rfc_vs_dt-10.py

feature_importance=pd.DataFrame({
    'rfc':rfc.feature_importances_,
    'dt':dt.feature_importances_
},index=df.drop(columns=['Loan_ID','Loan_Status']).columns)
feature_importance.sort_values(by='rfc',ascending=True,inplace=True)

index = np.arange(len(feature_importance))
fig, ax = plt.subplots(figsize=(18,8))
rfc_feature=ax.barh(index,feature_importance['rfc'],0.4,color='purple',label='Random Forest')
dt_feature=ax.barh(index+0.4,feature_importance['dt'],0.4,color='lightgreen',label='Decision Tree')
ax.set(yticks=index+0.4,yticklabels=feature_importance.index)

ax.legend()
plt.show()