pandas 通过另一列熊猫找到列组的最大值
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find the max of column group by another column pandas
提问by User1090
I have a dataframe with 2 columns,
我有一个包含 2 列的数据框，
count percent grpno.
0 14.78 1
1 0.00 2
2 8.80 3
3 9.60 4
4 55.90 4
5 0.00 2
6 0.00 6
7 0.00 5
8 6.90 1
9 59.00 4
I need to get the max of column 'count percent ' and group by column 'grpno.'. Though I tried doing the same by
我需要获得“count percent”列的最大值并按“grpno.”列分组。虽然我尝试通过
geostat.groupby(['grpno.'], sort=False)['count percent'].max()
I get the output to be
我得到的输出是
grpno.
1 14.78
2 0.00
3 8.80
4 59.00
6 0.00
5 0.00
Name: count percent, dtype: float64
But I need output to be a dataframe that has the column name modified as 'MaxOfcount percent' and 'grpno.' Can anyone help on this? Thanks
但我需要输出是一个数据框，其列名修改为“MaxOfcount percent”和“grpno”。任何人都可以帮忙吗？谢谢
回答by Stefan
res = df.groupby('grpno.')['count percent'].max().reset_index()
res.columns = ['grpno.', 'MaxOfcount percent']
grpno. MaxOfcount percent
0 1 14.78
1 2 0.00
2 3 8.80
3 4 59.00
4 5 0.00
5 6 0.00
You could also do it in one line:
您也可以在一行中完成：
res = df.groupby('grpno.', as_index=False)['count percent'].max().rename(columns={'count percent': 'MaxOfcount percent'})
回答by Anton Protopopov
You could use groupbywith argument as_index=False:
您可以使用groupbywith 参数as_index=False：
In [119]: df.groupby(['grpno.'], as_index=False)[['count percent']].max()
Out[119]:
grpno. count percent
0 1 14.78
1 2 0.00
2 3 8.80
3 4 59.00
4 5 0.00
5 6 0.00
df1 = df.groupby(['grpno.'], as_index=False)[['count percent']].max()
df1.columns = df1.columns[:-1].tolist() + ['MaxOfcount percent']
In [130]: df1
Out[130]:
grpno. MaxOfcount percent
0 1 14.78
1 2 0.00
2 3 8.80
3 4 59.00
4 5 0.00
5 6 0.00
