How to creat multiple columns of dummies for intervals in R

Question

data$Distance_100<-0
data$Distance_100[data$Distance<100]<-1

data$Distance_200<-0
data$Distance_200[data$Distance>=101&data$Distance<200]<-1

data$Distance_300<-0
data$Distance_300[data$Distance>=201&data$Distance<300]<-1

data$Distance_400<-0
data$Distance_400[data$Distance>=301&data$Distance<400]<-1

data$Distance_500<-0
data$Distance_500[data$Distance>=401&data$Distance<500]<-1

The outcome must be multiple columns. This code creat just one column data$DistanceCut5 = cut(data$Distance, breaks=c(0,100,200,300,400,500))

Answer 1

cut will create a single column, but if you want 1 column for each cut level you could do something like this:

Example

Libraries

library(tidyverse)

Code

# Vector with a sequence from 0 to 500 by 100
seq_0_500 <- seq(0,500,100)

# Example data.frame
tibble(
  # Variable distance = sequence from 1 to 500 by 1
  distance = 1:500
) %>% 
  mutate(
    #Create a categoric variable by 100: `(0,100]` `(100,200]` `(200,300]` `(300,400]` `(400,500]`
    distance_cut = cut(distance,seq_0_500, labels = paste0("Distance_",seq_0_500[-1])),
    #Auxiliar variable
    aux = 1
    ) %>% 
  # Pivot data to make one column for each cut level
  pivot_wider(names_from = distance_cut,values_from = aux) %>% 
  # Replace every NA for 0
  replace(is.na(.),0)

Output

# A tibble: 500 x 6
   distance Distance_100 Distance_200 Distance_300 Distance_400 Distance_500
      <int>        <dbl>        <dbl>        <dbl>        <dbl>        <dbl>
 1        1            1            0            0            0            0
 2        2            1            0            0            0            0
 3        3            1            0            0            0            0
 4        4            1            0            0            0            0
 5        5            1            0            0            0            0
 6        6            1            0            0            0            0
 7        7            1            0            0            0            0
 8        8            1            0            0            0            0
 9        9            1            0            0            0            0
10       10            1            0            0            0            0
# ... with 490 more rows