This function copies variable and value labels (including missing values) from one vector to another or from one data frame to another data frame. For data frame, labels are copied according to variable names, and only if variables are the same type in both data frames.
copy_labels(from, to, .strict = TRUE)
copy_labels_from(to, from, .strict = TRUE)A vector or a data.frame (or tibble) to copy labels from.
A vector or data.frame (or tibble) to copy labels to.
When from is a labelled vector, to have to be of the same
type (numeric or character) in order to copy value labels and SPSS-style
missing values. If this is not the case and .strict = TRUE, an error
will be produced. If .strict = FALSE, only variable label will be
copied.
Some base R functions like base::subset() drop variable and
value labels attached to a variable. copy_labels could be used
to restore these attributes.
copy_labels_from is intended to be used with dplyr syntax,
see examples.
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
df <- tibble(
id = 1:3,
happy = factor(c('yes', 'no', 'yes')),
gender = labelled(c(1, 1, 2), c(female = 1, male = 2))
) %>%
set_variable_labels(
id = "Individual ID",
happy = "Are you happy?",
gender = "Gender of respondent"
)
var_label(df)
#> $id
#> [1] "Individual ID"
#>
#> $happy
#> [1] "Are you happy?"
#>
#> $gender
#> [1] "Gender of respondent"
#>
fdf <- df %>% filter(id < 3)
var_label(fdf) # some variable labels have been lost
#> $id
#> [1] "Individual ID"
#>
#> $happy
#> [1] "Are you happy?"
#>
#> $gender
#> [1] "Gender of respondent"
#>
fdf <- fdf %>% copy_labels_from(df)
var_label(fdf)
#> $id
#> [1] "Individual ID"
#>
#> $happy
#> [1] "Are you happy?"
#>
#> $gender
#> [1] "Gender of respondent"
#>
# Alternative syntax
fdf <- subset(df, id < 3)
fdf <- copy_labels(from = df, to = fdf)