LocationDimensionScript.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This script was created to help create the Location Dimension for our crime fact Table. In this script we:\n",
    "1. Create a dataframe of the location features from Vancouver Crime Dataset\n",
    "2. Create a dataframe from the Vancouver Census Data retrieved from Vancouver Open Data\n",
    "3. Merge these 2 dataframes\n",
    "4. Repeat step 1 for Denver\n",
    "5. Repeat step 2 for Denver Open Data\n",
    "6. Repeat step 3 for Denver\n",
    "7. Merge Vancouver and Denver Dataframes\n",
    "8. Export as CSV to be imported to SQL database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Maxwell\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:90: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "C:\\Users\\Maxwell\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:91: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "C:\\Users\\Maxwell\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:94: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "C:\\Users\\Maxwell\\Anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:6692: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=False'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass 'sort=True'.\n",
      "\n",
      "  sort=sort)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                 address averageHHIncome cityID   cityName  \\\n",
      "locationID                                                                   \n",
      "0                       9XX TERMINAL AVE           31534      1  VANCOUVER   \n",
      "1                         11XX KEEFER ST           31534      1  VANCOUVER   \n",
      "2                         11XX KEEFER ST           31534      1  VANCOUVER   \n",
      "3                         11XX KEEFER ST           31534      1  VANCOUVER   \n",
      "4                        11XX WILLIAM ST           31534      1  VANCOUVER   \n",
      "5                          11XX GRANT ST           31534      1  VANCOUVER   \n",
      "6                       11XX E PENDER ST           31534      1  VANCOUVER   \n",
      "7                       11XX E PENDER ST           31534      1  VANCOUVER   \n",
      "8                       11XX E PENDER ST           31534      1  VANCOUVER   \n",
      "9                     11XX E HASTINGS ST           31534      1  VANCOUVER   \n",
      "10                    11XX E HASTINGS ST           31534      1  VANCOUVER   \n",
      "11                    11XX E HASTINGS ST           31534      1  VANCOUVER   \n",
      "12                     11XX E GEORGIA ST           31534      1  VANCOUVER   \n",
      "13                        11XX E 6TH AVE           31534      1  VANCOUVER   \n",
      "14                     10XX E CORDOVA ST           31534      1  VANCOUVER   \n",
      "15                     10XX E CORDOVA ST           31534      1  VANCOUVER   \n",
      "16                     10XX E GEORGIA ST           31534      1  VANCOUVER   \n",
      "17            TERMINAL AVE / COTTRELL ST           31534      1  VANCOUVER   \n",
      "18                TERMINAL AVE / BEGG ST           31534      1  VANCOUVER   \n",
      "19                PRIOR ST / HEATLEY AVE           31534      1  VANCOUVER   \n",
      "20          PRINCESS AVE / E HASTINGS ST           31534      1  VANCOUVER   \n",
      "21                          10XX MAIN ST           31534      1  VANCOUVER   \n",
      "22                MAIN ST / TERMINAL AVE           31534      1  VANCOUVER   \n",
      "23                        10XX PARKER ST           31534      1  VANCOUVER   \n",
      "24               KEEFER ST / HEATLEY AVE           31534      1  VANCOUVER   \n",
      "25                   GORE AVE / PRIOR ST           31534      1  VANCOUVER   \n",
