Recode Categorical Variable to Binary (0/1)

Recode categorical variable as new variable in R

Found this answer here (https://rstudio-pubs-static.s3.amazonaws.com/116317_e6922e81e72e4e3f83995485ce686c14.html#/9)

df <- mutate(df, cat = ifelse(grepl("Sailfin molly", common_name), "Fish",
                                      ifelse(grepl("Hardhead silverside", common_name), "Fish", "Crab")))

Recode categorical factor with N categories into N binary columns

Even better with the help of @AnandaMahto's search capabilities,

model.matrix(~ . + 0, data=df, contrasts.arg = lapply(df, contrasts, contrasts=FALSE))
#    v1a v1b v1c v2a v2b v2c
# 1    0   1   0   0   0   1
# 2    1   0   0   1   0   0
# 3    0   0   1   0   0   1
# 4    0   1   0   1   0   0
# 5    0   0   1   0   0   1
# 6    0   0   1   0   1   0
# 7    1   0   0   1   0   0
# 8    1   0   0   0   1   0
# 9    1   0   0   0   0   1
# 10   1   0   0   0   1   0

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I think this is what you're looking for. I'd be happy to delete if it's not so. Thanks to @G.Grothendieck (once again) for the excellent usage of model.matrix!

cbind(with(df, model.matrix(~ v1 + 0)), with(df, model.matrix(~ v2 + 0)))
#    v1a v1b v1c v2a v2b v2c
# 1    0   1   0   0   0   1
# 2    1   0   0   1   0   0
# 3    0   0   1   0   0   1
# 4    0   1   0   1   0   0
# 5    0   0   1   0   0   1
# 6    0   0   1   0   1   0
# 7    1   0   0   1   0   0
# 8    1   0   0   0   1   0
# 9    1   0   0   0   0   1
# 10   1   0   0   0   1   0

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Note: Your output is just:

with(df, model.matrix(~ v2 + 0))

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Note 2: This gives a matrix. Fairly obvious, but still, wrap it with as.data.frame(.) if you want a data.frame.

Convert categorical variable into binary columns in R

Try this:

library(dplyr)
library(tidyr)
df %>%
  separate_rows(answer_openq, sep = ',') %>%
  pivot_wider(names_from = answer_openq, values_from = answer_openq, 
              values_fn = function(x) 1, values_fill = 0)
# A tibble: 4 × 5
  respondent     a     c     b     d
       <int> <dbl> <dbl> <dbl> <dbl>
1          1     1     0     0     0
2          2     1     1     0     0
3          3     0     0     1     0
4          4     1     0     0     1

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