Function _generate_marginal_results

pandas/core/reshape/pivot.py:536–629

(
    table,
    data: DataFrame,
    values,
    rows,
    cols,
    aggfunc,
    kwargs,
    observed: bool,
    margins_name: Hashable = "All",
    dropna: bool = True,
)

def _generate_marginal_results(
    table,
    data: DataFrame,
    values,
    rows,
    cols,
    aggfunc,
    kwargs,
    observed: bool,
    margins_name: Hashable = "All",
    dropna: bool = True,
):
    margin_keys: list | Index
    if len(cols) > 0:
        # need to "interleave" the margins
        table_pieces = []
        margin_keys = []

        def _all_key(key):
            return (key, margins_name) + ("",) * (len(cols) - 1)

        if len(rows) > 0:
            margin = (
                data[rows + values]
                .groupby(rows, observed=observed, dropna=dropna)
                .agg(aggfunc, **kwargs)
            )
            cat_axis = 1

            for key, piece in table.T.groupby(level=0, observed=observed):
                piece = piece.T
                all_key = _all_key(key)

                piece[all_key] = margin[key]

                table_pieces.append(piece)
                margin_keys.append(all_key)
        else:
            margin = (
                data[cols[:1] + values]
                .groupby(cols[:1], observed=observed, dropna=dropna)
                .agg(aggfunc, **kwargs)
                .T
            )

            cat_axis = 0
            for key, piece in table.groupby(level=0, observed=observed):
                if len(cols) > 1:
                    all_key = _all_key(key)
                else:
                    all_key = margins_name
                table_pieces.append(piece)
                transformed_piece = margin[key].to_frame().T
                if isinstance(piece.index, MultiIndex):
                    # We are adding an empty level
                    transformed_piece.index = MultiIndex.from_tuples(
                        [all_key],
                        names=[*piece.index.names, None],