R/superspread.R
superspread.RdCreates 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)Data frame containing the multiple categorical variables.
Uses dplyr-style select functions to select multiple variables. Use everything() to select all variables. These variables must all be character type.
Other superspread functions:
superspread_count()
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) {
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"))
}