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Bikeshare System Data Part 2 (The Bike)
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Bikeshare2.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# import modules\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.ticker as tkr\n",
"import numpy as np\n",
"import pandas as pd\n",
"from datetime import datetime, timedelta\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"\n",
"# use fivethirtyeight plot style\n",
"plt.style.use('fivethirtyeight')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# lists based on csv filenames will be used to load multiple csv files into pd dataframe\n",
"quarters = ['4th', '3rd', '2nd', '1st']\n",
"years = ['2014']"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# column names for pd dataframe \n",
"headers = ['Duration', 'Minutes', 'Start Date', 'Starting Station', 'Start Terminal', \n",
" 'End Date', 'End Station', 'End Terminal', 'Bike', 'Member Type']"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# loading multiple csv files into python list\n",
"tmp_lst = []\n",
"for year in years:\n",
" for quarter in quarters:\n",
" path = 'c:/users/mra/desktop/admin/chart-it/Bikeshare/system data/{}-{}-quarter.csv'.format(year,quarter) \n",
" frame = pd.read_csv(path, names = headers, header = 0, low_memory = False) \n",
" tmp_lst.append(frame)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# use concat method to convert python list into pd dataframe\n",
"bike_share = (pd.concat(tmp_lst, ignore_index = True))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: convert_objects is deprecated. Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
}
],
"source": [
"# convert 'Minutes' column data into float data type\n",
"bike_share['Minutes'] = bike_share.Minutes.convert_objects(convert_numeric=True)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# fill zero minute rides float '0' \n",
"bike_share['Minutes'] = bike_share['Minutes'].fillna(value=0)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# convert minutes column into float64 datatype\n",
"bike_share['Minutes'] = bike_share.Minutes.astype('float64')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# convert 'Start Date' column data into datetime data type\n",
"bike_share['Start Date'] = pd.to_datetime(bike_share['Start Date'], format='%m/%d/%Y %H:%M')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# convert 'End Date' column data into datetime data type\n",
"bike_share['End Date'] = pd.to_datetime(bike_share['End Date'], format='%m/%d/%Y %H:%M')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# new dataframe groups data in a more useable format (by bike number) and aggregates the desired data (e.g., total minutes by bike number)\n",
"bikes_by_number = bike_share.groupby(\"Bike\").agg({'Start Date': min, 'End Date': max, 'Minutes':[sum, np.mean, np.size]})"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# new dataframe excludes bikes that were not usedin both January and December (i.e., proxy to exclude bikes used for a partial year). \n",
"full_time_bikes = bikes_by_number[(bikes_by_number['Start Date']['min'] < '01-30-2014') & \n",
" (bikes_by_number['End Date']['max'] > '12-01-2014')]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# query data for most and least popular bikes by total minutes ridden and by total number of rides\n",
"least_popular_by_mins = full_time_bikes[full_time_bikes.Minutes['sum'] == full_time_bikes.Minutes['sum'].min()]\n",
"most_popular_by_mins = full_time_bikes[full_time_bikes.Minutes['sum'] == full_time_bikes.Minutes['sum'].max()]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"('W20167', 'W01136')"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# extract desired bike numbers \n",
"most_popular_by_mins.index[0], least_popular_by_mins.index[0]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# new dataframe with least popular bike\n",
"least_popular_bike_data = bike_share[bike_share['Bike']==least_popular_by_mins.index[0]]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# new dataframe with most popular bike\n",
"most_popular_bike_data = bike_share[bike_share['Bike']==most_popular_by_mins.index[0]]"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# groups most popular bike data by 'Member Type'\n",
"most_popular_bike_mt = most_popular_bike_data.groupby(by=\"Member Type\").agg(['sum', 'mean', 'count'])"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# groups least popular bike data by 'Member Type'\n",
"least_popular_bike_mt = least_popular_bike_data.groupby(by=\"Member Type\").agg(['sum', 'mean', 'count'])"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# groupsby most and least popular bikes by 'Member Type'\n",
"most_popular_bike_hist = pd.DataFrame({'Minutes': most_popular_bike_data.Minutes, \n",
" 'Member Type': most_popular_bike_data['Member Type']}).dropna(how='all')\n",
"least_popular_bike_hist = pd.DataFrame({'Minutes': least_popular_bike_data.Minutes, \n",
" 'Member Type': least_popular_bike_data['Member Type']}).dropna(how='all')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# adds separate 'Casual' and 'Registered' columns to data frame \n",
"most_popular_bike_hist['Casual'] = most_popular_bike_hist.groupby('Member Type').get_group('Casual')['Minutes']; \n",
"most_popular_bike_hist['Registered'] = most_popular_bike_hist.groupby('Member Type').get_group('Registered')['Minutes']\n",
"\n",
"least_popular_bike_hist['Casual'] = least_popular_bike_hist.groupby('Member Type').get_group('Casual')['Minutes']; \n",
"least_popular_bike_hist['Registered'] = least_popular_bike_hist.groupby('Member Type').get_group('Registered')['Minutes']"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# calculates median ride length \n",
"most_popular_bike_casual_median_ride_length = most_popular_bike_hist['Casual'].median() \n",
"most_popular_bike_registered_median_ride_length = most_popular_bike_hist['Registered'].median() \n",
"\n",
"least_popular_bike_casual_median_ride_length = least_popular_bike_hist['Casual'].median() \n",
"least_popular_bike_registered_median_ride_length = least_popular_bike_hist['Registered'].median() "
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
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"<p>62 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" Casual Registered\n",
"492530 59.22 NaN\n",
"493090 95.00 NaN\n",
"493709 NaN 5.43\n",
"494641 NaN 10.13\n",
