Python Pandas 按多列分组,另一列的平均值 - 不按对象分组 [英] Python Pandas group by multiple columns, mean of another - no group by object
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问题描述
我有一些看起来像这样的数据,名为test_df"
I have some data that looks like this, and called 'test_df'
ID Year Value Value2
0 A 2012 1 4
1 A 2012 2 5
2 A 2013 4 6
3 A 2013 5 7
4 B 2014 6 8
5 B 2014 7 4
6 B 2013 8 8
我希望它看起来像这样:
I want it to look like this:
ID Year Value_avg Value2_avg
A 2012 1.5 4.5
A 2013 4.5 6.5
B 2013 8.0 8.0
B 2014 6.5 6.0
但是,当我尝试按多列分组时,它们最终会按对象分组:
However, when I try to group by multiple columns they end up as group by objects:
Value_avg Value2_avg
ID Year
A 2012 1.5 4.5
2013 4.5 6.5
B 2013 8.0 8.0
2014 6.5 6.0
这是我试过的代码:
out_df = pd.DataFrame()
out_df['Value_avg'] = test_df['Value'].groupby([test_df['ID'], test_df['Year']]).mean()
out_df['Value2_avg'] = test_df['Value2'].groupby([test_df['ID'], test_df['Year']]).mean()
我尝试添加:
out_df['Value_avg'] = test_df['Value'].groupby([test_df['ID'],
test_df['Year']], as_index=False).mean()
但得到这个错误:
"TypeError: as_index=False only valid with DataFrame"
推荐答案
add_suffix
+ reset_index
df.groupby(['ID','Year']).mean().add_suffix('_avg').reset_index()
Out[337]:
ID Year Value_avg Value2_avg
0 A 2012 1.5 4.5
1 A 2013 4.5 6.5
2 B 2013 8.0 8.0
3 B 2014 6.5 6.0
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