library(tidyREDCap)The tidyREDCap package creates data sets with labelled
columns.
tidyREDCap::import_instruments(
url = "https://bbmc.ouhsc.edu/redcap/api/",
token = Sys.getenv("REDCapR_test")
)If you would like to see the labels on the data set
demographics, you can use the RStudio function
View(), as shown below.
View(demographics)However, some functions do not work well with labeled variables.
library(skimr) # for the skim() function
demographics |> skim()| Name | demographics |
| Number of rows | 5 |
| Number of columns | 10 |
| _______________________ | |
| Column type frequency: | |
| Date | 1 |
| character | 7 |
| numeric | 2 |
| ________________________ | |
| Group variables | None |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| dob | 0 | 1 | 1934-04-09 | 2003-08-30 | 1955-04-15 | 5 |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| name_first | 0 | 1 | 5 | 8 | 0 | 5 | 0 |
| name_last | 0 | 1 | 3 | 8 | 0 | 4 | 0 |
| address | 0 | 1 | 29 | 38 | 0 | 5 | 0 |
| telephone | 0 | 1 | 14 | 14 | 0 | 5 | 0 |
| 0 | 1 | 12 | 19 | 0 | 5 | 0 | |
| sex | 0 | 1 | 4 | 6 | 0 | 2 | 0 |
| demographics_complete | 0 | 1 | 8 | 8 | 0 | 1 | 0 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| record_id | 0 | 1 | 3.0 | 1.58 | 1 | 2 | 3 | 4 | 5 | ▇▇▇▇▇ |
| age | 0 | 1 | 44.4 | 31.57 | 11 | 11 | 59 | 61 | 80 | ▇▁▁▇▃ |
So you need a way to drop the label off of a variable or to drop all the labels from all the variables in a dataset.
You can drop the label from a single variable with the drop_label() function. For example:
demographics_changed <- drop_label(demographics, "first_name")You can drop all the labels using the drop_labels()
function. For example:
demographics_without_labels <- drop_labels(demographics)
demographics_without_labels |>
skim()| Name | demographics_without_labe… |
| Number of rows | 5 |
| Number of columns | 10 |
| _______________________ | |
| Column type frequency: | |
| character | 7 |
| numeric | 3 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| name_first | 0 | 1 | 5 | 8 | 0 | 5 | 0 |
| name_last | 0 | 1 | 3 | 8 | 0 | 4 | 0 |
| address | 0 | 1 | 29 | 38 | 0 | 5 | 0 |
| telephone | 0 | 1 | 14 | 14 | 0 | 5 | 0 |
| 0 | 1 | 12 | 19 | 0 | 5 | 0 | |
| sex | 0 | 1 | 4 | 6 | 0 | 2 | 0 |
| demographics_complete | 0 | 1 | 8 | 8 | 0 | 1 | 0 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| record_id | 0 | 1 | 3.0 | 1.58 | 1 | 2 | 3 | 4 | 5 | ▇▇▇▇▇ |
| dob | 0 | 1 | -56.0 | 11581.94 | -13051 | -6269 | -5375 | 12121 | 12294 | ▃▇▁▁▇ |
| age | 0 | 1 | 44.4 | 31.57 | 11 | 11 | 59 | 61 | 80 | ▇▁▁▇▃ |