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.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"scrolled": true
},
"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>city</th>\n",
" <th>driver_count</th>\n",
" <th>type</th>\n",
" <th>date</th>\n",
" <th>fare</th>\n",
" <th>ride_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Richardfort</td>\n",
" <td>38</td>\n",
" <td>Urban</td>\n",
" <td>2018-02-24 08:40:38</td>\n",
" <td>13.93</td>\n",
" <td>5628545007794</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Richardfort</td>\n",
" <td>38</td>\n",
" <td>Urban</td>\n",
" <td>2018-02-13 12:46:07</td>\n",
" <td>14.00</td>\n",
" <td>910050116494</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Richardfort</td>\n",
" <td>38</td>\n",
" <td>Urban</td>\n",
" <td>2018-02-16 13:52:19</td>\n",
" <td>17.92</td>\n",
" <td>820639054416</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Richardfort</td>\n",
" <td>38</td>\n",
" <td>Urban</td>\n",
" <td>2018-02-01 20:18:28</td>\n",
" <td>10.26</td>\n",
" <td>9554935945413</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Richardfort</td>\n",
" <td>38</td>\n",
" <td>Urban</td>\n",
" <td>2018-04-17 02:26:37</td>\n",
" <td>23.00</td>\n",
" <td>720020655850</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city driver_count type date fare ride_id\n",
"0 Richardfort 38 Urban 2018-02-24 08:40:38 13.93 5628545007794\n",
"1 Richardfort 38 Urban 2018-02-13 12:46:07 14.00 910050116494\n",
"2 Richardfort 38 Urban 2018-02-16 13:52:19 17.92 820639054416\n",
"3 Richardfort 38 Urban 2018-02-01 20:18:28 10.26 9554935945413\n",
"4 Richardfort 38 Urban 2018-04-17 02:26:37 23.00 720020655850"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib inline\n",
"# Dependencies and Setup\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import numpy as np\n",
"#import matplotlib.pyplot.legend as legend\n",
"import matplotlib.collections as mcol\n",
"from matplotlib.legend_handler import HandlerLineCollection, HandlerTuple\n",
"from matplotlib.lines import Line2D\n",
"\n",
"# File to Load\n",
"city_data_to_load = \"data/city_data.csv\"\n",
"ride_data_to_load = \"data/ride_data.csv\"\n",
"\n",
"# Read the City and Ride Data\n",
"city_df=pd.read_csv(city_data_to_load)\n",
"rider_df=pd.read_csv(ride_data_to_load)\n",
"\n",
"# Combine the data into a single dataset\n",
"CityRide_merge=pd.merge(city_df, rider_df, how='outer', on='city')\n",
"\n",
"# Display the data table for preview\n",
"CityRide_merge.head()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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>City Name</th>\n",
" <th>City Type</th>\n",
" <th>Driver Count</th>\n",
" <th>Avg Fare</th>\n",
" <th>Total Fare</th>\n",
" <th>Ride Count</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Richardfort</td>\n",
" <td>Urban</td>\n",
" <td>38</td>\n",
" <td>22.373214</td>\n",
" <td>626.45</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Williamsstad</td>\n",
" <td>Urban</td>\n",
" <td>59</td>\n",
" <td>24.362174</td>\n",
" <td>560.33</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Port Angela</td>\n",
" <td>Urban</td>\n",
" <td>67</td>\n",
" <td>23.836842</td>\n",
" <td>452.90</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Rodneyfort</td>\n",
" <td>Urban</td>\n",
" <td>34</td>\n",
" <td>28.616957</td>\n",
" <td>658.19</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>West Robert</td>\n",
" <td>Urban</td>\n",
" <td>39</td>\n",
" <td>25.123871</td>\n",
" <td>778.84</td>\n",
" <td>31</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" City Name City Type Driver Count Avg Fare Total Fare Ride Count\n",
"0 Richardfort Urban 38 22.373214 626.45 28\n",
"1 Williamsstad Urban 59 24.362174 560.33 23\n",
"2 Port Angela Urban 67 23.836842 452.90 19\n",
"3 Rodneyfort Urban 34 28.616957 658.19 23\n",
"4 West Robert Urban 39 25.123871 778.84 31"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#create summary by city\n",
"temp_dict_list = []\n",
"for city in CityRide_merge[\"city\"].unique():\n",
" temp_dict={\"City Name\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"city\"].max(),\n",
" \"City Type\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"type\"].max(),\n",
" \"Driver Count\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"driver_count\"].max(),\n",
" \"Avg Fare\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"fare\"].mean(), \n",
" \"Total Fare\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"fare\"].sum(),\n",
" \"Ride Count\": CityRide_merge.loc[CityRide_merge[\"city\"]==city][\"ride_id\"].count()}\n",
" temp_dict_list.append(temp_dict)\n",
"CitySummary = pd.DataFrame(temp_dict_list)\n",
"\n",
"CitySummary.head()\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"scrolled": true
},
"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>city</th>\n",
" <th>date</th>\n",
" <th>fare</th>\n",
" <th>ride_id</th>\n",
" <th>driver_count</th>\n",
" <th>type</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Lake Jonathanshire</td>\n",
" <td>2018-01-14 10:14:22</td>\n",
" <td>13.83</td>\n",
" <td>5739410935873</td>\n",
" <td>5</td>\n",
