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Oleh_Bike_Share_Chicago Project 1
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{ | |
"metadata": { | |
"name": "", | |
"signature": "sha256:3299a47b5ed5ffa8a8b26378649118ed99fc3ba74536ff1e9a01e7b0f2eed6b4" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"#The Chicago Bike Share program " | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"#\"Divvy\" releases anonymized bike trip data. See my analysis below. " | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"#enigma link to my dataset \n", | |
"\n", | |
"https://app.enigma.io/search/source/us.states.il.cities.chicago.cdot.divy\n", | |
"\n", | |
"raw format: https://api.enigma.io/v2/data/3651c3b295eb9cc3a1d7bf8096ad577a/us.states.il.cities.chicago.cdot.divy.2013?conjunction=and" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"from pandas import DataFrame, read_csv\n", | |
"import matplotlib.pyplot as plt\n", | |
"import pandas as pd\n", | |
"import numpy as np\n", | |
"import sys\n", | |
"%matplotlib inline" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 1 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"location = r'/Users/olehdubno/Desktop/python_tests/bikeshare.csv'\n", | |
"\n", | |
"df = read_csv(location,low_memory=False)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 2 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df['gender'] = df['gender'].map({'Female': 0, 'Male': 1, 'NaN':2})\n", | |
"df['usertype'] = df['usertype'].map({'Customer':0,'Subscriber':1})" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 3 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df_clean = pd.DataFrame(df)\n", | |
"df_clean['birthday'].dropna(inplace=True)\n", | |
"df_clean['tripduration'].dropna(inplace=True)\n", | |
"df_clean['gender'].dropna(inplace=True)\n", | |
"df_clean['birthday'].dropna(inplace=True)\n", | |
"\n", | |
"df_clean['log_birthday'] = np.log(df_clean['birthday'])\n", | |
"df_clean['log_tripduration'] = np.log(df_clean['tripduration'])" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [], | |
"prompt_number": 4 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df.columns" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 33, | |
"text": [ | |
"Index([u'trip_id', u'starttime', u'stoptime', u'bikeid', u'tripduration', u'from_station_id', u'from_station_name', u'to_station_id', u'to_station_name', u'usertype', u'gender', u'birthday', u'serialid'], dtype='object')" | |
] | |
} | |
], | |
"prompt_number": 33 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df.info()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"<class 'pandas.core.frame.DataFrame'>\n", | |
"Int64Index: 759788 entries, 0 to 759787\n", | |
"Data columns (total 13 columns):\n", | |
"trip_id 759788 non-null int64\n", | |
"starttime 759788 non-null object\n", | |
"stoptime 759788 non-null object\n", | |
"bikeid 759788 non-null int64\n", | |
"tripduration 759788 non-null int64\n", | |
"from_station_id 759788 non-null int64\n", | |
"from_station_name 759788 non-null object\n", | |
"to_station_id 759788 non-null int64\n", | |
"to_station_name 759788 non-null object\n", | |
"usertype 759788 non-null object\n", | |
"gender 403046 non-null object\n", | |
"birthday 402909 non-null float64\n", | |
"serialid 759788 non-null int64\n", | |
"dtypes: float64(1), int64(6), object(6)" | |
] | |
} | |
], | |
"prompt_number": 34 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"There are close to 760,000 records in the data set\n", | |
"\n", | |
"\"usertype\" column has subscribers (1) and customers (0). The \"birthday\" and \"gender\" is only available from the subscriber (1) field." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df.tripduration.hist(range=(-1000,5000)).set_title('Trip Duration in Seconds')\n", | |
"df.describe()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"html": [ | |
