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# pandas.api.typing.Resampler.first

final Resampler.first(numeric_only=False, min_count=0, skipna=True)

  Compute the first non-null entry of each column.

  This method returns the first value encountered in each resampled time period, skipping missing values by default.

  Parameters:
    numeric_only bool, default False

      Include only float, int, boolean columns.

    min_count int, default 0

      The required number of valid values to perform the operation. If fewer than `min_count` non-NA values are present the result will be NA.

    skipna bool, default True

      Exclude NA/null values. If an entire group is NA, the result will be NA.

  Returns:
    Series or DataFrame

      First values within each group.

  See also

  `core.resample.Resampler.last`

    Compute the last non-null value in each group.

  `core.resample.Resampler.mean`

    Compute mean of groups, excluding missing values.

  Examples

      >>> s = pd.Series(
      ...     [1, 2, 3, 4],
      ...     index=pd.DatetimeIndex(
      ...         ["2023-01-01", "2023-01-15", "2023-02-01", "2023-02-15"]
      ...     ),
      ... )
      >>> s
      2023-01-01    1
      2023-01-15    2
      2023-02-01    3
      2023-02-15    4
      dtype: int64
      >>> s.resample("MS").first()
      2023-01-01    1
      2023-02-01    3
      Freq: MS, dtype: int64