      "26              GORE AVE / E HASTINGS ST           31534      1  VANCOUVER   \n",
      "27           E HASTINGS ST / JACKSON AVE           31534      1  VANCOUVER   \n",
      "28              E HASTINGS ST / GORE AVE           31534      1  VANCOUVER   \n",
      "29              E HASTINGS ST / CLARK DR           31534      1  VANCOUVER   \n",
      "...                                  ...             ...    ...        ...   \n",
      "235980               8095 E COLORADO AVE           62026      2     DENVER   \n",
      "235981               7955 E COLORADO AVE           62026      2     DENVER   \n",
      "235982                         NOT GIVEN           62026      2     DENVER   \n",
      "235983             1600 BLK S TRENTON ST           62026      2     DENVER   \n",
      "235984                         NOT GIVEN           62026      2     DENVER   \n",
      "235985             1700 BLK S QUEBEC WAY           62026      2     DENVER   \n",
      "235986                  1433 S ULSTER ST           62026      2     DENVER   \n",
      "235987                 1792 S TRENTON ST           62026      2     DENVER   \n",
      "235988                 1600 S QUEBEC WAY           62026      2     DENVER   \n",
      "235989          7700 E CHERRY CREEK S DR           62026      2     DENVER   \n",
      "235990               7900 BLK E IOWA AVE           62026      2     DENVER   \n",
      "235991             1600 BLK S TRENTON ST           62026      2     DENVER   \n",
      "235992                  1351 S ULSTER ST           62026      2     DENVER   \n",
      "235993                         NOT GIVEN           62026      2     DENVER   \n",
      "235994                1636 S ROSEMARY ST           62026      2     DENVER   \n",
      "235995                 7850 E JEWELL AVE           62026      2     DENVER   \n",
      "235996                         NOT GIVEN           62026      2     DENVER   \n",
      "235997              1800 BLK S ULSTER ST           62026      2     DENVER   \n",
      "235998            7300 BLK E FLORIDA AVE           62026      2     DENVER   \n",
      "235999                         NOT GIVEN           62026      2     DENVER   \n",
      "236000                  1471 S ULSTER ST           62026      2     DENVER   \n",
      "236001          1900 BLOCK S ROSEMARY ST           62026      2     DENVER   \n",
      "236002          7400 BLOCK E FLORIDA AVE           62026      2     DENVER   \n",
      "236003                  1491 S ULSTER ST           62026      2     DENVER   \n",
      "236004                  1944 S QUEBEC ST           62026      2     DENVER   \n",
      "236005              1900 BLK S QUINCE ST           62026      2     DENVER   \n",
      "236006                 1732 S TRENTON ST           62026      2     DENVER   \n",
      "236007       S TRENTON ST / E MEXICO AVE           62026      2     DENVER   \n",
      "236008                  1447 S ULSTER ST           62026      2     DENVER   \n",
      "236009             1400 BLK S QUEBEC WAY           62026      2     DENVER   \n",
      "\n",
      "           latitude longitude neighbourhood population  povertyRate  \\\n",
      "locationID                                                            \n",
      "0           49.2698  -123.084    Strathcona      12585          0.0   \n",
      "1           49.2792  -123.081    Strathcona      12585          0.0   \n",
      "2           49.2791  -123.081    Strathcona      12585          0.0   \n",
      "3           49.2791  -123.081    Strathcona      12585          0.0   \n",
      "4            49.274   -123.08    Strathcona      12585          0.0   \n",
      "5           49.2715  -123.079    Strathcona      12585          0.0   \n",