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"571020 NaN 5.55\n",
"634735 NaN 2.20\n",
"... ... ...\n",
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"2402094 NaN 6.18\n",
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"\n",
"[62 rows x 2 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# delete unnecessary columns in dataframes \n",
"most_popular_bike_hist.drop(['Member Type','Minutes'], axis=1)\n",
"least_popular_bike_hist.drop(['Member Type', 'Minutes'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create column with total ride data (casual + registered)\n",
"most_popular_bike_hist['Total'] = most_popular_bike_hist['Casual'].fillna(0) + most_popular_bike_hist['Registered'].fillna(0)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# create column with total ride data (casual + registered)\n",
"least_popular_bike_hist['Total'] = least_popular_bike_hist['Casual'].fillna(0) + least_popular_bike_hist['Registered'].fillna(0)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(28958.800000000003, 1569, 18.456851497769282, 10.77, 37.32763816460879)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# most popular bike summary statistics\n",
"most_popular_bike_hist['Total'].sum(),most_popular_bike_hist['Total'].count(),most_popular_bike_hist['Total'].mean(),most_popular_bike_hist['Total'].median(),most_popular_bike_hist['Total'].std()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(893.73, 62, 14.415000000000001, 8.0, 17.09343894358396)"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# least popular bike summary statistics\n",
"least_popular_bike_hist['Total'].sum(), least_popular_bike_hist['Total'].count(), least_popular_bike_hist['Total'].mean(), least_popular_bike_hist['Total'].median(), least_popular_bike_hist['Total'].std()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# new df to calculate monthly ride numbers by various metrics (rides, total minutes)\n",
"data_by_bike = bike_share.set_index('Start Date').groupby('Bike')"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# resample by month\n",
"data_by_bike_count = data_by_bike['Minutes'].resample('M', how='count')\n",
"data_by_bike_total_mins = data_by_bike['Minutes'].resample('M', how='sum')"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# unstack months (moves months to x-axis)\n",
"data_by_bike_count = data_by_bike_count.unstack('Start Date')\n",
"data_by_bike_total_mins = data_by_bike_total_mins.unstack('Start Date')"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# adds annual sum column\n",
"data_by_bike_count['Total'] = data_by_bike_count.sum(1)\n",
"data_by_bike_total_mins['Total'] = data_by_bike_total_mins.sum(1)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# dataframe/groupby bike number using median as the aggregator\n",
"data_by_bike_median_mins = bike_share.groupby('Bike').agg('median')"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"count 2292.000000\n",
"mean 995.123909\n",
"std 254.618844\n",
"min 62.000000\n",
"25% 842.000000\n",
"50% 1026.500000\n",
"75% 1178.000000\n",
"max 1649.000000\n",
"Name: size, dtype: float64"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# full-time bikes summary statistics\n",
"full_time_bikes['Minutes']['size'].describe() "
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of bike rides: 3207. Median number of rides per bike: 1026.5. Stdev of rides: 254.61884353327642 Median ride duration per bike: 10.74. Standard deviation of ride duration per bike: 1.3458295943542464. Median total minutes across bikes: 17495.969999999976. Standard deviation of median total minutes: 4667.548045607136\n"
]
}
],
"source": [
"# general bike usage summary statistics\n",
"number_of_bikes_used_in_2014 = len(bikes_by_number)\n",
"median_number_of_rides_per_bike = full_time_bikes['Minutes']['size'].median() #uses full-time bikes only\n",
"standard_deviation_median_number_of_rides_per_bike = full_time_bikes['Minutes']['size'].std() #uses full-time bikes only\n",
"median_ride_duration_per_bike = data_by_bike_median_mins['Minutes'].median()\n",
"standard_deviation_of_ride_duration_per_bike = data_by_bike_median_mins['Minutes'].std()\n",
"median_total_minutes_across_bikes = full_time_bikes['Minutes']['sum'].median() #uses full-time bikes only\n",
"standard_deviation_of_median_total_minutes_across_bikes = full_time_bikes['Minutes']['sum'].std() #uses full-time bikes only\n",
"\n",
"print(\"Number of bike rides: {}. Median number of rides per bike: {}. Stdev of rides: {} \\\n",
" Median ride duration per bike: {}. Standard deviation of ride duration per bike: {}. \\\n",
" Median total minutes across bikes: {}. Standard deviation of median total minutes: {}\".\n",
" format(number_of_bikes_used_in_2014, median_number_of_rides_per_bike, standard_deviation_median_number_of_rides_per_bike,\n",
" median_ride_duration_per_bike, standard_deviation_of_ride_duration_per_bike, median_total_minutes_across_bikes, \n",
" standard_deviation_of_median_total_minutes_across_bikes))"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Minutes</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Bike</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>W00005</th>\n",
" <td>10.255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00006</th>\n",
" <td>10.250</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00007</th>\n",
" <td>10.700</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00008</th>\n",
" <td>10.870</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00009</th>\n",
" <td>10.450</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00010</th>\n",
" <td>10.680</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00011</th>\n",
" <td>11.350</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00012</th>\n",
" <td>10.350</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00013</th>\n",
" <td>9.560</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00014</th>\n",
" <td>11.380</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00015</th>\n",
" <td>10.195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00016</th>\n",
" <td>10.250</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00017</th>\n",
" <td>10.630</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00019</th>\n",
" <td>9.850</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00020</th>\n",
" <td>10.650</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00021</th>\n",
" <td>10.880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00022</th>\n",
