Creates dummy variables from multiple categorical variables. Uses data.table() for speed (enhanced from the previous version) Uses dplyr select() special functions to select categorical variables.

Creates dummy variables from multiple categorical variables. Uses data.table() for speed (enhanced from the previous version) Uses dplyr select() special functions to select categorical variables.

superspread(df, select_helpers)

Arguments

df

Data frame containing the multiple categorical variables.

select_helpers

Uses dplyr-style select functions to select multiple variables. Use everything() to select all variables. These variables must all be character type.

See also

Other superspread functions: superspread_count()

Examples

superspread(iris,"Species")
#> # A tibble: 150 × 8
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species setosa versicolor
#>           <dbl>       <dbl>        <dbl>       <dbl> <fct>   <lgl>  <lgl>     
#>  1          5.1         3.5          1.4         0.2 setosa  TRUE   FALSE     
#>  2          4.9         3            1.4         0.2 setosa  TRUE   FALSE     
#>  3          4.7         3.2          1.3         0.2 setosa  TRUE   FALSE     
#>  4          4.6         3.1          1.5         0.2 setosa  TRUE   FALSE     
#>  5          5           3.6          1.4         0.2 setosa  TRUE   FALSE     
#>  6          5.4         3.9          1.7         0.4 setosa  TRUE   FALSE     
#>  7          4.6         3.4          1.4         0.3 setosa  TRUE   FALSE     
#>  8          5           3.4          1.5         0.2 setosa  TRUE   FALSE     
#>  9          4.4         2.9          1.4         0.2 setosa  TRUE   FALSE     
#> 10          4.9         3.1          1.5         0.1 setosa  TRUE   FALSE     
#> # ℹ 140 more rows
#> # ℹ 1 more variable: virginica <lgl>
if (FALSE) { # \dontrun{
library(data.table)
library(dplyr)
dt <- data.table(id = 1:10000,
                 cat1 = sample(letters[1:3],10000,replace = TRUE),
                 cat2 = sample(letters[1:4],10000,replace = TRUE),
                 cat3 = sample(letters[1:5],10000,replace = TRUE))
dt <- as.data.table(dt)
superspread(df = dt, select_helpers = contains("cat"))
} # }