      "6             49.28   -123.08    Strathcona      12585          0.0   \n",
      "7             49.28   -123.08    Strathcona      12585          0.0   \n",
      "8             49.28  -123.081    Strathcona      12585          0.0   \n",
      "9           49.2811  -123.079    Strathcona      12585          0.0   \n",
      "10          49.2809  -123.081    Strathcona      12585          0.0   \n",
      "11          49.2809  -123.081    Strathcona      12585          0.0   \n",
      "12          49.2782  -123.081    Strathcona      12585          0.0   \n",
      "13          49.2653   -123.08    Strathcona      12585          0.0   \n",
      "14          49.2819  -123.082    Strathcona      12585          0.0   \n",
      "15           49.282  -123.081    Strathcona      12585          0.0   \n",
      "16          49.2782  -123.081    Strathcona      12585          0.0   \n",
      "17          49.2699  -123.084    Strathcona      12585          0.0   \n",
      "18          49.2707  -123.087    Strathcona      12585          0.0   \n",
      "19          49.2766   -123.09    Strathcona      12585          0.0   \n",
      "20          49.2812  -123.091    Strathcona      12585          0.0   \n",
      "21          49.2755    -123.1    Strathcona      12585          0.0   \n",
      "22          49.2727    -123.1    Strathcona      12585          0.0   \n",
      "23          49.2759  -123.081    Strathcona      12585          0.0   \n",
      "24          49.2793   -123.09    Strathcona      12585          0.0   \n",
      "25          49.2767  -123.097    Strathcona      12585          0.0   \n",
      "26          49.2813  -123.097    Strathcona      12585          0.0   \n",
      "27          49.2812  -123.093    Strathcona      12585          0.0   \n",
      "28          49.2813  -123.097    Strathcona      12585          0.0   \n",
      "29          49.2813  -123.077    Strathcona      12585          0.0   \n",
      "...             ...       ...           ...        ...          ...   \n",
      "235980      39.6839  -104.895  indian-creek       3799          7.2   \n",
      "235981      39.6839  -104.896  indian-creek       3799          7.2   \n",
      "235982      39.6827   -104.89  indian-creek       3799          7.2   \n",
      "235983      39.6859  -104.897  indian-creek       3799          7.2   \n",
      "235984      39.6893  -104.903  indian-creek       3799          7.2   \n",
      "235985      39.6848  -104.894  indian-creek       3799          7.2   \n",
      "235986      39.6904  -104.894  indian-creek       3799          7.2   \n",
      "235987      39.6841  -104.896  indian-creek       3799          7.2   \n",
      "235988      39.6874  -104.895  indian-creek       3799          7.2   \n",
      "235989      39.6809  -104.899  indian-creek       3799          7.2   \n",
      "235990      39.6867  -104.897  indian-creek       3799          7.2   \n",
      "235991      39.6849  -104.897  indian-creek       3799          7.2   \n",
      "235992      39.6895  -104.894  indian-creek       3799          7.2   \n",
      "235993      39.6856  -104.897  indian-creek       3799          7.2   \n",
      "235994       39.686    -104.9  indian-creek       3799          7.2   \n",
      "235995      39.6822  -104.897  indian-creek       3799          7.2   \n",
      "235996      39.6826  -104.897  indian-creek       3799          7.2   \n",
      "235997      39.6826  -104.894  indian-creek       3799          7.2   \n",
      "235998      39.6889  -104.902  indian-creek       3799          7.2   \n",
      "235999      39.6826  -104.894  indian-creek       3799          7.2   \n",
      "236000      39.6906  -104.895  indian-creek       3799          7.2   \n",