" <td>Urban</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>South Michelleport</td>\n",
" <td>2018-03-04 18:24:09</td>\n",
" <td>30.24</td>\n",
" <td>2343912425577</td>\n",
" <td>72</td>\n",
" <td>Urban</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Port Samanthamouth</td>\n",
" <td>2018-02-24 04:29:00</td>\n",
" <td>33.44</td>\n",
" <td>2005065760003</td>\n",
" <td>57</td>\n",
" <td>Urban</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Rodneyfort</td>\n",
" <td>2018-02-10 23:22:03</td>\n",
" <td>23.44</td>\n",
" <td>5149245426178</td>\n",
" <td>34</td>\n",
" <td>Urban</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>South Jack</td>\n",
" <td>2018-03-06 04:28:35</td>\n",
" <td>34.58</td>\n",
" <td>3908451377344</td>\n",
" <td>46</td>\n",
" <td>Urban</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" city date fare ride_id \\\n",
"0 Lake Jonathanshire 2018-01-14 10:14:22 13.83 5739410935873 \n",
"1 South Michelleport 2018-03-04 18:24:09 30.24 2343912425577 \n",
"2 Port Samanthamouth 2018-02-24 04:29:00 33.44 2005065760003 \n",
"3 Rodneyfort 2018-02-10 23:22:03 23.44 5149245426178 \n",
"4 South Jack 2018-03-06 04:28:35 34.58 3908451377344 \n",
"\n",
" driver_count type \n",
"0 5 Urban \n",
"1 72 Urban \n",
"2 57 Urban \n",
"3 34 Urban \n",
"4 46 Urban "
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Bubble Plot of Ride Sharing Data"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"# Obtain the x and y coordinates for each of the three city types\n",
"x_axis = CitySummary[\"Ride Count\"]\n",
"y_axis= CitySummary[\"Avg Fare\"]\n",
"size = (CitySummary[\"Driver Count\"]*10)\n",
"labels = ['Urban', 'Suburban', 'Rural']\n",
"colors = []\n",
"\n",
"for color in CitySummary[\"City Type\"]:\n",
" if color==\"Urban\":\n",
" colors.append(\"coral\")\n",
" elif color==\"Suburban\":\n",
" colors.append(\"skyblue\")\n",
" elif color==\"Rural\":\n",
" colors.append(\"gold\")\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"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": [
"# Build the scatter plots for each city types\n",
"plt.scatter(x_axis, y_axis, marker=\"o\", color=colors, label=labels, edgecolors=\"black\", s=size, alpha=0.75)\n",
"\n",
"# Incorporate the other graph properties\n",
"plt.title(\"Pyber Ride Share Data\")\n",
"plt.xlabel(\"Total Rides (Per City)\")\n",
"plt.ylabel(\"Average Fare ($)\")\n",
"plt.grid(True)\n",
"\n",
"# Create a legend\n",
"#plt.legend(labels, loc=\"best\", title=\"City Types\")\n",
"# we'll plot empty lists with the desired size and label\n",
"for area in ['Urban']:\n",
" plt.scatter([], [], c='coral', alpha=0.3, s=10, label='Urban')\n",
" \n",
"plt.legend(scatterpoints=1, frameon=True, labelspacing=0.5, title='City Types')\n",
"\n",
"# Incorporate a text label regarding circle size\n",
"plt.text(42, 33, 'Note: Circle size correlates to driver count per city.',family='serif', style='italic', \n",
" ha='left', va='center', wrap=True)\n",
"\n",
"# Save Figure\n",
"#plt.savefig(\"PyberRide.png\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"# Show plot\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Total Fares by City Type"
]
},
{
"cell_type": "code",
"execution_count": 45,
"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>Total Fare</th>\n",
" <th>Ride Count</th>\n",
" </tr>\n",
" <tr>\n",
" <th>City Type</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Rural</th>\n",
" <td>4327.93</td>\n",
" <td>125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Suburban</th>\n",
" <td>19356.33</td>\n",
" <td>625</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Urban</th>\n",
" <td>39854.38</td>\n",
" <td>1625</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Total Fare Ride Count\n",
"City Type \n",
"Rural 4327.93 125\n",
"Suburban 19356.33 625\n",
"Urban 39854.38 1625"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Calculate Type Percents\n",
"CityTypePct = CitySummary.groupby([\"City Type\"])[\"Total Fare\", \"Ride Count\"].sum()\n",
"CityTypePct.head()\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Build Pie Chart\n",
"sizes = CityTypePct[\"Total Fare\"]\n",
"explode = (0, 0, 0.15)\n",
"labels2 = [\"Rural\", \"Suburban\", \"Urban\"]\n",
"colors2 = [\"gold\", \"skyblue\", \"coral\"]\n",
"plt.pie(sizes, explode=explode, labels=labels2, colors=colors2,\n",
" autopct=\"%1.1f%%\", shadow=True, startangle=100)\n",
"\n",
"# Save Figure\n",
"plt.savefig(\"PyberTotalFares.jpeg\")\n",
"\n",
"# Show Figure\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Total Rides by City Type"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Calculate Ride Percents\n",
"\n",
"# Build Pie Chart\n",
"\n",
"# Save Figure\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Show Figure\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Total Drivers by City Type"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Calculate Driver Percents\n",
"\n",
"# Build Pie Charts\n",
"\n",
"# Save Figure\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Show Figure\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"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": "3.6.8"
},
"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": 2
}