plot_imps.txt

def plot_importance(tree, X_train, top_n=10, figsize=(10,10), ax=None):
    
    """Takes in pre-fit descision tree and the training X data used. Will output
    a horizontal bar plot (.plt) of the top 10 (default) features used in said tree."""
    
    ## Imports
    import pandas as pd
    import matplotlib as plt

    ## Generate feature importances + store into series with correct column names 
    imps = pd.Series(tree.feature_importances_,index=X_train.columns)
    
    ## Sort values s.t. "top_n" importances display in horizontal bar graph
    imps.sort_values(ascending=True).tail(top_n).plot(kind='barh',figsize=figsize, ax=ax)
    return imps