Method stack

pandas/core/frame.py:11176–11380

Stack the prescribed level(s) from columns to index. Return a reshaped DataFrame or Series having a multi-level index with one or more new inner-most levels compared to the current DataFrame. The new inner-most levels are created by pivoting the columns of t

(
        self,
        level: IndexLabel = -1,
        dropna: bool | lib.NoDefault = lib.no_default,
        sort: bool | lib.NoDefault = lib.no_default,
        future_stack: bool = True,
    )

        )

    def stack(
        self,
        level: IndexLabel = -1,
        dropna: bool | lib.NoDefault = lib.no_default,
        sort: bool | lib.NoDefault = lib.no_default,
        future_stack: bool = True,
    ):
        """
        Stack the prescribed level(s) from columns to index.

        Return a reshaped DataFrame or Series having a multi-level
        index with one or more new inner-most levels compared to the current
        DataFrame. The new inner-most levels are created by pivoting the
        columns of the current dataframe:

        - if the columns have a single level, the output is a Series;
        - if the columns have multiple levels, the new index level(s) is (are)
          taken from the prescribed level(s) and the output is a DataFrame.

        Parameters
        ----------
        level : int, str, list, default -1
            Level(s) to stack from the column axis onto the index
            axis, defined as one index or label, or a list of indices
            or labels.
        dropna : bool, default True
            Whether to drop rows in the resulting Frame/Series with
            missing values. Stacking a column level onto the index
            axis can create combinations of index and column values
            that are missing from the original dataframe. See Examples
            section.
        sort : bool, default True
            Whether to sort the levels of the resulting MultiIndex.
        future_stack : bool, default True
            Whether to use the new implementation that will replace the current
            implementation in pandas 3.0. When True, dropna and sort have no impact
            on the result and must remain unspecified. See :ref:`pandas 2.1.0 Release
            notes <whatsnew_210.enhancements.new_stack>` for more details.

        Returns
        -------
        DataFrame or Series
            Stacked dataframe or series.

        See Also
        --------
        DataFrame.unstack : Unstack prescribed level(s) from index axis
             onto column axis.
        DataFrame.pivot : Reshape dataframe from long format to wide
             format.
        DataFrame.pivot_table : Create a spreadsheet-style pivot table
             as a DataFrame.

        Notes
        -----
        The function is named by analogy with a collection of books
        being reorganized from being side by side on a horizontal
        position (the columns of the dataframe) to being stacked