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>trip_id</th>\n", | |
" <th>bikeid</th>\n", | |
" <th>tripduration</th>\n", | |
" <th>from_station_id</th>\n", | |
" <th>to_station_id</th>\n", | |
" <th>usertype</th>\n", | |
" <th>gender</th>\n", | |
" <th>birthday</th>\n", | |
" <th>serialid</th>\n", | |
" <th>log_birthday</th>\n", | |
" <th>log_tripduration</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>count</th>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" <td> 403046.000000</td>\n", | |
" <td> 402909.000000</td>\n", | |
" <td> 759788.0000</td>\n", | |
" <td> 402909.000000</td>\n", | |
" <td> 759788.000000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>mean</th>\n", | |
" <td> 553984.054582</td>\n", | |
" <td> 1117.964666</td>\n", | |
" <td> 1239.470455</td>\n", | |
" <td> 125.297671</td>\n", | |
" <td> 124.952351</td>\n", | |
" <td> 0.530458</td>\n", | |
" <td> 0.790471</td>\n", | |
" <td> 1976.854354</td>\n", | |
" <td> 379894.5000</td>\n", | |
" <td> 7.589248</td>\n", | |
" <td> 6.701703</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>std</th>\n", | |
" <td> 309503.044579</td>\n", | |
" <td> 736.470219</td>\n", | |
" <td> 2757.769764</td>\n", | |
" <td> 86.304741</td>\n", | |
" <td> 86.188268</td>\n", | |
" <td> 0.499072</td>\n", | |
" <td> 0.406973</td>\n", | |
" <td> 10.435801</td>\n", | |
" <td> 219332.0475</td>\n", | |
" <td> 0.005293</td>\n", | |
" <td> 0.815037</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>min</th>\n", | |
" <td> 3940.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 60.000000</td>\n", | |
" <td> 5.000000</td>\n", | |
" <td> 5.000000</td>\n", | |
" <td> 0.000000</td>\n", | |
" <td> 0.000000</td>\n", | |
" <td> 1906.000000</td>\n", | |
" <td> 1.0000</td>\n", | |
" <td> 7.552762</td>\n", | |
" <td> 4.094345</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>25%</th>\n", | |
" <td> 291602.500000</td>\n", | |
" <td> 499.000000</td>\n", | |
" <td> 473.000000</td>\n", | |
" <td> 53.000000</td>\n", | |
" <td> 53.000000</td>\n", | |
" <td> 0.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1970.000000</td>\n", | |
" <td> 189947.7500</td>\n", | |
" <td> 7.585789</td>\n", | |
" <td> 6.159095</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>50%</th>\n", | |
" <td> 549574.500000</td>\n", | |
" <td> 1016.000000</td>\n", | |
" <td> 821.500000</td>\n", | |
" <td> 97.000000</td>\n", | |
" <td> 97.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1980.000000</td>\n", | |
" <td> 379894.5000</td>\n", | |
" <td> 7.590852</td>\n", | |
" <td> 6.711132</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>75%</th>\n", | |
" <td> 816606.250000</td>\n", | |
" <td> 1650.000000</td>\n", | |
" <td> 1357.000000</td>\n", | |
" <td> 185.000000</td>\n", | |
" <td> 181.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1985.000000</td>\n", | |
" <td> 569841.2500</td>\n", | |
" <td> 7.593374</td>\n", | |
" <td> 7.213032</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>max</th>\n", | |
" <td> 1109397.000000</td>\n", | |
" <td> 3003.000000</td>\n", | |
" <td> 86399.000000</td>\n", | |
" <td> 351.000000</td>\n", | |
" <td> 351.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1.000000</td>\n", | |
" <td> 1997.000000</td>\n", | |
" <td> 759788.0000</td>\n", | |
" <td> 7.599401</td>\n", | |
" <td> 11.366731</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"</div>" | |
], | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 17, | |
"text": [ | |
" trip_id bikeid tripduration from_station_id \\\n", | |
"count 759788.000000 759788.000000 759788.000000 759788.000000 \n", | |
"mean 553984.054582 1117.964666 1239.470455 125.297671 \n", | |
"std 309503.044579 736.470219 2757.769764 86.304741 \n", | |
"min 3940.000000 1.000000 60.000000 5.000000 \n", | |
"25% 291602.500000 499.000000 473.000000 53.000000 \n", | |
"50% 549574.500000 1016.000000 821.500000 97.000000 \n", | |
