如何在 pandas 中使用 groupby 或 pivot_table

Question

I have a dataframe in which i have four columns id,opposition,innings and wickets. I want to group by innings and opposition and want the sum of wicket and count of opposition.

consider this is my dataframe.

and my required output of the dataframe should be

The wickets column is the sum of wickets group by innings and opposition, and the match_play is the count of opposition group by opposition and innings.

I have tried with pivot table but got 'Opposition' not 1-dimensional

table = inn.pivot_table(values=['Opposition', 'Wickets'], index=['Opposition', 'Inning_no'],
                    aggfunc=['count','sum'])

Answer 1

Just use .groupby() on a dataframe. And reset_index() to convert Opposition and Innings to normal columns again (they are converted to multiindex during groupby )

import pandas as pd

df = pd.DataFrame({'id':[1,2,3,4,5], 'Opposition':['Sri Lanka', 'Sri Lanka', 'UAE','UAE','Sri Lanka'],
                   'Innings':[1,2,1,2,1], 'Wickets':[13,17,14,18,29]})

t = df.groupby(['Opposition', 'Innings'])['Wickets'].agg(Wickets=('sum'),
                                                         Match_play=('count')).reset_index()
print(t)

Output:

  Opposition  Innings  Wickets  Match_play
0  Sri Lanka        1       42           2
1  Sri Lanka        2       17           1
2        UAE        1       14           1
3        UAE        2       18           1