def get_node_colors_by_attr(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none'):
    """
    Get a list of node colors by binning some continuous-variable attribute into
    quantiles.

    Parameters
    ----------
    G : networkx multidigraph
    attr : string
        the name of the attribute
    num_bins : int
        how many quantiles (default None assigns each node to its own bin)
    cmap : string
        name of a colormap
    start : float
        where to start in the colorspace
    stop : float
        where to end in the colorspace
    na_color : string
        what color to assign nodes with null attribute values

    Returns
    -------
    list
    """
    if num_bins is None:
        num_bins=len(G.nodes())
    bin_labels = range(num_bins)
    attr_values = pd.Series([data[attr] for node, data in G.nodes(data=True)])
    cats = pd.qcut(x=attr_values, q=num_bins, labels=bin_labels)
    colors = get_colors(num_bins, cmap, start, stop)
    node_colors = [colors[int(cat)] if pd.notnull(cat) else na_color for cat in cats]
    return node_colors
Get a list of node colors by binning some continuous-variable attribute into
    quantiles.

    Parameters
    ----------
    G : networkx multidigraph
    attr : string
        the name of the attribute
    num_bins : int
        how many quantiles (default None assigns each node to its own bin)
    cmap : string
        name of a colormap
    start : float
        where to start in the colorspace
    stop : float
        where to end in the colorspace
    na_color : string
        what color to assign nodes with null attribute values

    Returns
    -------
    list