>\n",
       "      <th>SEX OFFENSES FORCIBLE</th>\n",
       "      <th>SEX OFFENSES NON FORCIBLE</th>\n",
       "      <th>STOLEN PROPERTY</th>\n",
       "      <th>SUICIDE</th>\n",
       "      <th>SUSPICIOUS OCC</th>\n",
       "      <th>TREA</th>\n",
       "      <th>TRESPASS</th>\n",
       "      <th>VANDALISM</th>\n",
       "      <th>VEHICLE THEFT</th>\n",
       "      <th>WARRANTS</th>\n",
       "      <th>WEAPON LAWS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.003107</td>\n",
       "      <td>0.144157</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>0.001706</td>\n",
       "      <td>0.030331</td>\n",
       "      <td>0.002546</td>\n",
       "      <td>0.003918</td>\n",
       "      <td>0.017006</td>\n",
       "      <td>0.004563</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>0.006222</td>\n",
       "      <td>0.016794</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.003389</td>\n",
       "      <td>0.118949</td>\n",
       "      <td>0.000419</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.054715</td>\n",
       "      <td>0.083569</td>\n",
       "      <td>0.090857</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.007242</td>\n",
       "      <td>0.034805</td>\n",
       "      <td>0.004955</td>\n",
       "      <td>0.022612</td>\n",
       "      <td>0.005478</td>\n",
       "      <td>0.001134</td>\n",
       "      <td>0.003702</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.063798</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.007423</td>\n",
       "      <td>0.085186</td>\n",
       "      <td>0.134364</td>\n",
       "      <td>0.024847</td>\n",
       "      <td>0.016825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000842</td>\n",
       "      <td>0.073329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>0.000740</td>\n",
       "      <td>0.001878</td>\n",
       "      <td>0.006253</td>\n",
       "      <td>0.087575</td>\n",
       "      <td>0.002095</td>\n",
       "      <td>0.000397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.004584</td>\n",
       "      <td>0.003500</td>\n",
       "      <td>0.001513</td>\n",
       "      <td>0.001294</td>\n",
       "      <td>0.046992</td>\n",
       "      <td>0.003739</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.005207</td>\n",
       "      <td>0.048157</td>\n",
       "      <td>0.427854</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.001750</td>\n",
       "      <td>0.047212</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.008198</td>\n",
       "      <td>0.002711</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003141</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032183</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000603</td>\n",
       "      <td>0.022824</td>\n",
       "      <td>0.056735</td>\n",
       "      <td>0.084867</td>\n",
       "      <td>0.023232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.001961</td>\n",
       "      <td>0.061367</td>\n",
       "      <td>0.000601</td>\n",
       "      <td>0.000150</td>\n",
       "      <td>0.134061</td>\n",
       "      <td>0.001181</td>\n",
       "      <td>0.001502</td>\n",
       "      <td>0.011651</td>\n",
       "      <td>0.003122</td>\n",
       "      <td>0.000806</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.009051</td>\n",
       "      <td>0.015790</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.002461</td>\n",
       "      <td>0.325578</td>\n",
       "      <td>0.000776</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.016525</td>\n",
       "      <td>0.085564</td>\n",
       "      <td>0.058313</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.004047</td>\n",
       "      <td>0.002307</td>\n",
       "      <td>0.012616</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.010519</td>\n",
       "      <td>0.004212</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.006079</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>0.033189</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.070182</td>\n",
       "      <td>0.097074</td>\n",
       "      <td>0.015747</td>\n",
       "      <td>0.003091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.001676</td>\n",
       "      <td>0.136586</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.037153</td>\n",
       "      <td>0.004208</td>\n",
       "      <td>0.002448</td>\n",
       "      <td>0.043413</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>0.000415</td>\n",
       "      <td>0.001078</td>\n",
       "      <td>0.009510</td>\n",
       "      <td>0.010549</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.004686</td>\n",
       "      <td>0.119217</td>\n",
       "      <td>0.004272</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.042090</td>\n",
       "      <td>0.077238</td>\n",
       "      <td>0.116001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.006095</td>\n",
       "      <td>0.042958</td>\n",
       "      <td>0.004916</td>\n",
       "      <td>0.019638</td>\n",
       "      <td>0.005816</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.008383</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>0.041175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004344</td>\n",
       "      <td>0.083787</td>\n",
       "      <td>0.107747</td>\n",
       "      <td>0.038953</td>\n",
       "      <td>0.017185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.001676</td>\n",
       "      <td>0.136586</td>\n",
       "      <td>0.000312</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.037153</td>\n",
       "      <td>0.004208</td>\n",
       "      <td>0.002448</td>\n",
       "      <td>0.043413</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.000453</td>\n",
       "      <td>0.000415</td>\n",
       "      <td>0.001078</td>\n",
       "      <td>0.009510</td>\n",
       "      <td>0.010549</td>\n",
       "      <td>0.000770</td>\n",
