diff --git a/index.html b/index.html new file mode 100644 index 0000000..ae2dbba --- /dev/null +++ b/index.html @@ -0,0 +1,460 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##
Python Geospatial Data Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Import Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import folium\n", + "import math\n", + "from folium.plugins import MarkerCluster,HeatMap\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Import Data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " INCIDENT_NUMBER OFFENSE_CODE OFFENSE_CODE_GROUP \\\n", + "0 I192082859 724 Auto Theft \n", + "1 I192082751 724 Auto Theft \n", + "2 I192082680 727 Auto Theft \n", + "\n", + " OFFENSE_DESCRIPTION DISTRICT REPORTING_AREA SHOOTING \\\n", + "0 AUTO THEFT E18 519 NaN \n", + "1 AUTO THEFT E18 493 NaN \n", + "2 AUTO THEFT - LEASED/RENTED VEHICLE D14 794 NaN \n", + "\n", + " OCCURRED_ON_DATE YEAR MONTH DAY_OF_WEEK HOUR UCR_PART \\\n", + "0 2019-10-13 09:28:24 2019 10 Sunday 9 Part One \n", + "1 2019-10-12 20:11:26 2019 10 Saturday 20 Part One \n", + "2 2019-10-12 15:12:43 2019 10 Saturday 15 Part One \n", + "\n", + " STREET Lat Long Location \\\n", + "0 LINCOLN ST 42.259518 -71.121563 (42.25951765, -71.12156299) \n", + "1 METROPOLITAN AVE 42.262092 -71.116710 (42.26209214, -71.11670964) \n", + "2 ALLSTON ST 42.352375 -71.135096 (42.35237455, -71.13509584) \n", + "\n", + " Date Time \n", + "0 2019-10-13 09:28:24 \n", + "1 2019-10-12 20:11:26 \n", + "2 2019-10-12 15:12:43 " + ], + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
INCIDENT_NUMBEROFFENSE_CODEOFFENSE_CODE_GROUPOFFENSE_DESCRIPTIONDISTRICTREPORTING_AREASHOOTINGOCCURRED_ON_DATEYEARMONTHDAY_OF_WEEKHOURUCR_PARTSTREETLatLongLocationDateTime
0I192082859724Auto TheftAUTO THEFTE18519NaN2019-10-13 09:28:24201910Sunday9Part OneLINCOLN ST42.259518-71.121563(42.25951765, -71.12156299)2019-10-1309:28:24
1I192082751724Auto TheftAUTO THEFTE18493NaN2019-10-12 20:11:26201910Saturday20Part OneMETROPOLITAN AVE42.262092-71.116710(42.26209214, -71.11670964)2019-10-1220:11:26
2I192082680727Auto TheftAUTO THEFT - LEASED/RENTED VEHICLED14794NaN2019-10-12 15:12:43201910Saturday15Part OneALLSTON ST42.352375-71.135096(42.35237455, -71.13509584)2019-10-1215:12:43
\n
" + }, + "metadata": {}, + "execution_count": 3 + } + ], + "source": [ + "df=pd.read_csv('https://raw.githubusercontent.com/VinitaSilaparasetty/coursera-spatial-data-analysis/master/boston-crime%202.csv')\n", + "df.head(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate Base Map" + ] + }, + { + "source": [ + "A BASE MAP OF BOSTON AREA" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "boston= (42.358443, -71.05977)\n", + "m=folium.Map(location=boston,title='Stamen terrain',zoom_start=12)\n", + "m" + ], + "cell_type": "code", + "metadata": {}, + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 10 + } + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Mark Crime Scenes" + ] + }, + { + "source": [ + "A MAP SHOWING DISTRICTS WITH THE HIGHEST CRIME RATES" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 20 + } + ], + "source": [ + "mc= MarkerCluster()\n", + "for idx,row in df.iterrows():\n", + " if not math.isnan(row['Long']) and not math.isnan(row['Lat']):\n", + " mc.add_child(folium.Marker([row['Lat'],row['Long']]))\n", + "m.add_child(mc)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### View Districts with Highest Crime Rates" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "crime=df.groupby(['DISTRICT','STREET','REPORTING_AREA','Lat','Long']).sum().reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "crime.update(crime['DISTRICT'].map('District:{}'.format))\n", + "crime.update(crime['REPORTING_AREA'].map('Reports:{}'.format))\n" + ] + }, + { + "source": [ + " HEATMAP SHOWING CRIME RATE" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 33 + } + ], + "source": [ + "m2=folium.Map(location=boston,tiles='Stamentoner',zoom_start=12)\n", + "HeatMap(data=crime[['Lat','Long']],radius=15).add_to(m2)\n", + "def plotDot(point):\n", + " folium.CircleMarker(location=[point.Lat,point.Long],\n", + " radius=5,\n", + " weight=2,\n", + " popup=[point.DISTRICT,point.REPORTING_AREA],\n", + " fill_color='#000000').add_to(m2)\n", + "crime.apply(plotDot,axis=1)\n", + "m2.fit_bounds(m2.get_bounds())\n", + "m2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Medical Assistance Analysis" + ] + }, + { + "source": [ + "A MAP SHOWING REQUIRED MEDICAL ASSISTANCE" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "C:\\Users\\Lenovo G500\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\core\\series.py:4463: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " return super().fillna(\n", + "C:\\Users\\Lenovo G500\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pandas\\core\\series.py:4463: 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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " return super().fillna(\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 37 + } + ], + "source": [ + "med=df.loc[df.OFFENSE_CODE_GROUP== 'Medical Assistance'][['Lat','Long']]\n", + "med.Lat.fillna(0,inplace=True)\n", + "med.Long.fillna(0,inplace=True)\n", + "m6=folium.Map(location=boston,tiles='openstreetmap',zoom_start=11)\n", + "HeatMap(data=med,radius=16).add_to(m6)\n", + "m6" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Crimes Commited" + ] + }, + { + "source": [ + "A BAR GRAPH SHOWING COMMITTED CRIMES" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 46 + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n" + }, + "metadata": { + "needs_background": "light" + } + } + ], + "source": [ + "sns.catplot(y='OFFENSE_CODE_GROUP',\n", + "kind='count',\n", + "height=8,\n", + "aspect=1.5,\n", + "order=df.OFFENSE_CODE_GROUP.value_counts().index,\n", + "data=df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Motor Vehicle Accident Response" + ] + }, + { + "source": [ + "OPENSTREETMAP SHOWING POSSIBLE CAUSES OF MOTOR VEHICLE ACCIDENTS" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 47 + } + ], + "source": [ + "mv=df.loc[df.OFFENSE_CODE_GROUP=='Motor Vehicle Accident Response'][['Lat','Long']]\n", + "mv.fillna(0,inplace=True)\n", + "mv.Lat.fillna(0,inplace=True)\n", + "mv.Long.fillna(0,inplace=True)\n", + "m4=folium.Map(location=boston,tiles='openstreetmap',zoom_start=11)\n", + "HeatMap(data=mv,radius=16).add_to(m4)\n", + "m4" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Larceny" + ] + }, + { + "source": [ + "OPENSTREETMAP SHOWING POSSIBLE CAUSES OF LARCENCY" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ], + "text/html": "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + }, + "metadata": {}, + "execution_count": 48 + } + ], + "source": [ + "lar=df.loc[df.OFFENSE_CODE_GROUP=='Larcency'][['Lat','Long']]\n", + "lar.Lat.fillna(0,inplace=True)\n", + "lar.Long.fillna(0,inplace=True)\n", + "m5=folium.Map(location=boston,tiles='openstreetmap',zoom_start=11)\n", + "HeatMap(data=lar,radius=16).add_to(m5)\n", + "m5" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "name": "python3", + "display_name": "Python 3.9.2 64-bit", + "metadata": { + "interpreter": { + "hash": "0f3950ccbf038c7b7e44d1291b37cf5b5e353bd747310665b8476becee64f219" + } + } + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.2-final" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file