      "236001      39.6813    -104.9  indian-creek       3799          7.2   \n",
      "236002      39.6893  -104.902  indian-creek       3799          7.2   \n",
      "236003      39.6898  -104.895  indian-creek       3799          7.2   \n",
      "236004      39.6816  -104.903  indian-creek       3799          7.2   \n",
      "236005      39.6817  -104.902  indian-creek       3799          7.2   \n",
      "236006       39.685  -104.896  indian-creek       3799          7.2   \n",
      "236007      39.6856  -104.897  indian-creek       3799          7.2   \n",
      "236008      39.6899  -104.894  indian-creek       3799          7.2   \n",
      "236009      39.6898  -104.897  indian-creek       3799          7.2   \n",
      "\n",
      "           unemploymentRate           x           y  \n",
      "locationID                                           \n",
      "0                       8.5   493906.50  5457452.47  \n",
      "1                       8.5   494091.91  5458493.10  \n",
      "2                       8.5   494091.89  5458483.95  \n",
      "3                       8.5   494134.16  5458483.87  \n",
      "4                       8.5   494179.16  5457922.63  \n",
      "5                       8.5   494251.27  5457645.92  \n",
      "6                       8.5   494172.53  5458584.98  \n",
      "7                       8.5   494158.36  5458585.35  \n",
      "8                       8.5   494093.19  5458587.06  \n",
      "9                       8.5   494228.28  5458709.95  \n",
      "10                      8.5   494141.12  5458690.14  \n",
      "11                      8.5   494094.70  5458689.13  \n",
      "12                      8.5   494090.41  5458385.80  \n",
      "13                      8.5   494160.48  5456947.17  \n",
      "14                      8.5   494033.14  5458795.62  \n",
      "15                      8.5   494073.88  5458803.74  \n",
      "16                      8.5   494077.84  5458386.10  \n",
      "17                      8.5   493898.00  5457459.00  \n",
      "18                      8.5   493640.00  5457556.00  \n",
      "19                      8.5   493472.00  5458207.00  \n",
      "20                      8.5   493347.00  5458719.00  \n",
      "21                      8.5   492743.24  5458089.61  \n",
      "22                      8.5   492730.00  5457781.00  \n",
      "23                      8.5   494084.11  5458126.65  \n",
      "24                      8.5   493482.00  5458509.00  \n",
      "25                      8.5   492953.00  5458221.00  \n",
      "26                      8.5   492911.00  5458733.00  \n",
      "27                      8.5   493205.00  5458724.00  \n",
      "28                      8.5   492911.00  5458733.00  \n",
      "29                      8.5   494392.00  5458735.00  \n",
      "...                     ...         ...         ...  \n",
      "235980                    0  3170342.00  1674567.00  \n",
      "235981                    0  3170057.00  1674552.00  \n",
      "235982                    0  3171566.00  1674118.00  \n",
      "235983                    0  3169812.00  1675265.00  \n",
      "235984                    0  3168023.00  1676503.00  \n",
      "235985                    0  3170545.00  1674869.00  \n",
      "235986                    0  3170449.00  1676930.00  \n",
      "235987                    0  3169942.00  1674645.00  \n",
      "235988                    0  3170351.00  1675834.00  \n",
      "235989                    0  3169147.00  1673473.00  \n",
      "235990                    0  3169746.00  1675591.00  \n",
      "235991                    0  3169752.00  1674903.00  \n",
      "235992                    0  3170454.00  1676585.00  \n",
      "235993                    0  3169732.00  1675189.00  \n",
