Spread columns by count in R dplyr

Question

I have a factor column. I would like to spread into one column for each factor and then fill the gaps by the count of that factor appears for each id. Suppose we have:

car <- c("a","b","b","b","c","c","a","b","b","b","c","c")
type <- c("good", "regular", "bad","good", "regular", "bad","good", "regular", "bad","good", "regular", "bad")
car_type <- data.frame(car,type)

and get:

   car    type
1    a    good
2    b regular
3    b     bad
4    b    good
5    c regular
6    c     bad
7    a    good
8    b regular
9    b     bad
10   b    good
11   c regular
12   c     bad

I want this:

> results
  car good regular bad
1   a    2       0   0
2   b    2       2   2
3   c    0       2   2

I try this using dplyr, but I'm not really use to it, so It doesn't work.

car_type %>%
  select(car, type) %>%
  group_by(car) %>%
  mutate(seq = unique(type)) %>%
  spread(seq, type)

I would thanks any help.

Answer 1

Update for tidyr::pivot_wider:

library(tidyverse)

car_type %>% 
  count(car, type) %>% 
  pivot_wider(names_from=type, values_from=n, values_fill=0)

Original Answer

With reshape2:

library(reshape2)

dcast(car_type, car ~ type)

If you were going to use dplyr, the code would be:

dplyr and reshape2

car_type %>% count(car, type) %>%
  dcast(car ~ type, fill=0)

dplyr and tidyr

car_type %>% count(car, type) %>%
  spread(type, n, fill=0)

In each case, count(car, type) is equivalent to

group_by(car, type) %>% tally

or

group_by(car, type) %>% summarise(n=n())

With data.table

library(data.table)

dcast(setDT(car_type), car ~ type, fill=0)