def parallel_coordinates(frame, class_column, cols=None, ax=None, color=None,
                         use_columns=False, xticks=None, colormap=None,
                         axvlines=True, axvlines_kwds=None, sort_labels=False,
                         **kwds):
    """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, False
        Sort class_column labels, useful when assigning colors

        .. versionadded:: 0.20.0

    kwds : keywords
        Options to pass to matplotlib plotting method

    Returns
    -------
    class:`matplotlib.axis.Axes`

    Examples
    --------
    >>> from matplotlib import pyplot as plt
    >>> df = pd.read_csv('https://raw.github.com/pandas-dev/pandas/master'
                        '/pandas/tests/data/iris.csv')
    >>> pd.plotting.parallel_coordinates(
            df, 'Name',
            color=('#556270', '#4ECDC4', '#C7F464'))
    >>> plt.show()
    """
    if axvlines_kwds is None:
        axvlines_kwds = {'linewidth': 1, 'color': 'black'}
    import matplotlib.pyplot as plt

    n = len(frame)
    classes = frame[class_column].drop_duplicates()
    class_col = frame[class_column]

    if cols is None:
        df = frame.drop(class_column, axis=1)
    else:
        df = frame[cols]

    used_legends = set()

    ncols = len(df.columns)

    # determine values to use for xticks
    if use_columns is True:
        if not np.all(np.isreal(list(df.columns))):
            raise ValueError('Columns must be numeric to be used as xticks')
        x = df.columns
    elif xticks is not None:
        if not np.all(np.isreal(xticks)):
            raise ValueError('xticks specified must be numeric')
        elif len(xticks) != ncols:
            raise ValueError('Length of xticks must match number of columns')
        x = xticks
    else:
        x = lrange(ncols)

    if ax is None:
        ax = plt.gca()

    color_values = _get_standard_colors(num_colors=len(classes),
                                        colormap=colormap, color_type='random',
                                        color=color)

    if sort_labels:
        classes = sorted(classes)
        color_values = sorted(color_values)
    colors = dict(zip(classes, color_values))

    for i in range(n):
        y = df.iloc[i].values
        kls = class_col.iat[i]
        label = pprint_thing(kls)
        if label not in used_legends:
            used_legends.add(label)
            ax.plot(x, y, color=colors[kls], label=label, **kwds)
        else:
            ax.plot(x, y, color=colors[kls], **kwds)

    if axvlines:
        for i in x:
            ax.axvline(i, **axvlines_kwds)

    ax.set_xticks(x)
    ax.set_xticklabels(df.columns)
    ax.set_xlim(x[0], x[-1])
    ax.legend(loc='upper right')
    ax.grid()
    return ax