Python Pandas：根据其他列中的唯一标识符创建具有最小值的新列

Question

I have a dataframe:

pd.DataFrame({'person':['x', 'x', 'x', 'x', 'y', 'y', 'y', 'y'], 
              'bank':['chase', 'bod', 'chase', 'boa', 'chase', 'bod', 'chase', 'boa'],
              'amount': [100, 80, 90, 60, 150, 111, 524, 51]})

Assuming there could be many people in the "person" column. But there are only "chase" and "boa" in the "bank" column. Every person will have both "chase" and "boa". For each person, I want to get the minimum number in the "amount" column for each bank. The output will be like this:

Each row should have the person, min amount in chase ("chase_min") and min amount in boa ("boa_min").

Thank you!

Answer 1

You can use min() as the aggfunc for a pivot table.

pd.pivot_table(df, index='person', columns=['bank'], values='amount', aggfunc='min')

Answer 2

I think the current answer is overkill, and this solution has the advantage of producing a convenient index:

import pandas as pd

df = pd.DataFrame({'person': ['x', 'x', 'x', 'x', 'y', 'y', 'y', 'y'],
                   'bank': ['chase', 'bod', 'chase', 'boa', 'chase', 'bod', 'chase', 'boa'],
                   'amount': [100, 80, 90, 60, 150, 111, 524, 51]})

res = df.groupby(["person", "bank"]).min()

print(f"{df}\n\n{res}")

Output:

  person   bank  amount
0      x  chase     100
1      x    bod      80
2      x  chase      90
3      x    boa      60
4      y  chase     150
5      y    bod     111
6      y  chase     524
7      y    boa      51

              amount
person bank         
x      boa        60
       bod        80
       chase      90
y      boa        51
       bod       111
       chase     150