das*_*otz 0 python pandas pandas-groupby
我有一些看起来像这样的数据,叫做“ 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
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我希望它看起来像这样:
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
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但是,当我尝试按多列分组时,它们最终会按对象分组:
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
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这是我尝试的代码:
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()
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我尝试添加:
out_df['Value_avg'] = test_df['Value'].groupby([test_df['ID'],
test_df['Year']], as_index=False).mean()
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但是出现了这个错误:
"TypeError: as_index=False only valid with DataFrame"
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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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