如何让熊猫知道假期？

Question

I've been looking at the documentation here

I have a dataframe which contains a daily time series (Note that 2013-03-29 is a holiday and mydf contains 2013-03-28).

import pandas as pd

business_month_end_dates = pd.date_range('2010-01-31', '2014-04-30', freq='BM')

business_month_end_dates

DatetimeIndex(['2010-02-26', '2010-03-31', '2010-04-30', '2010-05-31',
           '2010-06-30', '2010-07-30', '2010-08-31', '2010-09-30',
           '2010-10-29', '2010-11-30', '2010-12-31', '2011-01-31',
           '2011-02-28', '2011-03-31', '2011-04-29', '2011-05-31',
           '2011-06-30', '2011-07-29', '2011-08-31', '2011-09-30',
           '2011-10-31', '2011-11-30', '2011-12-30', '2012-01-31',
           '2012-02-29', '2012-03-30', '2012-04-30', '2012-05-31',
           '2012-06-29', '2012-07-31', '2012-08-31', '2012-09-28',
           '2012-10-31', '2012-11-30', '2012-12-31', '2013-01-31',
           '2013-02-28', '2013-03-29', '2013-04-30', '2013-05-31',
           '2013-06-28', '2013-07-31', '2013-08-30', '2013-09-30',
           '2013-10-31', '2013-11-29', '2013-12-31', '2014-01-31',
           '2014-02-28', '2014-03-31', '2014-04-30'],
          dtype='datetime64[ns]', freq='BM')

I then create Business Year End Dates:

business_year_end_dates =  pd.date_range(business_month_end_dates[0],
                                 business_month_end_dates[len(business_month_end_dates)-1],
                                 freq=BYearEnd(month=3))

business_year_end_dates

DatetimeIndex(['2010-03-31', '2011-03-31', '2012-03-30', '2013-03-29',
           '2014-03-31'],
          dtype='datetime64[ns]', freq='BA-MAR')

My expected output is :

DatetimeIndex(['2010-03-31', '2011-03-31', '2012-03-30', '2013-03-28',
       '2014-03-31'],
      dtype='datetime64[ns]', freq='BA-MAR')

Should Pandas understand via BM business month end frequency that the 2013-03-29 is a holiday?

If not how do I make Pandas aware such that when I use BM it uses the previous working day in this case 2013-03-28?

Answer 1

Try something like this:

import numpy as np
import pandas as pd
from pandas.tseries.offsets import CustomBusinessMonthEnd

index = pd.date_range('2010-01-31', '2014-04-30', freq='BM')
df = pd.DataFrame(data=np.random.rand(len(index), 2), columns=['a', 'b'], index=index)

holidays = ['2013-03-29']

df = df.resample(rule=CustomBusinessMonthEnd(holidays=holidays)).last()

df = df.loc[df.index.month==3]

Output:

>>>df.index
>>>DatetimeIndex(['2010-03-31', '2011-03-31', '2012-03-30', '2013-03-28', '2014-03-31'], dtype='datetime64[ns]', freq='12CBM')