" <td>10.580</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00024</th>\n",
" <td>10.580</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00025</th>\n",
" <td>10.530</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00026</th>\n",
" <td>10.640</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00027</th>\n",
" <td>10.130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00028</th>\n",
" <td>9.185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00029</th>\n",
" <td>10.570</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00030</th>\n",
" <td>10.980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00031</th>\n",
" <td>10.420</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00032</th>\n",
" <td>10.180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00033</th>\n",
" <td>10.715</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00034</th>\n",
" <td>10.965</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00035</th>\n",
" <td>11.185</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W00036</th>\n",
" <td>10.730</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21922</th>\n",
" <td>10.890</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21928</th>\n",
" <td>10.070</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21932</th>\n",
" <td>7.265</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21934</th>\n",
" <td>9.050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21936</th>\n",
" <td>9.820</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21938</th>\n",
" <td>9.570</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21942</th>\n",
" <td>9.510</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21946</th>\n",
" <td>23.870</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21949</th>\n",
" <td>8.800</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21950</th>\n",
" <td>10.825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21956</th>\n",
" <td>18.725</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21957</th>\n",
" <td>10.250</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21960</th>\n",
" <td>8.440</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21961</th>\n",
" <td>8.765</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21962</th>\n",
" <td>9.325</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21963</th>\n",
" <td>9.805</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21968</th>\n",
" <td>6.850</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21970</th>\n",
" <td>10.105</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21980</th>\n",
" <td>11.650</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21982</th>\n",
" <td>2.970</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W21985</th>\n",
" <td>2.630</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00059</th>\n",
" <td>11.130</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00223</th>\n",
" <td>11.480</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00461</th>\n",
" <td>10.180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00527</th>\n",
" <td>10.330</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00583</th>\n",
" <td>9.920</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00644</th>\n",
" <td>9.720</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w00765</th>\n",
" <td>9.470</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w01100</th>\n",
" <td>11.050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>w01117</th>\n",
" <td>10.685</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>3207 rows × 1 columns</p>\n",
"</div>"
],
"text/plain": [
" Minutes\n",
"Bike \n",
"W00005 10.255\n",
"W00006 10.250\n",
"W00007 10.700\n",
"W00008 10.870\n",
"W00009 10.450\n",
"W00010 10.680\n",
"W00011 11.350\n",
"W00012 10.350\n",
"W00013 9.560\n",
"W00014 11.380\n",
"W00015 10.195\n",
"W00016 10.250\n",
"W00017 10.630\n",
"W00019 9.850\n",
"W00020 10.650\n",
"W00021 10.880\n",
"W00022 10.580\n",
"W00024 10.580\n",
"W00025 10.530\n",
"W00026 10.640\n",
"W00027 10.130\n",
"W00028 9.185\n",
"W00029 10.570\n",
"W00030 10.980\n",
"W00031 10.420\n",
"W00032 10.180\n",
"W00033 10.715\n",
"W00034 10.965\n",
"W00035 11.185\n",
"W00036 10.730\n",
"... ...\n",
"W21922 10.890\n",
"W21928 10.070\n",
"W21932 7.265\n",
"W21934 9.050\n",
"W21936 9.820\n",
"W21938 9.570\n",
"W21942 9.510\n",
"W21946 23.870\n",
"W21949 8.800\n",
"W21950 10.825\n",
"W21956 18.725\n",
"W21957 10.250\n",
"W21960 8.440\n",
"W21961 8.765\n",
"W21962 9.325\n",
"W21963 9.805\n",
"W21968 6.850\n",
"W21970 10.105\n",
"W21980 11.650\n",
"W21982 2.970\n",
"W21985 2.630\n",
"w00059 11.130\n",
"w00223 11.480\n",
"w00461 10.180\n",
"w00527 10.330\n",
"w00583 9.920\n",
"w00644 9.720\n",
"w00765 9.470\n",
"w01100 11.050\n",
"w01117 10.685\n",
"\n",
"[3207 rows x 1 columns]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# delete unnecessary columns\n",
"data_by_bike_median_mins.drop(['Start Terminal','End Terminal'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# dataframes with starting/ending stations of most popular and least popular mikes\n",
"most_popular_bike_station = bike_share[bike_share['Bike'] == 'W21456']\n",
"least_popular_bike_station = bike_share[bike_share['Bike'] == least_popular_by_mins.index[0]]"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Minutes</th>\n",
" <th>Starting Station</th>\n",
" <th>End Station</th>\n",
" <th>Member Type</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>492530</th>\n",
" <td>59.22</td>\n",
" <td>Bethesda Ave &amp; Arlington Rd</td>\n",
" <td>34th &amp; Water St NW</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>493090</th>\n",
" <td>95.00</td>\n",
" <td>34th &amp; Water St NW</td>\n",
" <td>25th St &amp; Pennsylvania Ave NW</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>493709</th>\n",
" <td>5.43</td>\n",
" <td>25th St &amp; Pennsylvania Ave NW</td>\n",
" <td>21st &amp; I St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>494641</th>\n",
" <td>10.13</td>\n",
" <td>21st &amp; I St NW</td>\n",
" <td>8th &amp; F St NW / National Portrait Gallery</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>494725</th>\n",
" <td>9.92</td>\n",
" <td>8th &amp; F St NW / National Portrait Gallery</td>\n",
" <td>3rd &amp; H St NE</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>494916</th>\n",
" <td>5.95</td>\n",
" <td>3rd &amp; H St NE</td>\n",
" <td>4th &amp; East Capitol St NE</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>496874</th>\n",
