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@dcasmr
Created November 12, 2018 07:27
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Creating a stacked area plot using Python seaborn library
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data source. [Uniform Crime reporting statistics:](https://www.ucrdatatool.gov/Search/Crime/State/StatebyState.cfm) <br> Violent crime in Washington DC"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"df = pd.read_csv(\"WashingtonDCCrime.csv\",encoding ='latin-1')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>Crime</th>\n",
" <th>Rate</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2005</td>\n",
" <td>Murder</td>\n",
" <td>33.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2006</td>\n",
" <td>Murder</td>\n",
" <td>29.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2007</td>\n",
" <td>Murder</td>\n",
" <td>30.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2008</td>\n",
" <td>Murder</td>\n",
" <td>31.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2009</td>\n",
" <td>Murder</td>\n",
" <td>24.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year Crime Rate\n",
"0 2005 Murder 33.5\n",
"1 2006 Murder 29.1\n",
"2 2007 Murder 30.8\n",
"3 2008 Murder 31.4\n",
"4 2009 Murder 24.2"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"Summary = pd.crosstab(df['Year'], df['Crime'], values=df['Rate'], aggfunc=np.sum)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
"<style>\n",
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"\n",
" .dataframe tbody tr th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>Crime</th>\n",
" <th>Aggravated Assault</th>\n",
" <th>Murder</th>\n",
" <th>Rape</th>\n",
" <th>Robery</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Year</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2005</th>\n",
" <td>682.2</td>\n",
" <td>33.5</td>\n",
" <td>28.5</td>\n",
" <td>635.7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006</th>\n",
" <td>789.1</td>\n",
" <td>29.1</td>\n",
" <td>31.8</td>\n",
" <td>658.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2007</th>\n",
" <td>626.7</td>\n",
" <td>30.8</td>\n",
" <td>32.6</td>\n",
" <td>725.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2008</th>\n",
" <td>626.4</td>\n",
" <td>31.4</td>\n",
" <td>31.4</td>\n",
" <td>748.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2009</th>\n",
" <td>565.3</td>\n",
" <td>24.2</td>\n",
" <td>25.0</td>\n",
" <td>734.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010</th>\n",
" <td>559.1</td>\n",
" <td>21.8</td>\n",
" <td>30.9</td>\n",
" <td>715.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>494.0</td>\n",
" <td>17.4</td>\n",
" <td>27.9</td>\n",
" <td>661.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>553.3</td>\n",
" <td>13.9</td>\n",
" <td>37.3</td>\n",
" <td>637.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>590.8</td>\n",
" <td>15.9</td>\n",
" <td>45.8</td>\n",
" <td>628.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>626.1</td>\n",
" <td>15.9</td>\n",
" <td>53.4</td>\n",
" <td>530.7</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Crime Aggravated Assault Murder Rape Robery\n",
"Year \n",
"2005 682.2 33.5 28.5 635.7\n",
"2006 789.1 29.1 31.8 658.4\n",
"2007 626.7 30.8 32.6 725.0\n",
"2008 626.4 31.4 31.4 748.5\n",
"2009 565.3 24.2 25.0 734.4\n",
"2010 559.1 21.8 30.9 715.0\n",
"2011 494.0 17.4 27.9 661.4\n",
"2012 553.3 13.9 37.3 637.3\n",
"2013 590.8 15.9 45.8 628.9\n",
"2014 626.1 15.9 53.4 530.7"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Summary"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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inHs1y8+yoNxL+DkG1z2/4KJyQh7Hrw5+ZybFhUxF8jj+HC7oIc41oWN1Zmz7nwUcB9ZP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CmgDhERERE5R5k6iTSzVkBH4FnfqoQ7Ux9OVPRQou1RyZRJKBeVzPrk2h5pZs7M3InDyQ2QioiI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\niIiISMiURIqIiIhIyP4PwmZNJSFyGiUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a9363ce1d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams[\"figure.figsize\"] = [10,8]\n",
"sns.set_context(\"notebook\", font_scale=1.5, rc={\"font.size\":14,\"axes.titlesize\":16,\"axes.labelsize\":12})\n",
"Summary.plot(kind=\"area\",stacked=True)\n",
"plt.title(\"Stacked area plot of Washington DC violent crime data\")\n",
"plt.ylabel(\"Crime Rate per 100000s\")\n",
"plt.xlabel(\"Year reported\")\n",
"plt.savefig('stacked_area.png', dpi=1200)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"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
}
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