def radviz(X, y=None, ax=None, features=None, classes=None,
           color=None, colormap=None, alpha=1.0, **kwargs):
    """
    Displays each feature as an axis around a circle surrounding a scatter
    plot whose points are each individual instance.

    This helper function is a quick wrapper to utilize the RadialVisualizer
    (Transformer) for one-off analysis.

    Parameters
    ----------

    X : ndarray or DataFrame of shape n x m
        A matrix of n instances with m features

    y : ndarray or Series of length n
        An array or series of target or class values

    ax : matplotlib Axes, default: None
        The axes to plot the figure on.

    features : list of strings, default: None
        The names of the features or columns

    classes : list of strings, default: None
        The names of the classes in the target

    color : list or tuple of colors, default: None
        Specify the colors for each individual class

    colormap : string or matplotlib cmap, default: None
        Sequential colormap for continuous target

    alpha : float, default: 1.0
        Specify a transparency where 1 is completely opaque and 0 is completely
        transparent. This property makes densely clustered points more visible.

    Returns
    -------
    ax : matplotlib axes
        Returns the axes that the parallel coordinates were drawn on.
    """
    # Instantiate the visualizer
    visualizer = RadialVisualizer(
        ax, features, classes, color, colormap, alpha, **kwargs
    )

    # Fit and transform the visualizer (calls draw)
    visualizer.fit(X, y, **kwargs)
    visualizer.transform(X)

    # Return the axes object on the visualizer
    return visualizer.ax