Encode Categorical Missing Values in a list
of data.frame
ls_explicit_na.Rd
Encode Categorical Missing Values in a list
of data.frame
Usage
ls_explicit_na(
data,
omit_tables = NULL,
omit_columns = NULL,
char_as_factor = TRUE,
na_level = "<Missing>"
)
Arguments
- data
(
list
ofdata.frame
) to be transformed.- omit_tables
(
character
) the names of the tables to omit from processing.- omit_columns
(
character
) the names of the columns to omit from processing.- char_as_factor
(
logical
) should character columns be converted into factor.- na_level
(
string
) the label to encode missing levels.
Details
This is a helper function to encode missing values (i.e NA
and empty string
) of every character
and
factor
variable found in a list
of data.frame
. The label
attribute of the columns is preserved.
Examples
df1 <- data.frame(
"char" = c("a", "b", NA, "a", "k", "x"),
"char2" = c("A", "B", NA, "A", "K", "X"),
"fact" = factor(c("f1", "f2", NA, NA, "f1", "f1")),
"logi" = c(NA, FALSE, TRUE, NA, FALSE, NA)
)
df2 <- data.frame(
"char" = c("a", "b", NA, "a", "k", "x"),
"fact" = factor(c("f1", "f2", NA, NA, "f1", "f1")),
"num" = c(1:5, NA)
)
df3 <- data.frame(
"char" = c(NA, NA, "A")
)
db <- list(df1 = df1, df2 = df2, df3 = df3)
ls_explicit_na(db)
#> $df1
#> char char2 fact logi
#> 1 a A f1 NA
#> 2 b B f2 FALSE
#> 3 <Missing> <Missing> <Missing> TRUE
#> 4 a A <Missing> NA
#> 5 k K f1 FALSE
#> 6 x X f1 NA
#>
#> $df2
#> char fact num
#> 1 a f1 1
#> 2 b f2 2
#> 3 <Missing> <Missing> 3
#> 4 a <Missing> 4
#> 5 k f1 5
#> 6 x f1 NA
#>
#> $df3
#> char
#> 1 <Missing>
#> 2 <Missing>
#> 3 A
#>
ls_explicit_na(db, omit_tables = "df3", omit_columns = "char2")
#> $df1
#> char char2 fact logi
#> 1 a A f1 NA
#> 2 b B f2 FALSE
#> 3 <Missing> <NA> <Missing> TRUE
#> 4 a A <Missing> NA
#> 5 k K f1 FALSE
#> 6 x X f1 NA
#>
#> $df2
#> char fact num
#> 1 a f1 1
#> 2 b f2 2
#> 3 <Missing> <Missing> 3
#> 4 a <Missing> 4
#> 5 k f1 5
#> 6 x f1 NA
#>
#> $df3
#> char
#> 1 <NA>
#> 2 <NA>
#> 3 A
#>