"75% 816606.250000 1650.000000 1357.000000 185.000000 \n", | |
"max 1109397.000000 3003.000000 86399.000000 351.000000 \n", | |
"\n", | |
" to_station_id usertype gender birthday \\\n", | |
"count 759788.000000 759788.000000 403046.000000 402909.000000 \n", | |
"mean 124.952351 0.530458 0.790471 1976.854354 \n", | |
"std 86.188268 0.499072 0.406973 10.435801 \n", | |
"min 5.000000 0.000000 0.000000 1906.000000 \n", | |
"25% 53.000000 0.000000 1.000000 1970.000000 \n", | |
"50% 97.000000 1.000000 1.000000 1980.000000 \n", | |
"75% 181.000000 1.000000 1.000000 1985.000000 \n", | |
"max 351.000000 1.000000 1.000000 1997.000000 \n", | |
"\n", | |
" serialid log_birthday log_tripduration \n", | |
"count 759788.0000 402909.000000 759788.000000 \n", | |
"mean 379894.5000 7.589248 6.701703 \n", | |
"std 219332.0475 0.005293 0.815037 \n", | |
"min 1.0000 7.552762 4.094345 \n", | |
"25% 189947.7500 7.585789 6.159095 \n", | |
"50% 379894.5000 7.590852 6.711132 \n", | |
"75% 569841.2500 7.593374 7.213032 \n", | |
"max 759788.0000 7.599401 11.366731 " | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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AiPXa7kAMrbeAfZfe74ilJjKYcb8S2QO/j7dhM+7C9fhmm53ataYx1XYnRqjr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\nIiIiIiIiIiIiImIc/X8VeN84BM5JfwAAAABJRU5ErkJggg==\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x107ebe890>" | |
] | |
} | |
], | |
"prompt_number": 17 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The average trip duration is 1239.47 sec (20.65 minutes).\n", | |
"\n", | |
"The amount of people traveling that time averages close to 350,000." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.figure(figsize=(10,5))\n", | |
"plt.scatter(df.birthday, df.tripduration, lw=0, alpha=.05)\n", | |
"plt.xlabel(\"age\")\n", | |
"plt.ylabel(\"trip duration\")\n", | |
"#plt.xscale('log')\n", | |
"#plt.xkcd()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 6, | |
"text": [ | |
"<matplotlib.text.Text at 0x107ace450>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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SiMA/AHA/3B38gwB+f5SDEkKI/UZYey7pIVsqeU26UXQ2iZdzCV2qTHZIc8xy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\nAdexXU3eTcFA2bu3GBg8fyilHuWxM9vbo6qg3Kt/X7S1ReP4/fsjAV6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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x107eebf10>" | |
] | |
} | |
], | |
"prompt_number": 6 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The people who travel the longest are born between 1980 and 1990 on average. " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"plt.plot(df.tripduration, df.birthday, 'ro')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 28, | |
"text": [ | |
"[<matplotlib.lines.Line2D at 0x1a35d8990>]" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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EZqsQ/po/DB0KGuvm3tJSjh84AN3++JYIq6zCWcD6ri7JMD540Bht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\n5MT0fzkV9Gyq6YXcAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x1a3c47790>" | |
] | |
} | |
], | |
"prompt_number": 28 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Similar to the previous scatter plot, we could see that the majority of the \"trip durations\" fall around 1980. Explanation: younger people travel longer distances. Stipulated on personal knowledge, because I did not have the data for miles traveled :(" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df.birthday.dropna().plot(kind='kde',xlim=(1920,2010), style='g').set_title('Age of Bikeshare Users')" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 8, | |
"text": [ | |
"<matplotlib.text.Text at 0x107e5ffd0>" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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oGaHloEAfqis1ESE8bD+ynUd/fJRle5bRs2lPnu/6PO0i2zkdy1ZjE8aSnZvN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\nEEIIIYQQoiz4f4W1jwjJiBeUAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x106059250>" | |
