Recode one or multiple variables based on a lookup table created via createLookup
(and potentially formatted by collapseColumns).
Arguments
- GADSdat
A
GADSdatobject.- lookup
Lookup table created by
createLookupand - if necessary - collapsed bycollapseColumns. Column names must bec("variable", "value", "value_new").- suffix
Suffix to add to the existing variable names. If
NULL, the old variables will be overwritten.
Details
If there are missing values in the column value_new, NAs are inserted as new values
and a warning is issued.
The complete work flow when using a lookup table to recode multiple variables in a GADSdat could be:
(0) optional: Recode empty strings to NA (necessary, if the look up table is written to excel).
(1) create a lookup table with createLookup.
(2) Save the lookup table to .xlsx with write_xlsx from eatAnalysis.
(3) fill out the lookup table via Excel.
(4) Import the lookup table back to R via read_excel from readxl.
(5) Apply the final lookup table with applyLookup.
See applyLookup_expandVar for recoding a single variable into multiple variables.
Examples
## create an example GADSdat
iris2 <- iris
iris2$Species <- as.character(iris2$Species)
gads <- import_DF(iris2)
#> Sepal.Length has been renamed to Sepal_Length
#> Sepal.Width has been renamed to Sepal_Width
#> Petal.Length has been renamed to Petal_Length
#> Petal.Width has been renamed to Petal_Width
## create Lookup
lu <- createLookup(gads, recodeVars = "Species")
lu$value_new <- c("plant 1", "plant 2", "plant 3")
## apply lookup table
gads2 <- applyLookup(gads, lookup = lu, suffix = "_r")
#> No rows removed from meta data.
#> Adding meta data for the following variables: Species_r
## only recode some values
lu2 <- createLookup(gads, recodeVars = "Species")
lu2$value_new <- c("plant 1", "plant 2", NA)
gads3 <- applyLookup(gads, lookup = lu2, suffix = "_r")
#> Warning: Not all values have a recode value assigned (missings in value_new).
#> No rows removed from meta data.
#> Adding meta data for the following variables: Species_r
