pandas.arrays.PeriodArray

classpandas.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:

values:Union[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).

dtype:PeriodDtype, optional

A PeriodDtype instance from which to extract a freq. If both freq and dtype are specified, then the frequencies must match.

freq:str 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.freq matches freq.

copy:bool, default False

Whether to copy the ordinals before storing.

Attributes

None

Methods

None

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]