In [1]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#from timeConversion import secondsToHuman
%matplotlib inline


    

In [2]:

    

data = pd.read_csv('../data/UW_Trip_Data_4mo_QC_capacity.csv')
broken = pd.read_csv('../data/4mo_broken_buses.csv')


    

    




//anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py:2717: DtypeWarning: Columns (3) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)

In [3]:

    

pd.to_datetime(data.ServiceDate, coerce=True)
data = data.set_index(data.ServiceDate)


    

    




/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: the coerce=True keyword is deprecated, use errors='coerce' instead
  if __name__ == '__main__':

In [4]:

    

dates = data.ServiceDate.drop_duplicates()
dates = dates.apply(lambda x: '2' + x[1:])
dates.index = range(len(dates))
dates.sort()
data.ServiceDate = data.ServiceDate.apply(lambda x: '2' + x[1:])


    

    




/anaconda/lib/python2.7/site-packages/ipykernel/__main__.py:4: FutureWarning: sort is deprecated, use sort_values(inplace=True) for INPLACE sorting

In [5]:

    

def AvTime(code):
    pickupTimes = data[(data.Activity == code) & (data.ETA < 86400)]
    avTime = dates.apply(lambda x: sum(pickupTimes[pickupTimes.ServiceDate == x].ETA)/float(len(pickupTimes[pickupTimes.ServiceDate == x])))
    avTime.index=dates
    avTime = avTime / 3600.0
    return avTime


    

In [6]:

    

AvTime(4).plot()
AvTime(3).plot()


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x101163790>






    

In [7]:

    

(AvTime(3)-AvTime(4)).plot()


    

    
Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x10ef61590>






    

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