" <td>17.42</td>\n",
" <td>10th &amp; E St NW</td>\n",
" <td>6th &amp; H St NE</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>497000</th>\n",
" <td>17.35</td>\n",
" <td>6th &amp; H St NE</td>\n",
" <td>Bladensburg Rd &amp; Benning Rd NE</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>502441</th>\n",
" <td>11.58</td>\n",
" <td>Bladensburg Rd &amp; Benning Rd NE</td>\n",
" <td>Eastern Market Metro / Pennsylvania Ave &amp; 7th ...</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>502700</th>\n",
" <td>22.80</td>\n",
" <td>Eastern Market Metro / Pennsylvania Ave &amp; 7th ...</td>\n",
" <td>Kennedy Center</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510848</th>\n",
" <td>8.32</td>\n",
" <td>New Hampshire Ave &amp; T St NW</td>\n",
" <td>17th &amp; K St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>513067</th>\n",
" <td>5.88</td>\n",
" <td>17th &amp; K St NW</td>\n",
" <td>14th &amp; Rhode Island Ave NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>513438</th>\n",
" <td>6.27</td>\n",
" <td>14th &amp; Rhode Island Ave NW</td>\n",
" <td>12th &amp; U St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>513715</th>\n",
" <td>4.28</td>\n",
" <td>12th &amp; U St NW</td>\n",
" <td>14th &amp; Belmont St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>515706</th>\n",
" <td>19.55</td>\n",
" <td>14th &amp; Belmont St NW</td>\n",
" <td>Florida Ave &amp; R St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>516179</th>\n",
" <td>16.62</td>\n",
" <td>Florida Ave &amp; R St NW</td>\n",
" <td>18th St &amp; Wyoming Ave NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>516276</th>\n",
" <td>14.65</td>\n",
" <td>18th St &amp; Wyoming Ave NW</td>\n",
" <td>7th &amp; T St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>516513</th>\n",
" <td>7.90</td>\n",
" <td>7th &amp; T St NW</td>\n",
" <td>1st &amp; M St NE</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>518419</th>\n",
" <td>11.23</td>\n",
" <td>1st &amp; M St NE</td>\n",
" <td>10th &amp; E St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>519077</th>\n",
" <td>10.70</td>\n",
" <td>10th &amp; E St NW</td>\n",
" <td>4th &amp; M St SW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>519277</th>\n",
" <td>3.42</td>\n",
" <td>4th &amp; M St SW</td>\n",
" <td>4th &amp; E St SW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>519702</th>\n",
" <td>22.28</td>\n",
" <td>4th &amp; E St SW</td>\n",
" <td>S Joyce &amp; Army Navy Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>522497</th>\n",
" <td>6.73</td>\n",
" <td>S Joyce &amp; Army Navy Dr</td>\n",
" <td>20th &amp; Bell St</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552005</th>\n",
" <td>8.57</td>\n",
" <td>20th &amp; Bell St</td>\n",
" <td>S Glebe &amp; Potomac Ave</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552369</th>\n",
" <td>7.42</td>\n",
" <td>S Glebe &amp; Potomac Ave</td>\n",
" <td>23rd &amp; Crystal Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564755</th>\n",
" <td>3.88</td>\n",
" <td>23rd &amp; Crystal Dr</td>\n",
" <td>Crystal City Metro / 18th &amp; Bell St</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>567555</th>\n",
" <td>4.77</td>\n",
" <td>Crystal City Metro / 18th &amp; Bell St</td>\n",
" <td>27th &amp; Crystal Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>570650</th>\n",
" <td>18.17</td>\n",
" <td>27th &amp; Crystal Dr</td>\n",
" <td>Saint Asaph St &amp; Pendleton St</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>571020</th>\n",
" <td>5.55</td>\n",
" <td>Saint Asaph St &amp; Pendleton St</td>\n",
" <td>Prince St &amp; Union St</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>634735</th>\n",
" <td>2.20</td>\n",
" <td>Duke St &amp; John Carlyle St</td>\n",
" <td>Ballenger Ave &amp; Dulaney St</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1489890</th>\n",
" <td>46.77</td>\n",
" <td>Crabbs Branch Way &amp; Redland Rd</td>\n",
" <td>Crabbs Branch Way &amp; Redland Rd</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1661050</th>\n",
" <td>59.77</td>\n",
" <td>Crabbs Branch Way &amp; Redland Rd</td>\n",
" <td>Crabbs Branch Way &amp; Redland Rd</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1727662</th>\n",
" <td>11.07</td>\n",
" <td>Shady Grove Metro West</td>\n",
" <td>Crabbs Branch Way &amp; Redland Rd</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1776696</th>\n",
" <td>7.20</td>\n",
" <td>King Farm Blvd &amp; Piccard Dr</td>\n",
" <td>Shady Grove Metro West</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1801690</th>\n",
" <td>4.42</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>King Farm Blvd &amp; Piccard Dr</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1801999</th>\n",
" <td>3.88</td>\n",
" <td>King Farm Blvd &amp; Piccard Dr</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1985686</th>\n",
" <td>15.48</td>\n",
" <td>Rockville Metro West</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2099657</th>\n",
" <td>1.75</td>\n",
" <td>Rockville Metro West</td>\n",
" <td>Monroe St &amp; Monroe Pl</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2114926</th>\n",
" <td>16.68</td>\n",
" <td>Fallsgrove Dr &amp; W Montgomery Ave</td>\n",
" <td>Rockville Metro West</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2163881</th>\n",
" <td>53.85</td>\n",
" <td>Fallsgrove Dr &amp; W Montgomery Ave</td>\n",
" <td>Fallsgrove Dr &amp; W Montgomery Ave</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2164041</th>\n",
" <td>5.95</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Fallsgrove Dr &amp; W Montgomery Ave</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2182546</th>\n",
" <td>5.67</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2378194</th>\n",
" <td>6.92</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2382926</th>\n",
" <td>7.65</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2386717</th>\n",
" <td>6.82</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2402094</th>\n",
" <td>6.18</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2407002</th>\n",
" <td>7.95</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2455304</th>\n",
" <td>7.52</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>King Farm Blvd &amp; Pleasant Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2576682</th>\n",
" <td>3.40</td>\n",
" <td>4th &amp; E St SW</td>\n",
" <td>4th &amp; M St SW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2601366</th>\n",
