def scatterviz(X,
               y=None,
               ax=None,
               features=None,
               classes=None,
               color=None,
               colormap=None,
               markers=None,
               alpha=1.0,
               **kwargs):
    """Displays a bivariate scatter plot.

    This helper function is a quick wrapper to utilize the ScatterVisualizer
    (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, default: None
        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 two features or columns.
        More than that will raise an error.

    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

    markers : iterable of strings, default: ,+o*vhd
        Matplotlib style markers for points on the scatter plot points

    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 = ScatterVisualizer(ax=ax, features=features, classes=classes,
                                   color=color, colormap=colormap,
                                   markers=markers, alpha=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
Displays a bivariate scatter plot.

    This helper function is a quick wrapper to utilize the ScatterVisualizer
    (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, default: None
        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 two features or columns.
        More than that will raise an error.

    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

    markers : iterable of strings, default: ,+o*vhd
        Matplotlib style markers for points on the scatter plot points

    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.