Pivot numeric value column wider based on logical columns

I have a table that has a signal value and additional columns defining the type of signal. Each location has all types of signal. See example:

d <- data.frame("location"=c("L1","L1","L1","L2","L2","L2"),"signal"=c(1.1,1.04,1.75,1.24,2.2,22),"type1"=c(1,0,0,1,0,0),"type2"=c(0,1,0,0,1,0),"type3"=c(0,0,1,0,0,1))
d
 location signal type1 type2 type3
1       L1   1.10     1     0     0
2       L1   1.04     0     1     0
3       L1   1.75     0     0     1
4       L2   1.24     1     0     0
5       L2   2.20     0     1     0
6       L2  22.00     0     0     1

I would like to pivot this table wide so each type of signal has its own column depicting the signal such as:

location type1 type2 type3
L1 1.10 1.04 1.75
L2 1.24 2.20 22.00

Thank you.

>Solution :

The trick here will be converting the data set to a tidy (long) format, because right now it’s a blend of wide and long. Here’s one way of doing that, with the pivot_wider at the very end.

library(tidyverse)
d %>%
  pivot_longer(starts_with("type")) %>%
  filter(value>0) %>%
  select(-value) %>%
  pivot_wider(names_from = name, values_from = signal)

# A tibble: 2 x 4
  location type1 type2 type3
  <chr>    <dbl> <dbl> <dbl>
1 L1        1.1   1.04  1.75
2 L2        1.24  2.2  22