Method explode

pandas/core/frame.py:11382–11509

Transform each element of a list-like to a row, replicating index values. Parameters ---------- column : IndexLabel Column(s) to explode. For multiple columns, specify a non-empty list with each element be str or tuple, and all sp

(
        self,
        column: IndexLabel,
        ignore_index: bool = False,
    )

        return result.__finalize__(self, method="stack")

    def explode(
        self,
        column: IndexLabel,
        ignore_index: bool = False,
    ) -> DataFrame:
        """
        Transform each element of a list-like to a row, replicating index values.

        Parameters
        ----------
        column : IndexLabel
            Column(s) to explode.
            For multiple columns, specify a non-empty list with each element
            be str or tuple, and all specified columns their list-like data
            on same row of the frame must have matching length.

        ignore_index : bool, default False
            If True, the resulting index will be labeled 0, 1, …, n - 1.

        Returns
        -------
        DataFrame
            Exploded lists to rows of the subset columns;
            index will be duplicated for these rows.

        Raises
        ------
        ValueError :
            * If columns of the frame are not unique.
            * If specified columns to explode is empty list.
            * If specified columns to explode have not matching count of
              elements rowwise in the frame.

        See Also
        --------
        DataFrame.unstack : Pivot a level of the (necessarily hierarchical)
            index labels.
        DataFrame.melt : Unpivot a DataFrame from wide format to long format.
        Series.explode : Explode a DataFrame from list-like columns to long format.

        Notes
        -----
        This routine will explode list-likes including lists, tuples, sets,
        Series, and np.ndarray. The result dtype of the subset rows will
        be object. Scalars will be returned unchanged, and empty list-likes will
        result in a np.nan for that row. In addition, the ordering of rows in the
        output will be non-deterministic when exploding sets.

        Reference :ref:`the user guide <reshaping.explode>` for more examples.

        Examples
        --------
        >>> df = pd.DataFrame(
        ...     {
        ...         "A": [[0, 1, 2], "foo", [], [3, 4]],
        ...         "B": 1,
        ...         "C": [["a", "b", "c"], np.nan, [], ["d", "e"]],
        ...     }