Get business days between start and end date using pandas

You can also use date_range for this purpose.

In [3]: pd.date_range('2011-01-05', '2011-01-09', freq=BDay())

Out[3]: DatetimeIndex(['2011-01-05', '2011-01-06', '2011-01-07'], dtype='datetime64[ns]', freq='B', tz=None)

EDIT

Or even simpler

In [7]: pd.bdate_range('2011-01-05', '2011-01-09')

Out[7]: DatetimeIndex(['2011-01-05', '2011-01-06', '2011-01-07'], dtype='datetime64[ns]', freq='B', tz=None)

Note that both start and end dates are inclusive. Source: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.bdate_range.html


As of v0.14 you can use holiday calendars.

from pandas.tseries.holiday import USFederalHolidayCalendar
from pandas.tseries.offsets import CustomBusinessDay

us_bd = CustomBusinessDay(calendar=USFederalHolidayCalendar())
print pd.DatetimeIndex(start='2010-01-01',end='2010-01-15', freq=us_bd)

returns:

DatetimeIndex(['2010-01-04', '2010-01-05', '2010-01-06', '2010-01-07',
               '2010-01-08', '2010-01-11', '2010-01-12', '2010-01-13',
               '2010-01-14', '2010-01-15'],
              dtype='datetime64[ns]', freq='C')

Just be careful when using bdate_range or BDay() - the name might mislead you to think that it is a range of business days, whereas in reality it's just calendar days with weekends stripped out (ie. it doesn't take holidays into account).


Use BDay() to get the business days in range.

from pandas.tseries.offsets import *

In [185]: s
Out[185]: 
2011-01-01   -0.011629
2011-01-02   -0.089666
2011-01-03   -1.314430
2011-01-04   -1.867307
2011-01-05    0.779609
2011-01-06    0.588950
2011-01-07   -2.505803
2011-01-08    0.800262
2011-01-09    0.376406
2011-01-10   -0.469988
Freq: D

In [186]: s.asfreq(BDay())
Out[186]: 
2011-01-03   -1.314430
2011-01-04   -1.867307
2011-01-05    0.779609
2011-01-06    0.588950
2011-01-07   -2.505803
2011-01-10   -0.469988
Freq: B

With slicing:

In [187]: x=datetime(2011, 1, 5)

In [188]: y=datetime(2011, 1, 9)

In [189]: s.ix[x:y]
Out[189]: 
2011-01-05    0.779609
2011-01-06    0.588950
2011-01-07   -2.505803
2011-01-08    0.800262
2011-01-09    0.376406
Freq: D

In [190]: s.ix[x:y].asfreq(BDay())
Out[190]: 
2011-01-05    0.779609
2011-01-06    0.588950
2011-01-07   -2.505803
Freq: B

and count()

In [191]: s.ix[x:y].asfreq(BDay()).count()
Out[191]: 3

Tags:

Python

Pandas