删除 data.frame 中具有全部或部分 NA(缺失值)的行 [英] Remove rows with all or some NAs (missing values) in data.frame

问题描述

我想删除此数据框中的以下行:

I'd like to remove the lines in this data frame that:

a) 在所有列中包含 NA. 下面是我的示例数据框.

a) contain NAs across all columns. Below is my example data frame.

             gene hsap mmul mmus rnor cfam
1 ENSG00000208234    0   NA   NA   NA   NA
2 ENSG00000199674    0   2    2    2    2
3 ENSG00000221622    0   NA   NA   NA   NA
4 ENSG00000207604    0   NA   NA   1    2
5 ENSG00000207431    0   NA   NA   NA   NA
6 ENSG00000221312    0   1    2    3    2

基本上，我想获得如下数据框.

Basically, I'd like to get a data frame such as the following.

             gene hsap mmul mmus rnor cfam
2 ENSG00000199674    0   2    2    2    2
6 ENSG00000221312    0   1    2    3    2

b) 仅在某些列中包含 NAs，所以我也可以得到这个结果:

b) contain NAs in only some columns, so I can also get this result:

             gene hsap mmul mmus rnor cfam
2 ENSG00000199674    0   2    2    2    2
4 ENSG00000207604    0   NA   NA   1    2
6 ENSG00000221312    0   1    2    3    2

推荐答案

还要检查complete.cases :

> final[complete.cases(final), ]
             gene hsap mmul mmus rnor cfam
2 ENSG00000199674    0    2    2    2    2
6 ENSG00000221312    0    1    2    3    2

na.omit 更适合删除所有 NA.complete.cases 允许通过仅包含数据框的某些列来进行部分选择:

na.omit is nicer for just removing all NA's. complete.cases allows partial selection by including only certain columns of the dataframe:

> final[complete.cases(final[ , 5:6]),]
             gene hsap mmul mmus rnor cfam
2 ENSG00000199674    0    2    2    2    2
4 ENSG00000207604    0   NA   NA    1    2
6 ENSG00000221312    0    1    2    3    2

您的解决方案不起作用.如果你坚持使用 is.na，那么你必须这样做:

Your solution can't work. If you insist on using is.na, then you have to do something like:

> final[rowSums(is.na(final[ , 5:6])) == 0, ]
             gene hsap mmul mmus rnor cfam
2 ENSG00000199674    0    2    2    2    2
4 ENSG00000207604    0   NA   NA    1    2
6 ENSG00000221312    0    1    2    3    2

但使用 complete.cases 会更清晰、更快.

but using complete.cases is quite a lot more clear, and faster.

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