Method combine_first

pandas/core/frame.py:10365–10439

Update null elements with value in the same location in `other`. Combine two DataFrame objects by filling null values in one DataFrame with non-null values from other DataFrame. The row and column indexes of the resulting DataFrame will be the union of the two. The

(self, other: DataFrame)

        return frame_result.__finalize__(self, method="combine")

    def combine_first(self, other: DataFrame) -> DataFrame:
        """
        Update null elements with value in the same location in `other`.

        Combine two DataFrame objects by filling null values in one DataFrame
        with non-null values from other DataFrame. The row and column indexes
        of the resulting DataFrame will be the union of the two. The resulting
        dataframe contains the 'first' dataframe values and overrides the
        second one values where both first.loc[index, col] and
        second.loc[index, col] are not missing values, upon calling
        first.combine_first(second).

        Parameters
        ----------
        other : DataFrame
            Provided DataFrame to use to fill null values.

        Returns
        -------
        DataFrame
            The result of combining the provided DataFrame with the other object.

        See Also
        --------
        DataFrame.combine : Perform series-wise operation on two DataFrames
            using a given function.

        Examples
        --------
        >>> df1 = pd.DataFrame({"A": [None, 0], "B": [None, 4]})
        >>> df2 = pd.DataFrame({"A": [1, 1], "B": [3, 3]})
        >>> df1.combine_first(df2)
             A    B
        0  1.0  3.0
        1  0.0  4.0

        Null values still persist if the location of that null value
        does not exist in `other`

        >>> df1 = pd.DataFrame({"A": [None, 0], "B": [4, None]})
        >>> df2 = pd.DataFrame({"B": [3, 3], "C": [1, 1]}, index=[1, 2])
        >>> df1.combine_first(df2)
             A    B    C
        0  NaN  4.0  NaN
        1  0.0  3.0  1.0
        2  NaN  3.0  1.0
        """

        def combiner(x: Series, y: Series):
            # GH#60128 The combiner is supposed to preserve EA Dtypes.
            return y if y.name not in self.columns else y.where(x.isna(), x)

        if len(other) == 0:
            combined = self.reindex(
                self.columns.append(other.columns.difference(self.columns)), axis=1
            )
            combined = combined.astype(other.dtypes)
        else: