Get the name of the category corresponding to the maximum value of a column

Question

I have a pandas dataframe with football team, football players and the number of minutes played during the season.

Team	Player	Minutes played
1	a	2
1	b	10
1	c	0
2	a	28
2	b	50
2	e	7
3	c	200
3	p	10

By doing :

df['count_max'] = df.groupby(['Team'])['Minutes played'].transform(max)
df

I get a new column with the maximum number of minutes played for each team

Team	Player	Minutes played	Count_max
1	a	2	10
1	b	10	10
1	c	0	10
2	a	28	50
2	b	50	50
2	e	7	50
3	c	200	200
3	p	10	200

But instead of this information, I would like to display the letter corresponding to the player (b for 1, b for 2 and c for 3). Do you know how can I update my code to do so ?

My expected output is :

Team	Player	Minutes played	Count_max
1	a	2	b
1	b	10	b
1	c	0	b
2	a	28	b
2	b	50	b
2	e	7	b
3	c	200	c
3	p	10	c

Answer 1

You can use idxmax in transform and map the index to Player column.

df['count_max'] = df.groupby('Team')['Minutes played'].transform('idxmax').map(df['Player'])

print(df)

   Team Player  Minutes played count_max
0     1      a               2         b
1     1      b              10         b
2     1      c               0         b
3     2      a              28         b
4     2      b              50         b
5     2      e               7         b
6     3      c             200         c
7     3      p              10         c