pandas 获取满足某些条件的索引
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Get indices that satisfy some criteria
提问by Amelio Vazquez-Reina
In Pandas, how can I get a list of indices of a series/dataframe for the entries that satisfy some property?
在 Pandas 中，如何获取满足某些属性的条目的系列/数据框的索引列表？
The following returns a Seriesobject
下面返回一个Series对象
my_dataframe.loc[:,'some_column'] == 'some_value'
that looks like this:
看起来像这样：
519 True
509 False
826 False
503 False
511 False
512 False
500 False
507 False
516 True
504 False
521 False
510 False
351 False
522 False
526 False
517 False
501 False
but what I want is two lists, one with
但我想要的是两个列表，一个是
[519, 516]
and one with the rest of indices. How can I do this in Pandas?
和其他索引之一。我怎样才能在 Pandas 中做到这一点？
回答by Jeff
In [8]: df = DataFrame(randn(10,2),columns=list('AB'))
In [9]: df
Out[9]:
A B
0 -1.046978 1.561624
1 -0.264645 0.717171
2 0.112354 -2.084449
3 -1.243482 -1.183749
4 1.055667 0.532444
5 -1.295805 2.168225
6 -1.239725 0.969934
7 -0.354017 1.434943
8 -0.867560 0.810315
9 0.097698 -0.033039
In [10]: df.loc[:,'B'] > 0
Out[10]:
0 True
1 True
2 False
3 False
4 True
5 True
6 True
7 True
8 True
9 False
Name: B, dtype: bool
In [14]: x = df.loc[:,'B'] > 0
Per Tom/Andy, much simpler
In [33]: x[x].index
Out[33]: Int64Index([0, 1, 4, 5, 6, 7, 8], dtype=int64)
In [34]: x[~x].index
Out[34]: Int64Index([2, 3, 9], dtype=int64)
回答by TomAugspurger
A slight variant on @Jeff's example:
@Jeff 示例的一个小变种：
In [18]: df
Out[18]:
A B
0 0.319489 1.012319
1 0.494205 -0.918240
2 1.501922 -0.409661
3 -1.593702 0.705407
4 -0.735312 1.037567
5 -0.201132 -0.673124
6 1.237310 -0.877043
7 -0.946714 0.984164
8 -0.923548 0.415094
9 0.135281 -0.199951
In [14] list1 = df.index[df.loc[:, 'B'] > 0]
In [15]: list1
Out[15]: Int64Index([0, 3, 4, 7, 8], dtype=int64)
In [16]: list2 = df.index - list1
In [17]: list2
Out[17]: Int64Index([1, 2, 5, 6, 9], dtype=int64)
