Pandas Series: dt.to_period() function

Series.dt.to_period() function

Cast to PeriodArray/Index at a particular frequency.

Converts DatetimeArray/Index to PeriodArray/Index.

Syntax:

Series.dt.to_period(self, *args, **kwargs)

Parameter:

Returns: PeriodArray/Index

Raises: ValueError
When converting a DatetimeArray/Index with non-regular values, so that a frequency cannot be inferred.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
df = pd.DataFrame({"y": [1, 2, 3]},
                  index=pd.to_datetime(["2019-03-31 00:00:00",
                                        "2019-05-31 00:00:00",
                                        "2019-08-31 00:00:00"]))
df.index.to_period("M")

Output:

PeriodIndex(['2019-03', '2019-05', '2019-08'], dtype='period[M]', freq='M')

Example - Infer the daily frequency:

Python-Pandas Code:

import numpy as np
import pandas as pd
idx = pd.date_range("2019-01-01", periods=2)
idx.to_period()

Output:

PeriodIndex(['2019-01-01', '2019-01-02'], dtype='period[D]', freq='D')

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