How to remove a deeper attribute from a variable

[Andrzej]

Hi ,

this works:

attr(temp$d1, "labels") <- attr(temp$d1, "labels")[-1]

attr(temp$d2, "labels") <- attr(temp$d2, "labels")[-1]

attr(temp$d3, "labels") <-  attr(temp$d3, "labels")[-1]

attr(temp$d4, "labels") <-  attr(temp$d4, "labels")[-1]

attr(temp$d5, "labels") <-  attr(temp$d5, "labels")[-1]

attr(temp$d6, "labels") <-  attr(temp$d6, "labels")[-1]

attr(temp$d7, "labels") <-  attr(temp$d7, "labels")[-1]

attr(temp$d8, "labels") <-  attr(temp$d8, "labels")[-1]

attr(temp$d9, "labels") <-  attr(temp$d9, "labels")[-1]

so in order to automate it I have written:

for(i in 2:dim(temp)[2]){
  
attr(temp[,i],"labels") <- attr(temp[,i],"labels")[-1]
  
}

but it doesn't work.

That code below doesn't work as well:

for(i in 2:10){
  
attr(temp[,i],"labels") <- attr(temp[,i],"labels")[-1]
  
}

temp is the name of my dataframe, I want to apply this to columns 2:10.
Please help, thank you.

[williaml]

Hi, can you provide a reproducible example of the dataset temp?

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[Andrzej]

Good morning, and here you are:

temp  <-  structure(list(d1 = structure(c(NA, NA, 1, 2, 1, NA, 4, 1, 2, 
2), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d2 = structure(c(NA, NA, 1, 2, 1, NA, 4, 1, 2, 2), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d3 = structure(c(NA, NA, NA, 2, 1, NA, 3, NA, 2, 2), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d4 = structure(c(NA, NA, NA, 2, NA, NA, 4, 4, 1, 1), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d5 = structure(c(3, 4, 4, 2, 1, 1, 1, 4, 4, 3), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d6 = structure(c(2, 1, NA, 2, 2, NA, 1, 1, NA, 3), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d7 = structure(c(4, 2, NA, 2, 2, NA, 3, 4, 2, 4), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d8 = structure(c(2, 2, NA, 2, 2, NA, 3, 4, 3, 4), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
)), d9 = structure(c(1, NA, NA, 2, 1, NA, NA, 1, 1, 1), format.spss = "F1.0", display_width = 12L, class = c("haven_labelled", 
"vctrs_vctr", "double"), labels = c(`not applicable` = 0, `not reduced` = 1, 
`slightly reduced` = 2, `moderately reduced` = 3, `strongly reduced` = 4
))), row.names = c(NA, -10L), class = c("tbl_df", "tbl", "data.frame"
))

I would like for example to remove (or exclude) the label "'not applicable' = 0".
I thought that for loop should work, but it did not.
Also I want to ask if is it a faster way to write this:

attr(temp$d1, "labels") <- attr(temp$d1, "labels")[-1]

attr(temp$d2, "labels") <- attr(temp$d2, "labels")[-1]

attr(temp$d3, "labels") <-  attr(temp$d3, "labels")[-1]

attr(temp$d4, "labels") <-  attr(temp$d4, "labels")[-1]

attr(temp$d5, "labels") <-  attr(temp$d5, "labels")[-1]

attr(temp$d6, "labels") <-  attr(temp$d6, "labels")[-1]

attr(temp$d7, "labels") <-  attr(temp$d7, "labels")[-1]

attr(temp$d8, "labels") <-  attr(temp$d8, "labels")[-1]

attr(temp$d9, "labels") <-  attr(temp$d9, "labels")[-1]

When I write it one by one it works, otherwise it does not.

[williaml]

Here you're not actually removing them:

attr(temp$d1, "labels") <- attr(temp$d1, "labels")[-1]

because when you run attr(temp$d1, "labels") again, the 'not applicable' label is still there.

Perhaps try this?

https://www.rdocumentation.org/packages/labelled/versions/2.8.0/topics/remove_labels