tree_interpreter.py

from treeinterpreter import treeinterpreter as ti

for i,row in X.iterrows():

    data_point = pd.DataFrame([row])
    data_point.set_axis(['value_variable']) # Once transposed, it will be the column name
    prediction, bias, contributions = ti.predict(rf_model, data_point)
    local_interpretation = data_point.append(
	    pd.DataFrame([[round(c[1],3) for c in contributions[0]]], columns=data_point.columns.tolist(), index=['contribution_variable'])
    ).T.sort_values('contribution_variable', ascending=False)
	# print(local_interpretation)