def plot_feature_importances(X, outputTable, labels, numEstimators = 50, numTopFeatures = 7):
"""
plots feature importances using random forest
@param X: X data
@param outputTable: a pandas data frame with columns being A,..,G
@param labels: column labels
@param numEstimators: n_estimators to use for RF
@param numTopFeatures: number of features to show
"""
for col in outputTable.columns:
print '-'*10, col
y = outputTable[col]
rf = RandomForester(num_features = X.shape[1], n_estimators = numEstimators)
rf.fit(X, y)
rf.plot(num_features=numTopFeatures, labels=labels)
print rf.top_indices(labels=labels)[1]
