code: def parallel_coordinates(
      frame: DataFrame,
      class_column: str,
      cols: list[str] | None = None,
      ax: Axes | None = None,
      color: list[str] | tuple[str, ...] | None = None,
      use_columns: bool = False,
      xticks: list | tuple | None = None,
      colormap: Colormap | str | None = None,
      axvlines: bool = True,
      axvlines_kwds: Mapping[str, Any] | None = None,
      sort_labels: bool = False,
      **kwargs,
  ) -> Axes:
      """
      Parallel coordinates plotting.
  
      Parameters
      ----------
      frame : DataFrame
      class_column : str
          Column name containing class names.
      cols : list, optional
          A list of column names to use.
      ax : matplotlib.axis, optional
          Matplotlib axis object.
      color : list or tuple, optional
          Colors to use for the different classes.
      use_columns : bool, optional
          If true, columns will be used as xticks.
      xticks : list or tuple, optional
          A list of values to use for xticks.
      colormap : str or matplotlib colormap, default None
          Colormap to use for line colors.
      axvlines : bool, optional
          If true, vertical lines will be added at each xtick.
      axvlines_kwds : keywords, optional
          Options to be passed to axvline method for vertical lines.
      sort_labels : bool, default False
          Sort class_column labels, useful when assigning colors.
      **kwargs
          Options to pass to matplotlib plotting method.
  
      Returns
      -------
      matplotlib.axes.Axes
  
      Examples
      --------
  
      .. plot::
          :context: close-figs
  
          >>> df = pd.read_csv(
          ...     'https://raw.githubusercontent.com/pandas-dev/'
          ...     'pandas/main/pandas/tests/io/data/csv/iris.csv'
          ... )
          >>> pd.plotting.parallel_coordinates(
          ...     df, 'Name', color=('#556270', '#4ECDC4', '#C7F464')
          ... )  # doctest: +SKIP
      """
      plot_backend = _get_plot_backend("matplotlib")
      return plot_backend.parallel_coordinates(
          frame=frame,
          class_column=class_column,
          cols=cols,
          ax=ax,
          color=color,
          use_columns=use_columns,
          xticks=xticks,
          colormap=colormap,
          axvlines=axvlines,
          axvlines_kwds=axvlines_kwds,
          sort_labels=sort_labels,
          **kwargs,
      )
  
imports: from __future__ import annotations
  from contextlib import contextmanager
  from typing import TYPE_CHECKING, Any
  from pandas.plotting._core import _get_plot_backend
label_desc: Use image node_id 8 for calling a global function with example usage: parallel_coordinates(frame, class_column, cols, ax, color, use_columns, xticks, colormap, axvlines, axvlines_kwds, sort_labels) and returns: plot_backend