# get feature importances from a model
import matplotlib.pyplot as plt
def plotFeatureImportances(model):
    #first print all features importances in descending order
    feature_importances = pd.DataFrame(model.feature_importances_,
                                   index = X.columns,
                                    columns=['importance']).sort_values('importance',ascending=False)
    print(feature_importances)
    # Next plot feature importances to get idea about where the curve breaks
    # in the graph i.e. select top appropriate features
    features = X.columns.tolist()
    importances = model.feature_importances_
    indices = np.argsort(importances)
    plt.title('Feature Importances')
    plt.barh(range(len(indices)), importances[indices], color='b', align='center')
    plt.yticks(range(len(indices)), [features[i] for i in indices])
    plt.xlabel('Relative Importance')
    plt.show()