      "235994                    0  3168960.00  1675308.00  \n",
      "235995                    0  3169855.00  1673940.00  \n",
      "235996                    0  3169633.00  1674095.00  \n",
      "235997                    0  3170491.00  1674079.00  \n",
      "235998                    0  3168225.00  1676382.00  \n",
      "235999                    0  3170587.00  1674082.00  \n",
      "236000                    0  3170233.00  1677004.00  \n",
      "236001                    0  3168800.00  1673592.00  \n",
      "236002                    0  3168370.00  1676504.00  \n",
      "236003                    0  3170346.00  1676715.00  \n",
      "236004                    0  3168021.00  1673705.00  \n",
      "236005                    0  3168332.00  1673734.00  \n",
      "236006                    0  3169865.00  1674965.00  \n",
      "236007                    0  3169732.00  1675189.00  \n",
      "236008                    0  3170456.00  1676732.00  \n",
      "236009                    0  3169592.00  1676715.00  \n",
      "\n",
      "[236010 rows x 12 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "#Vancouver Data\n",
    "#Vancouver\n",
    "van = pd.read_csv(\"crimeVan.csv\", encoding=\"UTF-8\")\n",
    "row_count = len(van)\n",
    "\n",
    "cityID_col = np.full(row_count,'1')\n",
    "cityName_col = np.full(row_count,'VANCOUVER')\n",
    "address_col = van[\"HUNDRED_BLOCK\"]\n",
    "neighbourhood_col = van[\"NEIGHBOURHOOD\"]\n",
    "latitude_col = van[\"Latitude\"]\n",
    "longitude_col = van[\"Longitude\"]\n",
    "x_col = van[\"X\"]\n",
    "y_col = van[\"Y\"]\n",
    "#You fill\n",
    "pop_col = np.full(row_count,'0')\n",
    "averageHH_col = np.full(row_count,'0')\n",
    "unemployment_col = np.full(row_count,'NOT GIVEN')\n",
    "#null\n",
    "poverty_col = np.full(row_count,'NOT GIVEN')\n",
    "\n",
    "dfvan = pd.DataFrame({'cityID':cityID_col, 'cityName':cityName_col, \n",
    "                          'address':address_col, 'neighbourhood':neighbourhood_col, 'latitude':latitude_col,\n",
    "                         'longitude':longitude_col,'x':x_col,'y':y_col,'neighbourhood':neighbourhood_col,\n",
    "                      'povertyRate':poverty_col})\n",
    "\n",
    "dfvan = dfvan.drop_duplicates()\n",
    "dfvan = dfvan.fillna('NOT GIVEN')\n",
    "dfvan[\"address\"] = dfvan[\"address\"].replace(to_replace='OFFSET TO PROTECT PRIVACY',\n",
    "                                                  value=\"NOT GIVEN\")\n",
    "\n",
    "#Vancouver Census Data\n",
    "cols=[0,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25]\n",
    "vanCensus = pd.read_csv(\"CensusLocalAreaProfiles2016.csv\",encoding=\"latin1\")\n",
    "\n",
    "rows=[' Total - Age groups and average age of the population - 100% data ','Employment rate',\n",
    "      'Unemployment rate','    Average total income in 2015 among recipients ($)','  Average monthly shelter costs for owned dwellings ($)']\n",
    "vanCen=vanCensus[vanCensus['Variable'].isin(rows)]\n",
    "\n",
    "nh = list(vanCen.columns.values)\n",
    "nh = nh[2:]\n",
    "header = vanCen['Variable'].tolist()\n",
    "\n",
    "values = vanCen.values.tolist()\n",
    "rows=[]\n",
    "for row in values:\n",
    "    rows.append(row[2:])\n",
    "    \n",
    "for i in range(len(nh)):\n",
    "    nh[i]=nh[i][:-1]\n",
    "nh[0]= \"Arbutus Ridge\"\n",
    "nh[1]= \"Central Business District\"\n",
    "nh[19]= \"Victoria-Fraserview\"\n",
    "\n",
    "nh = nh[:-2]\n",
    "rows[0]=rows[0][:-2]\n",
    "rows[1]=rows[1][:-2]\n",
    "rows[3]=rows[3][:-2]\n",
    "\n",
    "nh.append('Musqueam')\n",
    "rows[0].append('0')\n",
    "rows[1].append('0')\n",
    "rows[3].append('0')\n",
    "\n",
    "nh.append('Stanley Park')\n",
    "rows[0].append('0')\n",