" <td>4.23</td>\n",
" <td>17th &amp; Corcoran St NW</td>\n",
" <td>California St &amp; Florida Ave NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2608202</th>\n",
" <td>4.45</td>\n",
" <td>21st &amp; M St NW</td>\n",
" <td>M St &amp; Pennsylvania Ave NW</td>\n",
" <td>Casual</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2610818</th>\n",
" <td>4.53</td>\n",
" <td>20th &amp; O St NW / Dupont South</td>\n",
" <td>24th &amp; N St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2638879</th>\n",
" <td>5.38</td>\n",
" <td>California St &amp; Florida Ave NW</td>\n",
" <td>15th &amp; P St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2677510</th>\n",
" <td>6.58</td>\n",
" <td>34th St &amp; Wisconsin Ave NW</td>\n",
" <td>Wisconsin Ave &amp; O St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2720693</th>\n",
" <td>8.05</td>\n",
" <td>Wisconsin Ave &amp; O St NW</td>\n",
" <td>20th &amp; O St NW / Dupont South</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2758899</th>\n",
" <td>9.58</td>\n",
" <td>12th &amp; Hayes St / Pentagon City Metro</td>\n",
" <td>23rd &amp; Crystal Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2780821</th>\n",
" <td>10.63</td>\n",
" <td>Shady Grove Hospital</td>\n",
" <td>Piccard &amp; W Gude Dr</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2813119</th>\n",
" <td>12.47</td>\n",
" <td>15th &amp; P St NW</td>\n",
" <td>7th &amp; F St NW / National Portrait Gallery</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2889954</th>\n",
" <td>19.98</td>\n",
" <td>4th &amp; M St SW</td>\n",
" <td>21st &amp; M St NW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2898984</th>\n",
" <td>21.55</td>\n",
" <td>Aurora Hills Community Ctr/18th &amp; Hayes St</td>\n",
" <td>4th &amp; E St SW</td>\n",
" <td>Registered</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>62 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" Minutes Starting Station \\\n",
"492530 59.22 Bethesda Ave & Arlington Rd \n",
"493090 95.00 34th & Water St NW \n",
"493709 5.43 25th St & Pennsylvania Ave NW \n",
"494641 10.13 21st & I St NW \n",
"494725 9.92 8th & F St NW / National Portrait Gallery \n",
"494916 5.95 3rd & H St NE \n",
"496874 17.42 10th & E St NW \n",
"497000 17.35 6th & H St NE \n",
"502441 11.58 Bladensburg Rd & Benning Rd NE \n",
"502700 22.80 Eastern Market Metro / Pennsylvania Ave & 7th ... \n",
"510848 8.32 New Hampshire Ave & T St NW \n",
"513067 5.88 17th & K St NW \n",
"513438 6.27 14th & Rhode Island Ave NW \n",
"513715 4.28 12th & U St NW \n",
"515706 19.55 14th & Belmont St NW \n",
"516179 16.62 Florida Ave & R St NW \n",
"516276 14.65 18th St & Wyoming Ave NW \n",
"516513 7.90 7th & T St NW \n",
"518419 11.23 1st & M St NE \n",
"519077 10.70 10th & E St NW \n",
"519277 3.42 4th & M St SW \n",
"519702 22.28 4th & E St SW \n",
"522497 6.73 S Joyce & Army Navy Dr \n",
"552005 8.57 20th & Bell St \n",
"552369 7.42 S Glebe & Potomac Ave \n",
"564755 3.88 23rd & Crystal Dr \n",
"567555 4.77 Crystal City Metro / 18th & Bell St \n",
"570650 18.17 27th & Crystal Dr \n",
"571020 5.55 Saint Asaph St & Pendleton St \n",
"634735 2.20 Duke St & John Carlyle St \n",
"... ... ... \n",
"1489890 46.77 Crabbs Branch Way & Redland Rd \n",
"1661050 59.77 Crabbs Branch Way & Redland Rd \n",
"1727662 11.07 Shady Grove Metro West \n",
"1776696 7.20 King Farm Blvd & Piccard Dr \n",
"1801690 4.42 King Farm Blvd & Pleasant Dr \n",
"1801999 3.88 King Farm Blvd & Piccard Dr \n",
"1985686 15.48 Rockville Metro West \n",
"2099657 1.75 Rockville Metro West \n",
"2114926 16.68 Fallsgrove Dr & W Montgomery Ave \n",
"2163881 53.85 Fallsgrove Dr & W Montgomery Ave \n",
"2164041 5.95 Piccard & W Gude Dr \n",
"2182546 5.67 Piccard & W Gude Dr \n",
"2378194 6.92 King Farm Blvd & Pleasant Dr \n",
"2382926 7.65 Piccard & W Gude Dr \n",
"2386717 6.82 King Farm Blvd & Pleasant Dr \n",
"2402094 6.18 Piccard & W Gude Dr \n",
"2407002 7.95 King Farm Blvd & Pleasant Dr \n",
"2455304 7.52 Piccard & W Gude Dr \n",
"2576682 3.40 4th & E St SW \n",
"2601366 4.23 17th & Corcoran St NW \n",
"2608202 4.45 21st & M St NW \n",
"2610818 4.53 20th & O St NW / Dupont South \n",
"2638879 5.38 California St & Florida Ave NW \n",
"2677510 6.58 34th St & Wisconsin Ave NW \n",
"2720693 8.05 Wisconsin Ave & O St NW \n",
"2758899 9.58 12th & Hayes St / Pentagon City Metro \n",
"2780821 10.63 Shady Grove Hospital \n",
"2813119 12.47 15th & P St NW \n",
"2889954 19.98 4th & M St SW \n",
"2898984 21.55 Aurora Hills Community Ctr/18th & Hayes St \n",
"\n",
" End Station Member Type \n",
"492530 34th & Water St NW Casual \n",
"493090 25th St & Pennsylvania Ave NW Casual \n",
"493709 21st & I St NW Registered \n",
"494641 8th & F St NW / National Portrait Gallery Registered \n",
"494725 3rd & H St NE Registered \n",
"494916 4th & East Capitol St NE Registered \n",
"496874 6th & H St NE Registered \n",
"497000 Bladensburg Rd & Benning Rd NE Registered \n",
"502441 Eastern Market Metro / Pennsylvania Ave & 7th ... Registered \n",
"502700 Kennedy Center Registered \n",
"510848 17th & K St NW Registered \n",
"513067 14th & Rhode Island Ave NW Registered \n",
"513438 12th & U St NW Registered \n",
"513715 14th & Belmont St NW Registered \n",
"515706 Florida Ave & R St NW Registered \n",
"516179 18th St & Wyoming Ave NW Registered \n",
"516276 7th & T St NW Registered \n",
"516513 1st & M St NE Registered \n",
"518419 10th & E St NW Registered \n",
"519077 4th & M St SW Registered \n",
"519277 4th & E St SW Registered \n",
"519702 S Joyce & Army Navy Dr Registered \n",
"522497 20th & Bell St Registered \n",
"552005 S Glebe & Potomac Ave Registered \n",
"552369 23rd & Crystal Dr Registered \n",
"564755 Crystal City Metro / 18th & Bell St Registered \n",
"567555 27th & Crystal Dr Registered \n",
"570650 Saint Asaph St & Pendleton St Registered \n",
"571020 Prince St & Union St Registered \n",
"634735 Ballenger Ave & Dulaney St Registered \n",
"... ... ... \n",
"1489890 Crabbs Branch Way & Redland Rd Casual \n",
"1661050 Crabbs Branch Way & Redland Rd Casual \n",
"1727662 Crabbs Branch Way & Redland Rd Casual \n",
"1776696 Shady Grove Metro West Registered \n",
"1801690 King Farm Blvd & Piccard Dr Casual \n",
"1801999 King Farm Blvd & Pleasant Dr Casual \n",
"1985686 Piccard & W Gude Dr Registered \n",
"2099657 Monroe St & Monroe Pl Registered \n",
"2114926 Rockville Metro West Registered \n",
"2163881 Fallsgrove Dr & W Montgomery Ave Casual \n",
