pandas.DatetimeIndex.is_year_start#

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[ns]

>>> 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[ns]', 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[ns]

>>> 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[ns]', freq='BYS-JAN')

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