       "      <td>0.004686</td>\n",
       "      <td>0.119217</td>\n",
       "      <td>0.004272</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.042090</td>\n",
       "      <td>0.077238</td>\n",
       "      <td>0.116001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.006095</td>\n",
       "      <td>0.042958</td>\n",
       "      <td>0.004916</td>\n",
       "      <td>0.019638</td>\n",
       "      <td>0.005816</td>\n",
       "      <td>0.000319</td>\n",
       "      <td>0.008383</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>0.041175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004344</td>\n",
       "      <td>0.083787</td>\n",
       "      <td>0.107747</td>\n",
       "      <td>0.038953</td>\n",
       "      <td>0.017185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id     ARSON   ASSAULT  BAD CHECKS   BRIBERY  BURGLARY  DISORDERLY CONDUCT  \\\n",
       "0   0  0.003107  0.144157    0.000240  0.001706  0.030331            0.002546   \n",
       "1   1  0.000842  0.073329    0.000000  0.000117  0.000740            0.001878   \n",
       "2   2  0.001961  0.061367    0.000601  0.000150  0.134061            0.001181   \n",
       "3   3  0.001676  0.136586    0.000312  0.000463  0.037153            0.004208   \n",
       "4   4  0.001676  0.136586    0.000312  0.000463  0.037153            0.004208   \n",
       "\n",
       "   DRIVING UNDER THE INFLUENCE  DRUG/NARCOTIC  DRUNKENNESS  EMBEZZLEMENT  \\\n",
       "0                     0.003918       0.017006     0.004563      0.002051   \n",
       "1                     0.006253       0.087575     0.002095      0.000397   \n",
       "2                     0.001502       0.011651     0.003122      0.000806   \n",
       "3                     0.002448       0.043413     0.004985      0.000453   \n",
       "4                     0.002448       0.043413     0.004985      0.000453   \n",
       "\n",
       "   EXTORTION  FAMILY OFFENSES  FORGERY/COUNTERFEITING     FRAUD  GAMBLING  \\\n",
       "0   0.000132         0.001660                0.006222  0.016794  0.000012   \n",
       "1   0.000000         0.000039                0.004584  0.003500  0.001513   \n",
       "2   0.000210         0.000097                0.009051  0.015790  0.000221   \n",
       "3   0.000415         0.001078                0.009510  0.010549  0.000770   \n",
       "4   0.000415         0.001078                0.009510  0.010549  0.000770   \n",
       "\n",
       "   KIDNAPPING  LARCENY/THEFT  LIQUOR LAWS  LOITERING  MISSING PERSON  \\\n",
       "0    0.003389       0.118949     0.000419   0.000050        0.054715   \n",
       "1    0.001294       0.046992     0.003739   0.000405        0.005207   \n",
       "2    0.002461       0.325578     0.000776   0.000158        0.016525   \n",
       "3    0.004686       0.119217     0.004272   0.000236        0.042090   \n",
       "4    0.004686       0.119217     0.004272   0.000236        0.042090   \n",
       "\n",
       "   NON-CRIMINAL  OTHER OFFENSES  PORNOGRAPHY/OBSCENE MAT  PROSTITUTION  \\\n",
       "0      0.083569        0.090857                 0.000000      0.000104   \n",
       "1      0.048157        0.427854                 0.000000      0.000027   \n",
       "2      0.085564        0.058313                 0.000002      0.004047   \n",
       "3      0.077238        0.116001                 0.000000      0.000336   \n",
       "4      0.077238        0.116001                 0.000000      0.000336   \n",
       "\n",
       "   RECOVERED VEHICLE   ROBBERY   RUNAWAY  SECONDARY CODES  \\\n",
       "0           0.007242  0.034805  0.004955         0.022612   \n",
       "1           0.001750  0.047212  0.000007         0.008198   \n",
       "2           0.002307  0.012616  0.000163         0.010519   \n",
       "3           0.006095  0.042958  0.004916         0.019638   \n",
       "4           0.006095  0.042958  0.004916         0.019638   \n",
       "\n",
       "   SEX OFFENSES FORCIBLE  SEX OFFENSES NON FORCIBLE  STOLEN PROPERTY  \\\n",
       "0               0.005478                   0.001134         0.003702   \n",
       "1               0.002711                   0.000000         0.003141   \n",
       "2               0.004212                   0.000009         0.006079   \n",
       "3               0.005816                   0.000319         0.008383   \n",
       "4               0.005816                   0.000319         0.008383   \n",
       "\n",
       "    SUICIDE  SUSPICIOUS OCC      TREA  TRESPASS  VANDALISM  VEHICLE THEFT  \\\n",
       "0  0.001129        0.063798  0.000004  0.007423   0.085186       0.134364   \n",
       "1  0.000000        0.032183  0.000000  0.000603   0.022824       0.056735   \n",
       "2  0.000213        0.033189  0.000000  0.009406   0.070182       0.097074   \n",
       "3  0.000588        0.041175  0.000000  0.004344   0.083787       0.107747   \n",
       "4  0.000588        0.041175  0.000000  0.004344   0.083787       0.107747   \n",
       "\n",
       "   WARRANTS  WEAPON LAWS  \n",
       "0  0.024847     0.016825  \n",
       "1  0.084867     0.023232  \n",
       "2  0.015747     0.003091  \n",
       "3  0.038953     0.017185  \n",
       "4  0.038953     0.017185  "
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Création du CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "submission_df.to_csv(\"submission_sf_crime17.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reste à faire : \n",
    "    - tester d'obtenir de meilleurs hyperparamètres avec un grid search / random search (non fait car trop de temps de calcul)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Resultats Kaggle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://i.ibb.co/ZL87XZm/score.png\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "display(HTML('<img src=\"https://i.ibb.co/ZL87XZm/score.png\">'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}