"2164041 Fallsgrove Dr & W Montgomery Ave Registered \n",
"2182546 Piccard & W Gude Dr Casual \n",
"2378194 Piccard & W Gude Dr Registered \n",
"2382926 King Farm Blvd & Pleasant Dr Registered \n",
"2386717 Piccard & W Gude Dr Registered \n",
"2402094 King Farm Blvd & Pleasant Dr Registered \n",
"2407002 Piccard & W Gude Dr Registered \n",
"2455304 King Farm Blvd & Pleasant Dr Registered \n",
"2576682 4th & M St SW Registered \n",
"2601366 California St & Florida Ave NW Registered \n",
"2608202 M St & Pennsylvania Ave NW Casual \n",
"2610818 24th & N St NW Registered \n",
"2638879 15th & P St NW Registered \n",
"2677510 Wisconsin Ave & O St NW Registered \n",
"2720693 20th & O St NW / Dupont South Registered \n",
"2758899 23rd & Crystal Dr Registered \n",
"2780821 Piccard & W Gude Dr Registered \n",
"2813119 7th & F St NW / National Portrait Gallery Registered \n",
"2889954 21st & M St NW Registered \n",
"2898984 4th & E St SW Registered \n",
"\n",
"[62 rows x 4 columns]"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# delete unnecessary columns\n",
"most_popular_bike_station.drop(['Duration', 'Start Date', 'Start Terminal', 'End Terminal', 'End Date', 'Bike'], axis=1)\n",
"least_popular_bike_station.drop(['Duration', 'Start Date', 'Start Terminal', 'End Terminal', 'End Date', 'Bike'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
}
],
"source": [
"# dataframe to explore most popular bike stations\n",
"most_popular_bike_station = most_popular_bike_station.groupby('Starting Station').agg('count').sort('Member Type', ascending = False)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
}
],
"source": [
"# dataframe to explore least popular bike stations\n",
"least_popular_bike_station = least_popular_bike_station.groupby('Starting Station').agg('count').sort('Member Type', ascending = False).head()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"count 3207.000000\n",
"mean 10.716093\n",
"std 1.345830\n",
"min 2.630000\n",
"25% 10.330000\n",
"50% 10.740000\n",
"75% 11.120000\n",
"max 60.200000\n",
"Name: Minutes, dtype: float64"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# bike median ride length summary stats\n",
"data_by_bike_median_mins['Minutes'].describe()"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# add 'percent of total' column to calc most frequent starting locations\n",
"most_popular_bike_station['Pct'] = most_popular_bike_station['Minutes'] / most_popular_bike_station['Minutes'].sum() * 100"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
" from IPython.kernel.zmq import kernelapp as app\n"
]
}
],
"source": [
"# sorts by popularity\n",
"most_popular_bike_station_hist = most_popular_bike_station.sort('Pct', ascending=True)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# delete empty rows\n",
"data_by_bike_count_dropna = data_by_bike_count.dropna(how='any')"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(60.666666666666664, 104.25)"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# calculates 15th and 85th quantiles for ride number\n",
"full_time_bikes['Minutes']['size'].quantile(0.15) / 12, full_time_bikes['Minutes']['size'].quantile(0.85) / 12"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(199.56916666666649, 358.05886666666703)"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# calculates 15th and 85th quantiles for total hours\n",
"full_time_bikes['Minutes']['sum'].quantile(0.15) / 60, full_time_bikes['Minutes']['sum'].quantile(0.85) / 60"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# dataframe of bikes with a ride in every single month\n",
"data_by_bike_filtered = data_by_bike_count[(data_by_bike_count > 0)]"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# drop empty rows\n",
"data_by_bike_filtered = data_by_bike_filtered.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(1102.0, 985.0)"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# calculate median ride length and number of rides\n",
"data_by_bike_filtered['Total'].median(),data_by_bike_count['Total'].median()"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# calculate active number of bikes in every month and the percent growth in bikes from January\n",
"bikes_in_month = bike_share.set_index('Start Date').resample('M', lambda x: x.nunique())['Bike']\n",
"bikes_in_month_pct_change = bike_share.set_index('Start Date').resample('M', lambda x: x.nunique())['Bike']"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# calculate cumulative percent change\n",
"bikes_in_month_pct_change['cum_pct_change'] = (bikes_in_month / bikes_in_month[0]) - 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import matplotlib.dates as mdates\n",
"\n",
"# formatter functions used in plots to convert format of x/y axes \n",
"def func1(x, pos): \n",
" s = x / 60\n",
" s = '{:0,d}'.format(int(s))\n",
" return s\n",
"\n",
"def func2(x, pos): \n",
" s = '{}%'.format(x)\n",
" return s\n",
"\n",
"def func3(x, pos): \n",
" s = '{:.0f}%'.format(x * 100)\n",
" return s\n",
"\n",
"def func4(x, pos): \n",
" s = '{:0,d}'.format(int(x))\n",
" return s"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xcc362e8>"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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aObQO6c5K/t37lW/fvq3IyEhJd07qcHd3V2xsrOrVq2etZeTIkWrTpo2KFCmi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\nP99CzTPOQ3SEAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd2629e8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot histogram of total minutes by bike for full-time bikes only\n",
"\n",
"plt.subplot(1,1,1)\n",
"ax1 = full_time_bikes['Minutes']['size'].hist(alpha=1, grid = False, figsize=(10,6), stacked=True, bins=30)\n",
"ax1.set_xlabel('Number of Rides', fontsize=14)\n",
"ax1.set_ylabel('Number of Bikes', fontsize=14)\n",
"ax1.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"ax1.set_xlim(0,1600)\n",
"\n",
"x_format = tkr.FuncFormatter(func4) # make formatter\n",
"ax1.xaxis.set_major_formatter(x_format)\n",
"ax1.text(x=800,y=230,s='Median: 1,027 rides')\n",
"\n",
"ax1.text(x=200,y=210,s='15th %tile: {:.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.15)))\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, -600, 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"ax1.text(x=1300,y=210,s='85th %tile: {:,.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.85)))\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 500 , 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"\n",
