period_array(data: 'Sequence[Period | str | None] | AnyArrayLike', freq: 'str | Tick | None' = None, copy: 'bool' = False) -> 'PeriodArray'
A sequence of Period objects. These are required to all have the same freq.
Missing values can be indicated by None
or pandas.NaT
.
The frequency of every element of the array. This can be specified to avoid inferring the :None:None:`freq` from :None:None:`data`.
Whether to ensure a copy of the data is made.
Construct a new PeriodArray from a sequence of Period scalars.
>>> period_array([pd.Period('2017', freq='A'),This example is valid syntax, but we were not able to check execution
... pd.Period('2018', freq='A')]) <PeriodArray> ['2017', '2018'] Length: 2, dtype: period[A-DEC]
>>> period_array([pd.Period('2017', freq='A'),
... pd.Period('2018', freq='A'),
... pd.NaT]) <PeriodArray> ['2017', '2018', 'NaT'] Length: 3, dtype: period[A-DEC]
Integers that look like years are handled
This example is valid syntax, but we were not able to check execution>>> period_array([2000, 2001, 2002], freq='D') <PeriodArray> ['2000-01-01', '2001-01-01', '2002-01-01'] Length: 3, dtype: period[D]
Datetime-like strings may also be passed
This example is valid syntax, but we were not able to check execution>>> period_array(['2000-Q1', '2000-Q2', '2000-Q3', '2000-Q4'], freq='Q') <PeriodArray> ['2000Q1', '2000Q2', '2000Q3', '2000Q4'] Length: 4, dtype: period[Q-DEC]See :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.arrays.period.period_array
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