从所有值为NA，NULL或为空的数据框中删除列 [英] Remove columns from dataframe where ALL values are NA, NULL or empty

问题描述

我有一个数据框，其中某些值为NULL或Empty。我想删除这些列，其中所有值为 NULL 或空 。
列应该从数据框中删除，而不仅仅是隐藏。

I have a dataframe where some of the values are NULL or Empty. I would like to remove these columns in which all values are NULL or empty. Columns should be removed from the dataframe, do not hidden only.

我的头（df）看起来像data =

My head(df) looks like data=

  VAR1  VAR2  VAR3   VAR4  VAR5  VAR6  VAR7
1  2R+          52   1.05     0     0    30
2  2R+         169   1.02     0     0    40
3  2R+          83     NA     0     0    40
4  2R+          98   1.16     0     0    40
5  2R+         154   1.11     0     0    40
6  2R+         111     NA     0     0    15

数据框包含200多个变量，变量为空，并且零值不会顺序出现。

The dataframe contains more than 200 variables, variables are empty and zero values do not occur sequentially.

我尝试估算平均Col并选择列为Null或为空，类似于删除 NA（请参阅​​此处），但不起作用。

I tried to estimate the average Col and select the column is Null or empty, by analogy with the removal of "NA" (see here), but it does not work.

df <- df[,colSums(is.na(df))<nrow(df)]

我遇到一个错误： x必须是至少二维的数组

I got an error : 'x' must be an array of at least two dimensions

有人可以给我一些帮助吗？谢谢！

Can anyone give me some help? Thanks!

推荐答案

我们可以使用 Filter

Filter(function(x) !(all(x=="")), df)
#   Var1 Var3
#1  2R+   52
#2  2R+  169
#3  2R+   83
#4  2R+   98
#5  2R+   NA
#6  2R+  111
#7  2R+   94
#8  2R+  116
#9  2R+   86

注意：应该如果所有元素都是特定列的NA，则也可以使用

NOTE: It should also work if all the elements are NA for a particular column

df$Var3 <- NA
Filter(function(x) !(all(x=="")), df)
#   Var1
#1  2R+
#2  2R+
#3  2R+
#4  2R+
#5  2R+
#6  2R+
#7  2R+
#8  2R+
#9  2R+

更新

基于更新的数据集，如果我们需要删除仅包含0个值的列，则将代码更改为

Update

Based on the updated dataset, if we need to remove the columns with only 0 values, then change the code to

Filter(function(x) !(all(x==""|x==0)), df2)
#    VAR1 VAR3 VAR4 VAR7
#1  2R+   52 1.05   30
#2  2R+  169 1.02   40
#3  2R+   83   NA   40
#4  2R+   98 1.16   40
#5  2R+  154 1.11   40
#6  2R+  111   NA   15

数据

data

df2 <- structure(list(VAR1 = c("2R+", "2R+", "2R+", "2R+", "2R+", "2R+"
), VAR2 = c("", "", "", "", "", ""), VAR3 = c(52L, 169L, 83L, 
98L, 154L, 111L), VAR4 = c(1.05, 1.02, NA, 1.16, 1.11, NA), VAR5 = c(0L, 
0L, 0L, 0L, 0L, 0L), VAR6 = c(0L, 0L, 0L, 0L, 0L, 0L), VAR7 = c(30L, 
40L, 40L, 40L, 40L, 15L)), .Names = c("VAR1", "VAR2", "VAR3", 
"VAR4", "VAR5", "VAR6", "VAR7"), row.names = c("1", "2", "3", 
"4", "5", "6"), class = "data.frame")

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