"ax1.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax1.transAxes) "
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xcd85f98>"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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KT09X27ZtC/y+NG7cWFWrVtXkyZN1+PBh/fzzz5ozZ47atm2rcuXKqU6dOkpN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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xcc22710>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot histogram of total minutes by bike for full-time bikes only\n",
"\n",
"plt.subplot(1,1,1)\n",
"ax2 = full_time_bikes['Minutes']['sum'].hist(alpha=1, grid = False, figsize=(10,6), bins=50)\n",
"ax2.set_xlabel('Total Hours', fontsize=14)\n",
"ax2.set_ylabel('Number of Bikes', fontsize=14)\n",
"ax2.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"\n",
"ax2.xaxis.set_ticks(np.arange(0, 500 * 60, 50 * 60))\n",
"x_format = tkr.FuncFormatter(func1) # make formatter\n",
"ax2.xaxis.set_major_formatter(x_format)\n",
"ax2.text(x=(190 * 60),y=130, s='Median: {:.0f} hours'.format( median_total_minutes_across_bikes / 60))\n",
"\n",
"ax2.text(x=3500,y=110,s='15th %tile: {:.0f} hours'.format(full_time_bikes['Minutes']['sum'].quantile(0.15) /60))\n",
"ax2.arrow(full_time_bikes['Minutes']['sum'].quantile(0.15) , 100, 0, -100, head_width=5, head_length=300, fc='k', ec='k')\n",
"ax2.arrow(full_time_bikes['Minutes']['sum'].quantile(0.15) , 100, -9000, 0, head_width=5, head_length=300, fc='k', ec='k')\n",
"\n",
"ax2.text(x=22500,y=110,s='85th %tile: {:.0f} hours'.format(full_time_bikes['Minutes']['sum'].quantile(0.85) /60))\n",
"ax2.arrow(full_time_bikes['Minutes']['sum'].quantile(0.85), 100, 0, -100, head_width=5, head_length=300, fc='k', ec='k')\n",
"ax2.arrow(full_time_bikes['Minutes']['sum'].quantile(0.85), 100, 8000, 0, head_width=5, head_length=300, fc='k', ec='k')\n",
"\n",
"ax2.text(0.12, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax2.transAxes) "
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xd1cbac8>"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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AOM2pNbhms1n33Xefli1bprNnz6qwsFBWq1XZ2dl65JFHlJmZWadJN27cqOjoaIfXU089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\nAa4QQgghhChT/h8JPxHzwtMwaAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd20a278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot histogram of median minutes per ride by bike \n",
"\n",
"plt.subplot(1,1,1)\n",
"ax3 = data_by_bike_median_mins['Minutes'].hist(alpha=1, grid = False, figsize=(10,6), stacked=True, range=[7,14], bins=20)\n",
"ax3.set_xlabel('Median Ride Length (Minutes)')\n",
"ax3.set_ylabel('Number of Bikes')\n",
"ax3.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"\n",
"ax3.text(0.12, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax3.transAxes) "
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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blpZWrxAPTSTIG3UKr18dLdsdCyGEaJY0TeN4pcr2QifbC93sKHJxoLT+0ysA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4fPP/8cY2Nj3N3ddZJpLy8vlixZQnR0NP3792fKlCn07dsXGxsbPv74Y8qWLcv58+eBjNbrdu3a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\nYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd0acba8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot histogram of active bikes by month\n",
"\n",
"plt.subplot(1,1,1)\n",
"ax4 = bikes_in_month.plot(kind='line',alpha=1, grid = True, figsize=(10,6))\n",
"ax4.set_xlabel('Month', fontsize=14)\n",
"ax4.set_ylabel('Estimated Bikes in Operation', fontsize=14)\n",
"ax4.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='on', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"\n",
"ax4.set_ylim(1000,3600)\n",
"\n",
"date_fmt = 'Jan'\n",
"formatter = mdates.DateFormatter(date_fmt)\n",
"ax4.xaxis.set_major_formatter(formatter)\n",
"ax4.tick_params(axis='y')\n",
"\n",
"y_format = tkr.FuncFormatter(func4) \n",
"ax4.yaxis.set_major_formatter(y_format)\n",
"ax4.tick_params(axis='y', colors='#30a2da')\n",
"ax4.yaxis.label.set_color('#30a2da')\n",
"\n",
"plt.subplot(1,1,1)\n",
"ax5 = bikes_in_month_pct_change['cum_pct_change'].plot(kind='line',alpha=1, figsize=(10,6), \n",
" secondary_y=True, grid=False, style='k--', fontsize=14)\n",
"ax5.set_xlabel('Month')\n",
"ax5.set_ylabel('Percent Change Year-to-Date')\n",
"ax5.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='on', \n",
" top='off', \n",
" left='off',\n",
" labelbottom='on')\n",
"\n",
"date_fmt = 'Jan'\n",
"formatter = mdates.DateFormatter(date_fmt)\n",
"ax5.xaxis.set_major_formatter(formatter)\n",
"y_format = tkr.FuncFormatter(func3) # make formatter\n",
"ax5.yaxis.set_major_formatter(y_format)\n",
"ax5.set_ylim(0,0.26)\n",
"\n",
"\n",
"ax5.text(0.55, 0.31, 'Notable Maintenance Periods', transform=ax1.transAxes, fontsize=14, \n",
" verticalalignment='center', alpha=1, backgroundcolor='#f0f0f0')\n",
"ax5.arrow(0.9, 0.26, 0, 0.3, head_width=0.025, head_length=0.05, fc='k', ec='k', transform=ax5.transAxes)\n",
"ax5.arrow(0.58, 0.2, -0.13, 0, head_width=0.03, head_length=0.03, fc='k', ec='k', transform=ax5.transAxes)\n",
"\n",
"ax4.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax5.transAxes)\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"ax4.set_xlabel(\"Month\")\n",
"ax5.grid(False)\n",
"ax4.spines['bottom'].set_visible(True)\n",
"ax5.spines['bottom'].set_visible(True)\n",
"ax5.spines['bottom'].set_color('grey')\n",
"ax4.grid(True)\n",
"\n",
"\n",
"ax4.grid(b=True, which='minor')"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\MRA\\Anaconda3\\lib\\site-packages\\IPython\\kernel\\__main__.py:4: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
]
},
{
"data": {
"text/plain": [
"(array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), <a list of 10 Text yticklabel objects>)"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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5dOrUiaysrEJlPXr0YNu2bYWOHzt2DLVaXaL2/8zPESA2NhYPDw8cHBzo0KED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\nSYIphBBCCCEK1f8Dg1iFDDr0KuYAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xeda80f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot barh of most frequent starting stations for most popular bike \n",
"\n",
"plt.subplot(1,1,1)\n",
"ax6 = most_popular_bike_station.sort('Pct', ascending=True)['Pct'][-10:].plot(kind='barh',\n",
" alpha=1, grid = False, \n",
" figsize=(6,4), width=0.8,\n",
" edgecolor='black',\n",
" fontsize=14)\n",
"ax6.set_xlabel('Percent of Total Rides Started', fontsize=14)\n",
