How can I sort within partitions defined by one column but leave the partitions where they are?

Question

Consider the dataframe df

df = pd.DataFrame(dict(
        A=list(\'XXYYXXYY\'),
        B=range(8, 0, -1)
    ))

print(df)

   A  B
0  X  8
1           


        

Answer 1

You can use transform to get back your new desired index order, then use reindex to reorder your DataFrame:

# Use transform to return the new ordered index values.
new_idx = df.groupby('A')['B'].transform(lambda grp: grp.sort_values().index)

# Reindex.
df = df.reindex(new_idx.rename(None))

You could combine the two lines above into one long line, if so desired.

The resulting output:

   A  B
5  X  3
4  X  4
7  Y  1
6  Y  2
1  X  7
0  X  8
3  Y  5
2  Y  6

Note that if you don't care about maintaing your old index, you can directly reassign from the transform:

df['B'] = df.groupby('A')['B'].transform(lambda grp: grp.sort_values())

Which yields:

   A  B
0  X  3
1  X  4
2  Y  1
3  Y  2
4  X  7
5  X  8
6  Y  5
7  Y  6