如何确定Pandas列是否包含特定值 [英] How to determine whether a Pandas Column contains a particular value

问题描述

我试图确定Pandas列中是否有一个具有特定值的条目.我试图用if x in df['id']做到这一点.我以为这是行得通的，除了当我输入一个我知道不在列43 in df['id']中的值时，它仍然返回True.当我将一个子集添加到一个仅包含与缺少的ID df[df['id'] == 43]匹配的条目的数据框时，显然其中没有任何条目.如何确定Pandas数据框中的列是否包含特定值，为什么我的当前方法不起作用? (仅供参考，当我在对此类似问题的 answer 中使用实现时，我遇到了同样的问题.

I am trying to determine whether there is an entry in a Pandas column that has a particular value. I tried to do this with if x in df['id']. I thought this was working, except when I fed it a value that I knew was not in the column 43 in df['id'] it still returned True. When I subset to a data frame only containing entries matching the missing id df[df['id'] == 43] there are, obviously, no entries in it. How to I determine if a column in a Pandas data frame contains a particular value and why doesn't my current method work? (FYI, I have the same problem when I use the implementation in this answer to a similar question).

推荐答案

系列的

in检查值是否在索引中:

in of a Series checks whether the value is in the index:

In [11]: s = pd.Series(list('abc'))

In [12]: s
Out[12]: 
0    a
1    b
2    c
dtype: object

In [13]: 1 in s
Out[13]: True

In [14]: 'a' in s
Out[14]: False

一种选择是查看其是否为唯一值:

One option is to see if it's in unique values:

In [21]: s.unique()
Out[21]: array(['a', 'b', 'c'], dtype=object)

In [22]: 'a' in s.unique()
Out[22]: True

或python设置:

In [23]: set(s)
Out[23]: {'a', 'b', 'c'}

In [24]: 'a' in set(s)
Out[24]: True

如@DSM所指出的那样，直接在这些值上使用可能会更有效(特别是如果您仅对一个值执行此操作):

As pointed out by @DSM, it may be more efficient (especially if you're just doing this for one value) to just use in directly on the values:

In [31]: s.values
Out[31]: array(['a', 'b', 'c'], dtype=object)

In [32]: 'a' in s.values
Out[32]: True

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