"ax6.set_ylabel('', fontsize=14)\n",
"ax6.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"x_format = tkr.FuncFormatter(func2)\n",
"ax6.xaxis.set_major_formatter(x_format)\n",
"\n",
"\n",
"ax6.text(-0.45, -0.3, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax6.transAxes)\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"229"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# total number of stations visited by most popular bike\n",
"most_popular_bike_station['Pct'].count()"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xcf699b0>"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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sNpt14sSJXHkPAwICbPbb3rp1S9HR0ZJuX8mhRIkSio+Pt74nPj4+mjNnjk6c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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd1f4ba8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot histogram of total minutes by bike for full-time bikes only\n",
"\n",
"plt.subplot(1,1,1)\n",
"ax1 = full_time_bikes['Minutes']['size'].hist(alpha=1, grid = False, figsize=(10,6), stacked=True, bins=30)\n",
"ax1.set_xlabel('Number of Rides', fontsize=14)\n",
"ax1.set_ylabel('Number of Bikes', fontsize=14)\n",
"ax1.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"x_format = tkr.FuncFormatter(func4) # make formatter\n",
"ax1.xaxis.set_major_formatter(x_format)\n",
"ax1.text(x=800,y=230,s='Median: 1,027 rides')\n",
"\n",
"ax1.text(x=200,y=210,s='15th %tile: {:.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.15)), fontsize=14)\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, -600, 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"ax1.text(x=1300,y=210,s='85th %tile: {:,.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.85)), fontsize=14)\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"ax1.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 500 , 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"ax1.set_xlim(0,1700)\n",
"\n",
"ax1.text(0.1, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax1.transAxes) "
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xd291a58>"
]
},
"execution_count": 58,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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AhkMIBgAAgOEQggEAAGA4hGAAAAAYDiEYAAAAhkMIBgAAgOEQggEAAGA4hGAAAAAYDiEY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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd1b17f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot ride data\n",
"import matplotlib.dates as mdates\n",
"\n",
"def func1(x, pos): \n",
" s = '{:,d}'.format(int(x))\n",
" return s\n",
"\n",
"ax10 = full_time_bikes['Minutes']['size'].plot(kind='hist', stacked=False, grid=False, figsize=(10,6), fontsize=14, \\\n",
" alpha=1, bins=30)\n",
"ax10.set_xlabel('Rides', fontsize=14)\n",
"ax10.set_ylabel('Bikes (thousands)', fontsize=14)\n",
"ax10.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"\n",
"ax10.xaxis.set_major_formatter(formatter)\n",
"x_format = tkr.FuncFormatter(func1) # make formatter\n",
"ax10.xaxis.set_major_formatter(x_format)\n",
"\n",
"ax10.text(70,y=230,s='Median: 1,027 rides', fontsize=14)\n",
"\n",
"# ax10.text(x=200,y=210,s='15th %tile: {:.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.15)), fontsize=14)\n",
"# ax10.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"# ax10.arrow(full_time_bikes['Minutes']['size'].quantile(0.15) , 200, -600, 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"# ax10.text(x=1250,y=210,s='85th %tile: {:,.0f} rides'.format(full_time_bikes['Minutes']['size'].quantile(0.85)), fontsize=14)\n",
"# ax10.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 0, -1000, head_width=10, head_length=15, fc='k', ec='k')\n",
"# ax10.arrow(full_time_bikes['Minutes']['size'].quantile(0.85), 200, 500 , 0, head_width=10, head_length=15, fc='k', ec='k')\n",
"\n",
"ax10.set_xticks(np.arange(0,1800, 200))\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"ax10.set_xlim(0,1600)\n",
"\n",
"ax10.text(0.13, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax10.transAxes) "
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0xe9f3940>"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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16tVLSUlJVu2bNm1SUFCQevToIX9/f7Vt21bt2rXTxo0bJUmff/65ateurRdffFGBgYEa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\nyJDkVQghhBBCFBn/D9sDx/8TNYybAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd716940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot ride data\n",
"import matplotlib.dates as mdates\n",
"\n",
"ax10 = full_time_bikes['Minutes']['sum'].plot(kind='hist', stacked=False, grid=False, figsize=(10,6), fontsize=14, \\\n",
" alpha=1, bins=50)\n",
"ax10.set_xlabel('Hours', fontsize=14)\n",
"ax10.set_ylabel('Bikes (thousands)', fontsize=14)\n",
"ax10.tick_params(\n",
" axis='both',\n",
" which='both', \n",
" bottom='off', \n",
" top='off', \n",
" right='off',\n",
" left='off',\n",
" labelbottom='on')\n",
"\n",
"x_format = tkr.FuncFormatter(func1) # make formatter\n",
"ax10.xaxis.set_major_formatter(x_format)\n",
"\n",
"ax10.text(x=1000,y=130, s='Median: {:.0f} hours'.format( median_total_minutes_across_bikes / 60), fontsize=14)\n",
"\n",
"# ax10.text(x=3500,y=110,s='15th %tile: {:.0f} hours'.format(full_time_bikes['Minutes']['sum'].quantile(0.15) /60), fontsize=14)\n",
"# ax10.arrow(full_time_bikes['Minutes']['sum'].quantile(0.15) , 100, 0, -100, head_width=5, head_length=300, fc='k', ec='k')\n",
"# ax10.arrow(full_time_bikes['Minutes']['sum'].quantile(0.15) , 100, -9000, 0, head_width=5, head_length=300, fc='k', ec='k')\n",
"\n",
"# ax10.text(x=21500,y=110,s='85th %tile: {:.0f} hours'.format(full_time_bikes['Minutes']['sum'].quantile(0.85) /60), fontsize=14)\n",
"# ax10.arrow(full_time_bikes['Minutes']['sum'].quantile(0.85), 100, 0, -100, head_width=5, head_length=300, fc='k', ec='k')\n",
"# ax10.arrow(full_time_bikes['Minutes']['sum'].quantile(0.85), 100, 8000, 0, head_width=5, head_length=300, fc='k', ec='k')\n",
"\n",
"ax10.set_xticks(np.arange(0,500*60, 500*60 / 10))\n",
"\n",
"plt.xticks(fontsize=14)\n",
"plt.yticks(fontsize=14)\n",
"\n",
"ax10.text(0.1, -0.2, \"From: chart-it (MikeRAzar.com/chart-it) | Source: www.capitalbikeshare.com/system-data\", \n",
" fontsize=12, transform=ax10.transAxes) "
]
},
{
"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": "3.4.3"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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