pandas.period_range#

pandas.period_range(start=None, end=None, periods=None, freq=None, name=None)[source]#

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: A PeriodIndex of fixed frequency periods.

See also

date_range: Returns a fixed frequency DatetimeIndex.
Period: Represents a period of time.
PeriodIndex: Immutable ndarray holding ordinal values indicating regular periods in time.

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]')