    "rows[1].append('0')\n",
    "rows[3].append('0')\n",
    "\n",
    "nh.append('NOT GIVEN')\n",
    "rows[0].append('0')\n",
    "rows[1].append('0')\n",
    "rows[3].append('0')\n",
    "    \n",
    "df = pd.DataFrame({'neighbourhood':nh,'population':rows[0],'averageHHIncome':rows[1],\n",
    "                   'unemploymentRate':rows[3]})\n",
    "for i in range(len(df[\"population\"])):\n",
    "    if (type(df[\"population\"][i]) is str):\n",
    "        df[\"population\"][i] = int(df[\"population\"][i].replace(',',''))\n",
    "\n",
    "#Merge Vancouver with Census\n",
    "dfvan = pd.merge(dfvan, df, on='neighbourhood')\n",
    "\n",
    "#Denver Data\n",
    "d_nhbd = pd.read_csv('denver_nbrhd_2013_2017.csv')\n",
    "den = pd.read_csv(\"crimeDen.csv\", encoding=\"UTF-8\")\n",
    "\n",
    "for i in range(len(d_nhbd)):\n",
    "    d_nhbd['NBHD_NAME'][i] = d_nhbd['NBHD_NAME'][i].replace(' ', '-')\n",
    "    d_nhbd['NBHD_NAME'][i] = d_nhbd['NBHD_NAME'][i].lower()\n",
    "    \n",
    "for i in range(len(d_nhbd)):\n",
    "    d_nhbd['NBHD_NAME'][i] = d_nhbd['NBHD_NAME'][i].replace('---', '-')\n",
    "    \n",
    "nbhd_final = d_nhbd[['NBHD_NAME', 'TTL_POPULATION_ALL', 'AVG_HH_INCOME', 'PCT_POVERTY']].sort_index()   \n",
    "\n",
    "row_count = len(den)\n",
    "\n",
    "cityID_col = np.full(row_count,'2')\n",
    "cityName_col = np.full(row_count,'DENVER')\n",
    "address_col = den[\"INCIDENT_ADDRESS\"]\n",
    "latitude_col = den[\"GEO_LAT\"]\n",
    "longitude_col = den[\"GEO_LON\"]\n",
    "neighbourhood_col = den[\"NEIGHBORHOOD_ID\"]\n",
    "x_col = den[\"GEO_X\"]\n",
    "y_col = den[\"GEO_Y\"]\n",
    "pop_col = np.full(row_count,'0')\n",
    "averageHH_col = np.full(row_count,'0')\n",
    "poverty_col = np.full(row_count,'0')\n",
    "\n",
    "unemployment_col = np.full(row_count,'0')\n",
    "nbhd_final.columns = ['neighbourhood', 'population', 'averageHHIncome', 'povertyRate']\n",
    "dfden = pd.DataFrame({'cityID':cityID_col, 'cityName':cityName_col, \n",
    "                          'address':address_col, 'latitude':latitude_col,\n",
    "                         'longitude':longitude_col,'x':x_col,'y':y_col,'neighbourhood':neighbourhood_col,\n",
    "                      'unemploymentRate':unemployment_col})\n",
    "\n",
    "dfden = dfden.drop_duplicates()\n",
    "dfden[\"address\"] = dfden[\"address\"].fillna('NOT GIVEN')\n",
    "dfden[\"neighbourhood\"] = dfden[\"neighbourhood\"].fillna('NOT GIVEN')\n",
    "dfden[\"latitude\"] = dfden[\"latitude\"].fillna('0')\n",
    "dfden[\"longitude\"] = dfden[\"longitude\"].fillna('0')\n",
    "for i in range(len(nbhd_final[\"population\"])):\n",
    "    if (type(nbhd_final[\"population\"][i]) is str):\n",
    "        nbhd_final[\"population\"][i] = int(nbhd_final[\"population\"][i].replace(',',''))\n",
    "dfden = pd.merge(dfden, nbhd_final, on='neighbourhood')\n",
    "\n",
    "#Merge Vancouver and Denver Dataframes\n",
    "dfVanDen = dfvan.append(dfden)\n",
    "dfVanDen = dfVanDen.reset_index(drop=True)\n",
    "dfVanDen.index.names =['locationID']\n",
    "\n",
    "#Clean data w.r.t SQL constrstraints\n",
    "dfVanDen[\"averageHHIncome\"] = dfVanDen[\"averageHHIncome\"].replace(to_replace='None',\n",
    "                                                  value=0)\n",
    "dfVanDen[\"povertyRate\"] = dfVanDen[\"povertyRate\"].replace(to_replace='NOT GIVEN',\n",
    "                                                  value=0)\n",
    "dfVanDen[\"x\"] = dfVanDen[\"x\"].fillna(0)\n",
    "dfVanDen[\"y\"] = dfVanDen[\"y\"].fillna(0)\n",
    "\n",
    "dfVanDen.to_csv('LocationDimension.csv', header=True, encoding='utf-8')\n",
    "print(dfVanDen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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