pandas.DatetimeIndex.is_year_start — pandas 3.0.0rc0+33.g1fd184de2a documentation (original) (raw)

property DatetimeIndex.is_year_start[source]#

Indicate whether the date is the first day of a year.

Returns:

Series or DatetimeIndex

The same type as the original data with boolean values. Series will have the same name and index. DatetimeIndex will have the same name.

See also

is_year_end

Similar property indicating the last day of the year.

Examples

This method is available on Series with datetime values under the .dt accessor, and directly on DatetimeIndex.

dates = pd.Series(pd.date_range("2017-12-30", periods=3)) dates 0 2017-12-30 1 2017-12-31 2 2018-01-01 dtype: datetime64[us]

dates.dt.is_year_start 0 False 1 False 2 True dtype: bool

idx = pd.date_range("2017-12-30", periods=3) idx DatetimeIndex(['2017-12-30', '2017-12-31', '2018-01-01'], dtype='datetime64[us]', freq='D')

idx.is_year_start array([False, False, True])

This method, when applied to Series with datetime values under the .dt accessor, will lose information about Business offsets.

dates = pd.Series(pd.date_range("2020-10-30", periods=4, freq="BYS")) dates 0 2021-01-01 1 2022-01-03 2 2023-01-02 3 2024-01-01 dtype: datetime64[us]

dates.dt.is_year_start 0 True 1 False 2 False 3 True dtype: bool

idx = pd.date_range("2020-10-30", periods=4, freq="BYS") idx DatetimeIndex(['2021-01-01', '2022-01-03', '2023-01-02', '2024-01-01'], dtype='datetime64[us]', freq='BYS-JAN')

idx.is_year_start array([ True, True, True, True])