我有一个像这样的DataFrame:
df = pd.DataFrame(np.random.randn(6, 6),
columns=pd.MultiIndex.from_arrays((['A','A','A','B','B','B'],
['a', 'b', 'c', 'a', 'b', 'c'])))
df
A B
a b c a b c
0 -0.089902 -2.235642 0.282761 0.725579 1.266029 -0.354892
1 -1.753303 1.092057 0.484323 1.789094 -0.316307 0.416002
2 -0.409028 -0.920366 -0.396802 -0.569926 -0.538649 -0.844967
3 1.789569 -0.935632 0.004476 -1.873532 -1.136138 -0.867943
4 0.244112 0.298361 -1.607257 -0.181820 0.577446 0.556841
5 0.903908 -1.379358 0.361620 1.290646 -0.523404 -0.518992
我只想选择
c
列中值大于0的行。我认为必须使用pd.IndexSlice
仅选择第二级索引c
。idx = pd.IndexSlice
df.loc[:,idx[:,['c']]] > 0
A B
c c
0 True False
1 True True
2 False False
3 True False
4 False True
5 True False
因此,现在我希望我可以简单地执行
df[df.loc[:,idx[:,['c']]] > 0]
,但是这给了我意外的结果:df[df.loc[:,idx[:,['c']]] > 0]
A B
a b c a b c
0 NaN NaN 0.282761 NaN NaN NaN
1 NaN NaN 0.484323 NaN NaN 0.416002
2 NaN NaN NaN NaN NaN NaN
3 NaN NaN 0.004476 NaN NaN NaN
4 NaN NaN NaN NaN NaN 0.556841
5 NaN NaN 0.361620 NaN NaN NaN
我希望拥有的是所有值(不是
NaN
),并且只有任何c列都大于0的行。 A B
a b c a b c
0 -0.089902 -2.235642 0.282761 0.725579 1.266029 -0.354892
1 -1.753303 1.092057 0.484323 1.789094 -0.316307 0.416002
3 1.789569 -0.935632 0.004476 -1.873532 -1.136138 -0.867943
4 0.244112 0.298361 -1.607257 -0.181820 0.577446 0.556841
5 0.903908 -1.379358 0.361620 1.290646 -0.523404 -0.518992
因此,我可能需要在其中的某个地方潜入
any()
,但是,我不确定该怎么做。有什么提示吗? 最佳答案
您正在寻找any
df[(df.loc[:,idx[:,['c']]]>0).any(axis = 1)]
Out[133]:
A B
a b c a b c
1 -0.423313 0.459464 -1.457655 -0.559667 -0.056230 1.338850
3 -0.072396 1.305868 -1.239441 -0.708834 0.348704 0.260532
4 -1.415575 1.229508 0.148254 -0.812806 1.379552 -1.195062
5 -0.336973 -0.469335 1.345719 0.847943 1.465100 -0.285792
关于python - 具有MultiIndex的pandas DataFrame中的条件选择行,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/53887637/