pandas 选择倒数第二列也不是 nan [英] Pandas select the second to last column which is also not nan

问题描述

我已经尽可能多地清理了我的数据，并在 Pandas 数据框中读取了它们.所以问题是不同的文件有不同的列数，但它总是倒数第二个非 nan 列是我想要的.那么有没有办法把它们挑出来呢?这是数据的示例.

I've cleaned my data as much as I can and read them in Pandas dataframe. So the problem is that different files have different number of columns, but it always the second to the last non-nan column is what I want. So is there anyway to pick them out? Here is an example of the data.

     ...    f       g      h      l
0    ...    39994  29.568  29.569 NaN  
1    ...    39994  29.568  29.569 NaN  
2    ...    39994  29.568  29.569 NaN 

所以在这种情况下我想要列 g.所以在其他文件中，它可能是 f 或任何取决于最后 nan 列的数量.但它总是倒数第二个非 nan 列是我需要的.感谢您的帮助.

so I want the column g in this case. So in other files, it could be f or anything depends on the number of nan columns in the end. But it's always the second to the last non-nan column is what I need. Thanks for the help ahead.

推荐答案

与 @piRSquared 类似的想法.本质上，使用 loc 保留非空列，然后使用 iloc 选择倒数第二个.

Similar idea to @piRSquared. Essentially, use loc to keep the non-null columns, then use iloc to select the second to last.

df.loc[:, ~df.isnull().all()].iloc[:, -2]

样本输入:

   a  b  c   d   e   f   g   h   i   j
0  0  3  6   9  12  15  18  21 NaN NaN
1  1  4  7  10  13  16  19  22 NaN NaN
2  2  5  8  11  14  17  20  23 NaN NaN

示例输出:

0    18
1    19
2    20
Name: g, dtype: int32

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