Plot feature importances of a ML model

plot_feature_importances.py

def PlotFeatureImportances(model, feature_names):
    feature_importances = (pd
                           .DataFrame(
                               {'feature': feature_names,
                                'importance': model
                                .feature_importances_}))

    feature_importances = (feature_importances
                           .sort_values(by="importance",
                                        ascending=False))
    figsize(20, 10)
    plt.rcParams['font.size'] = 14
    sns.set(font_scale=1.5, style="whitegrid")

    # set color
    labels = np.array(feature_importances.feature)
    values = np.array(feature_importances.importance) 
    colors = ["#808080" if (y < max(values))
              else "#971539" for y in values]

    # set the plot
    ax = sns.barplot(x="importance", 
                     y="feature", 
                     data=feature_importances, 
                     palette = colors)

    # set title and save plot
    plt.title("Feature Importances", size =16)
    # plt.savefig("FeatureImportances.png")