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熊猫多索引布尔索引

[英]Pandas multiindex boolean indexing

So given a multiindexed dataframe, I would like to return only rows that satisfy a condition for all levels of the lower index in a multi index. 因此,给定一个多索引数据帧,我只想返回满足多索引中所有较低索引级别的条件的行。 Here is a small working example: 这是一个小的工作示例:

df = pd.DataFrame({'a': [1, 1, 2, 2], 'b': [1, 2, 3, 4], 'c': [0, 2, 2, 2]})
df = df.set_index(['a', 'b'])

print(df)

out: 出:

     c
a b   
1 1  0
  2  2
2 3  2
  4  2

Now, I would like to return the entries for which c > 1 . 现在,我想返回c > 1的条目。 For instance, I would like to do something like 例如,我想做类似的事情

df[df[c > 1]]

out: 出:

     c
a b   
1 2  2
2 3  2
  4  2

But I want to get 但我想得到

out: 出:

     c
a b   
2 3  2
  4  2

Any thoughts on how to do this in the most efficient way? 关于如何以最有效的方式执行此操作的任何想法?

我最终使用了groupby

df.groupby(level=0).filter(lambda x: all([c > 1 for v in x['c']]))

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