Clean variable names

Source: R/clean_variable_names.R

This function standardises the variable names in a data.frame. It uses the standardisation implemented by epitrix::clean_labels() in the epitrix package. See ?epitrix::clean_labels for more information.

clean_variable_names(x, protect = FALSE, ...)

Arguments

x

a data.frame
protect

a logical or numeric vector specifying which columns to protect from manipulation
...

further arguments passed to epitrix::clean_labels(); the most important is sep, which refers to the separator used between words, and defaults to the underscore _.

Value

A data.frame with standardised variable names.

See also

clean_data() for a one-shot wrapper to clean your data

Examples


## make toy data
onsets <- as.Date("2018-01-01") + sample(1:10, 20, replace = TRUE)
gender <- sample(c("male", "female"), 20, replace = TRUE)
case_type <- c("confirmed", "probable", "suspected", "not a case")
case <- sample(case_type, 20, replace = TRUE)
toy_data <- data.frame("Date of Onset." = onsets,
                       "_GENDER_ " = gender,
                       "Épi.Case_définition" = case)
## show data
toy_data
#>    Date.of.Onset. X_GENDER_. Épi.Case_définition
#> 1      2018-01-06     female           confirmed
#> 2      2018-01-07     female           confirmed
#> 3      2018-01-08       male            probable
#> 4      2018-01-11       male           confirmed
#> 5      2018-01-04     female           confirmed
#> 6      2018-01-07     female          not a case
#> 7      2018-01-03     female           suspected
#> 8      2018-01-11     female           confirmed
#> 9      2018-01-11     female            probable
#> 10     2018-01-07       male            probable
#> 11     2018-01-09     female          not a case
#> 12     2018-01-04       male            probable
#> 13     2018-01-10       male           confirmed
#> 14     2018-01-02       male          not a case
#> 15     2018-01-02       male          not a case
#> 16     2018-01-07       male           suspected
#> 17     2018-01-10     female          not a case
#> 18     2018-01-10       male           suspected
#> 19     2018-01-02       male           confirmed
#> 20     2018-01-07       male            probable


## clean variable names, store in new object, show results
clean_data <- clean_variable_names(toy_data)
clean_data
#>    date_of_onset x_gender epi_case_definition
#> 1     2018-01-06   female           confirmed
#> 2     2018-01-07   female           confirmed
#> 3     2018-01-08     male            probable
#> 4     2018-01-11     male           confirmed
#> 5     2018-01-04   female           confirmed
#> 6     2018-01-07   female          not a case
#> 7     2018-01-03   female           suspected
#> 8     2018-01-11   female           confirmed
#> 9     2018-01-11   female            probable
#> 10    2018-01-07     male            probable
#> 11    2018-01-09   female          not a case
#> 12    2018-01-04     male            probable
#> 13    2018-01-10     male           confirmed
#> 14    2018-01-02     male          not a case
#> 15    2018-01-02     male          not a case
#> 16    2018-01-07     male           suspected
#> 17    2018-01-10   female          not a case
#> 18    2018-01-10     male           suspected
#> 19    2018-01-02     male           confirmed
#> 20    2018-01-07     male            probable