Issue
I am grouping my dataset by column A and then would like to take the minimum value in column B and the corresponding value in column C.
data = pd.DataFrame({'A': [1, 2], 'B':[ 2, 4], 'C':[10, 4]})
data
A B C
0 1 4 3
1 1 5 4
2 1 2 10
3 2 7 2
4 2 4 4
5 2 6 6
and I would like to get :
A B C
0 1 2 10
1 2 4 4
For the moment I am grouping by A, and creating a value that indicates me the rows I will keep in my dataset:
a = data.groupby('A').min()
a['A'] = a.index
to_keep = [str(x[0]) + str(x[1]) for x in a[['A', 'B']].values]
data['id'] = data['A'].astype(str) + data['B'].astype('str')
data[data['id'].isin(to_keep)]
I am sure that there is a much more straight forward way to do this.
I have seen many answers here that use multi-indexing but I would like to do this without adding multi-index to my dataframe.
Thank you for your help.
Solution
I feel like you’re overthinking this. Just use groupby and idxmin:
df.loc[df.groupby('A').B.idxmin()]
A B C
2 1 2 10
4 2 4 4
df.loc[df.groupby('A').B.idxmin()].reset_index(drop=True)
A B C
0 1 2 10
1 2 4 4
Answered By – cs95
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