Creating a new column in R - r

Question

I have a data.frame like the following:
regions admit men_age group
1 1234 34 2
2 3416 51 1
3 2463 26 3
4 1762 29 2
5 2784 31 4
6 999 42 1
7 2111 23 2
8 1665 36 3
9 2341 21 4
10 1723 33 1
I would like to create new columns using admit and group as follows:
regions admit men_age group admit1 admit2 admit3 admit4
1 1234 34 2 0 1234 0 0
2 3416 51 1 3416 0 0 0
3 2463 26 3 0 0 2463 0
4 1762 29 2 0 1762 0 0
5 2784 31 4 0 0 0 2784
6 999 42 1 999 0 0 0
7 2111 23 2 0 2111 0 0
8 1665 36 3 0 0 1665 0
9 2341 21 4 0 0 0 2341
10 1723 33 1 1723 0 0 0
In fact, what I want to do is to create four new admit columns according to group column as follows: in admit 1 column, the value for rows where group is 1, put the corresponding admit number, other wise put zero. In admit 2 column, the values for rows where group is 2, put the corresponding admit number, otherwise put zero ans this applies for two other column as well.
I tried a couple of ways to solve it, but failed.
May please someone help me to solve this?

Answer 1

A solution using tidyverse. We can create the columns and then spread them with fill = 0.
library(tidyverse)
dat2 <- dat %>%
mutate(group2 = str_c("admit", group), admit2 = admit) %>%
spread(group2, admit2, fill = 0)
dat2
# regions admit men_age group admit1 admit2 admit3 admit4
# 1 1 1234 34 2 0 1234 0 0
# 2 2 3416 51 1 3416 0 0 0
# 3 3 2463 26 3 0 0 2463 0
# 4 4 1762 29 2 0 1762 0 0
# 5 5 2784 31 4 0 0 0 2784
# 6 6 999 42 1 999 0 0 0
# 7 7 2111 23 2 0 2111 0 0
# 8 8 1665 36 3 0 0 1665 0
# 9 9 2341 21 4 0 0 0 2341
# 10 10 1723 33 1 1723 0 0 0
DATA
dat <- read.table(text = "regions admit men_age group
1 1234 34 2
2 3416 51 1
3 2463 26 3
4 1762 29 2
5 2784 31 4
6 999 42 1
7 2111 23 2
8 1665 36 3
9 2341 21 4
10 1723 33 1",
header = TRUE)

Answer 2

A Base R solution would be using ifelse(). Supposed you data.frame is x, you could do this:
# create the columns with the selected values
for( i in 1:4 ) x[ i + 4 ] <- ifelse( x$group == i, x$admit, 0 )
# rename the columns to your liking
colnames( x )[ 5:8 ] <- c( "admit1", "admit2", "admit3", "admit4" )
This gives you
> x
regions admit men_age group admit1 admit2 admit3 admit4
1 1 1234 34 2 0 1234 0 0
2 2 3416 51 1 3416 0 0 0
3 3 2463 26 3 0 0 2463 0
4 4 1762 29 2 0 1762 0 0
5 5 2784 31 4 0 0 0 2784
6 6 999 42 1 999 0 0 0
7 7 2111 23 2 0 2111 0 0
8 8 1665 36 3 0 0 1665 0
9 9 2341 21 4 0 0 0 2341
10 10 1723 33 1 1723 0 0 0
If you don't like the explicit naming, you could do it in the for() loop already:
for( i in 1:4 )
{
adm <- paste ( "admit", i, sep = "" )
x[ adm ] <- ifelse( x$group == i, x$admit, 0 )
}