pandas sort values group by
df.groupby(['job']).apply(lambda x: (x.groupby('source')
.sum()
.sort_values('count', ascending=False))
.head(3))sort values within groups pandas dataframe
import pandas as pd
df = pd.DataFrame({'A':[1, 2, 3, 4, 5, 6],
'B':[0, 1, 2, 0, 1, 2]})
df.groupby('B').apply(lambda x: x.sort_values('A', ascending = True))groupby and sort python
In[34]: df.sort_values(['job','count'],ascending=False).groupby('job').head(3)
Out[35]:
count job source
4 7 sales E
2 6 sales C
1 4 sales B
5 5 market A
8 4 market D
6 3 market BGroup based sort pandas
df_scored.sort_values('Score', ascending= False).sort_index(level='Index1', sort_remaining=False)Copyright © 2021 Codeinu
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