pandas groupby sum
df.groupby(['Fruit','Name'])['Number'].sum()
pandas sort values group by
df.groupby(['job']).apply(lambda x: (x.groupby('source')
.sum()
.sort_values('count', ascending=False))
.head(3))
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 B
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