Method _get_index_name

pandas/io/parsers/python_parser.py:1104–1179

Try several cases to get lines: 0) There are headers on row 0 and row 1 and their total summed lengths equals the length of the next line. Treat row 0 as columns and row 1 as indices 1) Look for implicit index: there are more columns on row 1 than ro

(
        self,
    )

        )

    def _get_index_name(
        self,
    ) -> tuple[Sequence[Hashable] | None, list[Hashable], list[Hashable]]:
        """
        Try several cases to get lines:

        0) There are headers on row 0 and row 1 and their
        total summed lengths equals the length of the next line.
        Treat row 0 as columns and row 1 as indices
        1) Look for implicit index: there are more columns
        on row 1 than row 0. If this is true, assume that row
        1 lists index columns and row 0 lists normal columns.
        2) Get index from the columns if it was listed.
        """
        columns: Sequence[Hashable] = self.orig_names
        orig_names = list(columns)
        columns = list(columns)

        line: list[Scalar] | None
        if self._header_line is not None:
            line = self._header_line
        else:
            try:
                line = self._next_line()
            except StopIteration:
                line = None

        next_line: list[Scalar] | None
        try:
            next_line = self._next_line()
        except StopIteration:
            next_line = None

        # implicitly index_col=0 b/c 1 fewer column names
        implicit_first_cols = 0
        if line is not None:
            # leave it 0, #2442
            # Case 1
            index_col = self.index_col
            if index_col is not False:
                implicit_first_cols = len(line) - self.num_original_columns

            # Case 0
            if (
                next_line is not None
                and self.header is not None
                and index_col is not False
            ):
                if len(next_line) == len(line) + self.num_original_columns:
                    # column and index names on diff rows
                    self.index_col = list(range(len(line)))
                    self.buf = self.buf[1:]

                    for c in reversed(line):
                        columns.insert(0, c)

                    # Update list of original names to include all indices.
                    orig_names = list(columns)