] | |
} | |
], | |
"prompt_number": 8 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"KDE curve tells use that the most popular age among bike share users is around 1985.\n", | |
"Coincidentally that is also the age that has the longer trip durations. " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"df.boxplot(column='tripduration',by='gender',grid=True).set_ylim(0,2000)" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "pyout", | |
"prompt_number": 9, | |
"text": [ | |
"(0, 2000)" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x10f278bd0>" | |
] | |
} | |
], | |
"prompt_number": 9 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The boxplot shows that males, on average, traveled between stations faster than females, but only by a difference of about 200 seconds." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"customers = 0\n", | |
"subscribers = 0\n", | |
"for x in df.usertype:\n", | |
" if x == 0:\n", | |
" customers += 1\n", | |
" else:\n", | |
" subscribers += 1\n", | |
"\n", | |
"print \"Customers: \", customers\n", | |
"print \"Subscribers: \", subscribers" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"Customers: 356752\n", | |
"Subscribers: 403036\n" | |
] | |
} | |
], | |
"prompt_number": 10 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"fig, ax = plt.subplots(nrows=2, ncols=2,)\n", | |
"\n", | |
"ax[0, 0].hist(df.tripduration)\n", | |
"ax[0, 1].hist(np.log(df.tripduration))\n", | |
"ax[1, 0].plot(df.tripduration, df.birthday, 'ro')\n", | |
"ax[1, 1].plot(np.log(df.tripduration), df.birthday, 'ro')\n", | |
"\n", | |
"plt.show()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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jkxMScFQfNH9YHEBD8fCIeOm4qraD2oqVlmOg7SpRHzOLCLAUSbn/tbFfp7z/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\nBwcHBweHruP/A4Z9k1yC/zXQAAAAAElFTkSuQmCC\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x109818850>" | |
] | |
} | |
], | |
"prompt_number": 13 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"import statsmodels.formula.api as smf\n", | |
"# OLS, or ordinary least squares, takes a y (dependent variable) and X (independent variables) (formula = y ~ X)\n", | |
"# Below, we copy the data frame and remove the na variables, and create a single variable linear model\n", | |
"# to return a test statistic and p-value, to see how strong of a relationship bodyweight and brainweight have.\n", | |
"\n", | |
"fig, axes = plt.subplots(nrows=1,ncols=2)\n", | |
"\n", | |
"axes[0].plot(df_cleanedup.birthday, df_cleanedup.tripduration, 'go')\n", | |
"\n", | |
"model = smf.ols(formula='tripduration ~ birthday', data=df_cleanedup)\n", | |
"results = model.fit()\n", | |
"print 'NORMAL FIT SUMMARY'\n", | |
"print(results.summary())\n", | |
"print\n", | |
"\n", | |
"axes[1].plot(df_cleanedup.log_birthday, df_cleanedup.log_tripduration, 'mo')\n", | |
"\n", | |
"log_model = smf.ols(formula='log_tripduration ~ log_birthday', data=df_cleanedup)\n", | |
"log_results = log_model.fit()\n", | |
"print 'LOG-LOG FIT SUMMARY'\n", | |
"print(log_results.summary())\n", | |
"\n", | |
"print fig" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"NORMAL FIT SUMMARY\n", | |
" OLS Regression Results \n", | |
"==============================================================================\n", | |
"Dep. Variable: tripduration R-squared: 0.000\n", | |
"Model: OLS Adj. R-squared: -0.000\n", | |
"Method: Least Squares F-statistic: 0.5395\n", | |
"Date: Wed, 01 Oct 2014 Prob (F-statistic): 0.463\n", | |
"Time: 12:44:09 Log-Likelihood: -3.5077e+06\n", | |
"No. Observations: 402909 AIC: 7.015e+06\n", | |
"Df Residuals: 402907 BIC: 7.015e+06\n", | |
"Df Model: 1 \n", | |
"==============================================================================\n", | |
