# pandas.bdate_range

pandas.bdate_range(start=None, end=None, periods=None, freq='B', tz=None, normalize=True, name=None, weekmask=None, holidays=None, closed=None, **kwargs)

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

  Parameters
    start str or datetime-like, default None

      Left bound for generating dates.

    end str or datetime-like, default None

      Right bound for generating dates.

    periods int, default None

      Number of periods to generate.

    freq str or DateOffset, default ‘B’ (business daily)

      Frequency strings can have multiples, e.g. ‘5H’.

    tz str or None

      Time zone name for returning localized DatetimeIndex, for example Asia/Beijing.

    normalize bool, default False

      Normalize start/end dates to midnight before generating date range.

    name str, default None

      Name of the resulting DatetimeIndex.

    weekmask str 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’.

    holidays list-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.

    closed str, default None

      Make the interval closed with respect to the given frequency to the ‘left’, ‘right’, or both sides (None).

    **kwargs

      For compatibility. Has no effect on the result.

  Returns
    DatetimeIndex

  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')