pandas.bdate_range#

pandas.bdate_range(start=None, end=None, periods=None, freq='B', tz=None, normalize=True, name=None, weekmask=None, holidays=None, inclusive='both', **kwargs)[source]#

Return a fixed frequency DatetimeIndex with business day as the default.

Parameters:

startstr or datetime-like, default None: Left bound for generating dates.
endstr or datetime-like, default None: Right bound for generating dates.
periodsint, default None: Number of periods to generate.
freqstr, Timedelta, datetime.timedelta, or DateOffset, default ‘B’: Frequency strings can have multiples, e.g. ‘5h’. The default is business daily (‘B’).
tzstr or None: Time zone name for returning localized DatetimeIndex, for example Asia/Beijing.
normalizebool, default False: Normalize start/end dates to midnight before generating date range.
namestr, default None: Name of the resulting DatetimeIndex.
weekmaskstr or None, default None: Weekmask of valid business days, passed to numpy.busdaycalendar, only used when custom frequency strings are passed. The default value None is equivalent to ‘Mon Tue Wed Thu Fri’.
holidayslist-like or None, default None: Dates to exclude from the set of valid business days, passed to numpy.busdaycalendar, only used when custom frequency strings are passed.
inclusive{“both”, “neither”, “left”, “right”}, default “both”: Include boundaries; Whether to set each bound as closed or open.

Added in version 1.4.0.
**kwargs: For compatibility. Has no effect on the result.

Returns:

DatetimeIndex: Fixed frequency DatetimeIndex.

See also

date_range: Return a fixed frequency DatetimeIndex.
period_range: Return a fixed frequency PeriodIndex.
timedelta_range: Return a fixed frequency TimedeltaIndex.

Notes

Of the four parameters: start, end, periods, and freq, exactly three must be specified. Specifying freq is a requirement for bdate_range. Use date_range if specifying freq is not desired.

To learn more about the frequency strings, please see this link.

Examples

Note how the two weekend days are skipped in the result.

>>> pd.bdate_range(start="1/1/2018", end="1/08/2018")
DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',
           '2018-01-05', '2018-01-08'],
          dtype='datetime64[ns]', freq='B')

pandas.bdate_range#

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