How to create multiple columns from a single column in R

niks1 0
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I have a large data set in which i have a column which contains 5 different types of values. I want to create 5 different columns( 1 for each value) based on the column. Additionally, each row in those columns should contain either 1 or 0 based on whether another column contained that value For example suppose this is the data frame

l1=data.frame(c1=  c("A","A","B","B","B","C"), c2 = c("Blue","Green","Red","yellow","Black","Blue"))

The output should be

l2=data.frame(c1=c("A","A","B","B","B","C"), Blue=c(1,0,0,0,0,1),Green=c(0,1,0,0,0,0),Red=c(0,0,1,0,0,0),Yellow=c(0,0,0,1,0,0),Black=c(0,0,0,0,1,0))

Thank you!

r
2 Answers
library(tidyverse)
l1 %>%
  mutate(n = 1, dummy = row_number()) %>%
  pivot_wider(names_from = c2, values_from = n, values_fill = 0) %>%
  select(-dummy)

Result

# A tibble: 6 × 6
  c1     Blue Green   Red yellow Black
  <chr> <dbl> <dbl> <dbl>  <dbl> <dbl>
1 A         1     0     0      0     0
2 A         0     1     0      0     0
3 B         0     0     1      0     0
4 B         0     0     0      1     0
5 B         0     0     0      0     1
6 C         1     0     0      0     0
Jon Spring0

Using model.matrix you could do:

l2 <- as.data.frame(cbind(c1 = l1$c1, model.matrix(~ c2 - 1, l1)))

names(l2) <- gsub("^c2", "", names(l2))

l2
#>   c1 Black Blue Green Red yellow
#> 1  A     0    1     0   0      0
#> 2  A     0    0     1   0      0
#> 3  B     0    0     0   1      0
#> 4  B     0    0     0   0      1
#> 5  B     1    0     0   0      0
#> 6  C     0    1     0   0      0
user1kwS0
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