map（）函数在Python的Lambda函数内部如何工作？

Question

Can someone please explain what is actually going on in aggfunc here -

df.pivot_table(values='Loan_Status', index=['Credit_History'],
               aggfunc=lambda x: x.map({'Y':1,'N':0}).mean())

Thank you

Answer 1

Below example should illustrate what's happening. The Loan_Status values are aggregated by Credit_History according to the logic "add up number of Y's and divide by total number of observations".

import pandas as pd

df = pd.DataFrame([['Y', 'A'], ['N', 'B'], ['Y', 'C'], ['N', 'A'], ['Y', 'C']],
                  columns=['Loan_Status', 'Credit_History'])

df.pivot_table(values='Loan_Status', index=['Credit_History'],
               aggfunc=lambda x: x.map({'Y':1,'N':0}).mean())

#                 Loan_Status
# Credit_History             
# A                       0.5
# B                       0.0
# C                       1.0