" coef std err t P>|t| [95.0% Conf. Int.]\n", | |
"------------------------------------------------------------------------------\n", | |
"Intercept 1042.5152 436.107 2.391 0.017 187.758 1897.272\n", | |
"birthday -0.1620 0.221 -0.735 0.463 -0.594 0.270\n", | |
"==============================================================================\n", | |
"Omnibus: 1086480.791 Durbin-Watson: 1.981\n", | |
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 32178292664.795\n", | |
"Skew: 33.374 Prob(JB): 0.00\n", | |
"Kurtosis: 1385.860 Cond. No. 3.74e+05\n", | |
"==============================================================================\n", | |
"\n", | |
"Warnings:\n", | |
"[1] The condition number is large, 3.74e+05. This might indicate that there are\n", | |
"strong multicollinearity or other numerical problems." | |
] | |
}, | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"\n", | |
"\n", | |
"LOG-LOG FIT SUMMARY" | |
] | |
}, | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"\n", | |
" OLS Regression Results \n", | |
"==============================================================================\n", | |
"Dep. Variable: log_tripduration R-squared: 0.001\n", | |
"Model: OLS Adj. R-squared: 0.001\n", | |
"Method: Least Squares F-statistic: 369.3\n", | |
"Date: Wed, 01 Oct 2014 Prob (F-statistic): 2.96e-82\n", | |
"Time: 12:44:10 Log-Likelihood: -4.0033e+05\n", | |
"No. Observations: 402909 AIC: 8.007e+05\n", | |
"Df Residuals: 402907 BIC: 8.007e+05\n", | |
"Df Model: 1 \n", | |
"================================================================================\n", | |
" coef std err t P>|t| [95.0% Conf. Int.]\n", | |
"--------------------------------------------------------------------------------\n", | |
"Intercept 34.6978 1.476 23.502 0.000 31.804 37.592\n", | |
"log_birthday -3.7382 0.195 -19.216 0.000 -4.119 -3.357\n", | |
"==============================================================================\n", | |
"Omnibus: 16662.467 Durbin-Watson: 1.885\n", | |
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 48472.758\n", | |
"Skew: 0.152 Prob(JB): 0.00\n", | |
"Kurtosis: 4.672 Cond. No. 1.11e+04\n", | |
"==============================================================================\n", | |
"\n", | |
"Warnings:\n", | |
"[1] The condition number is large, 1.11e+04. This might indicate that there are\n", | |
"strong multicollinearity or other numerical problems." | |
] | |
}, | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
"\n", | |
"Figure(480x320)\n" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": 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8nPYx4Y36S4cdO4EEqlqfAiRXJdMW1sb6iPWkD0xnfcR6Jv7rRFkzUTqtpbwN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\npbOKNwSR+EEq1jTWVaZ9oxCheSGGi2Udo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| |
"text": [ | |
"<matplotlib.figure.Figure at 0x113feaf50>" | |
] | |
} | |
], | |
"prompt_number": 15 | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"According to my OLS Regression Results there's no relationship between Birthday and Tripduration.\n", | |
"However, if we consider the scatter plots we could distinctly see that \n", | |
"people born between years 1980 and 1990 do seem to have longer trip durations on average.\n", | |
"The longer trip durations for the young as opposed to the shorter ones for the elders could\n", | |
"be explained by the distance traveled and not the speed. Younger individuals travel\n", | |
"longer distances and elders travel shorter distances causing the tripduration to actually be\n", | |
"longer for the younger and shorter fot the older. Unfortunately, I do not have the miles traveled.\n", | |
"So this is merely my assumption. Sorry :(\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"How can I use this data " | |
] | |
} | |
], | |
"metadata": {} | |
} | |
] | |
} |
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