Skip to main content
`Ctrl`+`K`

# pandas.period_range

pandas.period_range(start=None, end=None, periods=None, freq=None, name=None)

  Return a fixed frequency PeriodIndex.

  The day (calendar) is the default frequency.

  Parameters:
    startstr, datetime, date, pandas.Timestamp, or period-like, default None

      Left bound for generating periods.

    endstr, datetime, date, pandas.Timestamp, or period-like, default None

      Right bound for generating periods.

    periodsint, default None

      Number of periods to generate.

    freqstr or DateOffset, optional

      Frequency alias. By default the freq is taken from start or end if those are Period objects. Otherwise, the default is `"D"` for daily frequency.

    namestr, default None

      Name of the resulting PeriodIndex.

  Returns:
    PeriodIndex

  Notes

  Of the three parameters: `start`, `end`, and `periods`, exactly two must be specified.

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

  Examples

      >>> pd.period_range(start='2017-01-01', end='2018-01-01', freq='M')
      PeriodIndex(['2017-01', '2017-02', '2017-03', '2017-04', '2017-05', '2017-06',
               '2017-07', '2017-08', '2017-09', '2017-10', '2017-11', '2017-12',
               '2018-01'],
              dtype='period[M]')

  If `start` or `end` are `Period` objects, they will be used as anchor endpoints for a `PeriodIndex` with frequency matching that of the `period_range` constructor.

      >>> pd.period_range(start=pd.Period('2017Q1', freq='Q'),
      ...                 end=pd.Period('2017Q2', freq='Q'), freq='M')
      PeriodIndex(['2017-03', '2017-04', '2017-05', '2017-06'],
                  dtype='period[M]')