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# pandas.Series.dt.is_year_start

Series.dt.is_year_start

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

  This boolean attribute evaluates to True if the date is January 1st, and False otherwise.

  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])