pandas.arrays.PeriodArray#
- class pandas.arrays.PeriodArray(values, dtype=None, freq=None, copy=False)[source]#
- Pandas ExtensionArray for storing Period data. - Users should use - array()to create new instances.- Parameters:
- valuesUnion[PeriodArray, Series[period], ndarray[int], PeriodIndex]
- The data to store. These should be arrays that can be directly converted to ordinals without inference or copy (PeriodArray, ndarray[int64]), or a box around such an array (Series[period], PeriodIndex). 
- dtypePeriodDtype, optional
- A PeriodDtype instance from which to extract a freq. If both freq and dtype are specified, then the frequencies must match. 
- freqstr or DateOffset
- The freq to use for the array. Mostly applicable when values is an ndarray of integers, when freq is required. When values is a PeriodArray (or box around), it’s checked that - values.freqmatches freq.
- copybool, default False
- Whether to copy the ordinals before storing. 
 
 - See also - Period
- Represents a period of time. 
- PeriodIndex
- Immutable Index for period data. 
- period_range
- Create a fixed-frequency PeriodArray. 
- array
- Construct a pandas array. 
 - Notes - There are two components to a PeriodArray - ordinals : integer ndarray 
- freq : pd.tseries.offsets.Offset 
 - The values are physically stored as a 1-D ndarray of integers. These are called “ordinals” and represent some kind of offset from a base. - The freq indicates the span covered by each element of the array. All elements in the PeriodArray have the same freq. - Examples - >>> pd.arrays.PeriodArray(pd.PeriodIndex(['2023-01-01', ... '2023-01-02'], freq='D')) <PeriodArray> ['2023-01-01', '2023-01-02'] Length: 2, dtype: period[D] - Attributes - None - Methods - None