CODEWITHSUNDEEP
rfactors
ljh2001
ljh2001

Reputation: 463

Coding a new factor based on levels of a numeric variable

I'm trying to create a factor column based on numeric values from another column. Here's a subset of my data: 

> dput(sample)
structure(list(ID = c(1683L, 1684L, 1684L, 1684L, 1684L, 1685L, 
1685L, 1685L, 1685L, 1686L, 1686L, 1686L, 1686L, 30759L, 30759L, 
30759L, 30759L, 30760L, 30760L, 30760L, 30760L), Month = structure(c(2L, 
2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 3L, 1L, 2L, 
2L, 3L, 1L, 2L), .Label = c("Jun", "Jul", "Aug"), class = "factor"), 
    Year = c(2018, 2017, 2017, 2018, 2018, 2017, 2017, 2018, 
    2018, 2017, 2017, 2018, 2018, 2017, 2017, 2018, 2018, 2017, 
    2017, 2018, 2018), Homerange = c(NA, 27.2850594918174, NA, 
    NA, NA, NA, 30.52684873837, NA, NA, NA, 30.7069481409563, 
    10.625864752589, 29.2661529202662, 32.3278427642325, NA, 
    NA, NA, NA, 33.8586876862157, NA, NA)), out.attrs = list(
    dim = c(58L, 4L, 2L), dimnames = list(Var1 = c("Var1= 1657", 
    "Var1= 1658", "Var1= 1659", "Var1= 1660", "Var1= 1661", "Var1= 1662", 
    "Var1= 1663", "Var1= 1664", "Var1= 1666", "Var1= 1667", "Var1= 1668", 
    "Var1= 1669", "Var1= 1670", "Var1= 1671", "Var1= 1672", "Var1= 1673", 
    "Var1= 1674", "Var1= 1675", "Var1= 1676", "Var1= 1678", "Var1= 1679", 
    "Var1= 1680", "Var1= 1681", "Var1= 1682", "Var1= 1683", "Var1= 1684", 
    "Var1= 1685", "Var1= 1686", "Var1=30759", "Var1=30760", "Var1=30761", 
    "Var1=30762", "Var1=30763", "Var1=30764", "Var1=30765", "Var1=30766", 
    "Var1=30767", "Var1=30768", "Var1=30769", "Var1=30770", "Var1=30771", 
    "Var1=30772", "Var1=30773", "Var1=30774", "Var1=30775", "Var1=30776", 
    "Var1=30777", "Var1=30778", "Var1=30779", "Var1=30780", "Var1=30781", 
    "Var1=30782", "Var1=30783", "Var1=30784", "Var1=30785", "Var1=30786", 
    "Var1=30787", "Var1=30788"), Var2 = c("Var2=Jun", "Var2=Jul", 
    "Var2=Aug", "Var2=Sep"), Var3 = c("Var3=2017", "Var3=2018"
    ))), row.names = c(315L, 84L, 142L, 258L, 316L, 85L, 143L, 
259L, 317L, 86L, 144L, 260L, 318L, 87L, 145L, 261L, 319L, 88L, 
146L, 262L, 320L), class = "data.frame")

The numeric column "ID" has values from 1659-1685 and 30759-30788. What I would like to do is create a factor column "Type" with 2 levels "V13" which corresponds to IDs 1659-1685, and "V16" which corresponds to IDs 30759-30788. I know I've done this before but for some reason I can't remember how. Thanks for the help!

Upvotes: 1

Views: 78

Answers (2)

jay.sf
jay.sf

Reputation: 73212

Straight base R solution would be to apply ifelse.

sample <- transform(sample,
                    Type=factor(ifelse(ID %in% 1659:1685, "V13", 
                                       ifelse(ID %in% 30759:30788, "V16",
                                              NA))))

Or slightly more efficient with cut (credits to @camille):

transform(sample, Type2=cut(sample$ID, c(1659, 1685, 1686, 30788), include.lowest=TRUE,
                            labels=c("V13", NA, "V16")))

or with data.table::inrange

library(data.table)
sample <- transform(sample,
                    Type=factor(ifelse(ID %inrange% c(1659, 1685), "V13", 
                                       ifelse(ID %inrange% c(30759, 30788), "V16",
                                              NA))))

 

str(sample)
# 'data.frame': 21 obs. of  5 variables:
# $ ID       : int  1683 1684 1684 1684 1684 1685 1685 1685 1685 1686 ...
# $ Month    : Factor w/ 3 levels "Jun","Jul","Aug": 2 2 3 1 2 2 3 1 2 2 ...
# $ Year     : num  2018 2017 2017 2018 2018 ...
# $ Homerange: num  NA 27.3 NA NA NA ...
# $ Type     : Factor w/ 2 levels "V13","V16": 1 1 1 1 1 1 1 1 1 NA ...

Upvotes: 3

MrNetherlands
MrNetherlands

Reputation: 940

Assuming that it is on purpose that ID 1686 it not considered in your ranges you can try this:

library(dplyr)
library(forcats)
df %>% 
  mutate(type = case_when(between(ID, 1659, 1685) ~ "V13",
                          between(ID, 30759, 30788) ~ "V16")) %>%
  mutate(type = as_factor(type))

# A tibble: 21 x 5
      ID Month  Year Homerange type 
   <int> <fct> <dbl>     <dbl> <fct>
 1  1683 Jul    2018      NA   V13  
 2  1684 Jul    2017      27.3 V13  
 3  1684 Aug    2017      NA   V13  
 4  1684 Jun    2018      NA   V13  
 5  1684 Jul    2018      NA   V13  
 6  1685 Jul    2017      NA   V13  
 7  1685 Aug    2017      30.5 V13  
 8  1685 Jun    2018      NA   V13  
 9  1685 Jul    2018      NA   V13  
10  1686 Jul    2017      NA   NA   
11  1686 Aug    2017      30.7 NA   
12  1686 Jun    2018      10.6 NA   
13  1686 Jul    2018      29.3 NA   
14 30759 Jul    2017      32.3 V16  
15 30759 Aug    2017      NA   V16  
16 30759 Jun    2018      NA   V16  
17 30759 Jul    2018      NA   V16  
18 30760 Jul    2017      NA   V16  
19 30760 Aug    2017      33.9 V16  
20 30760 Jun    2018      NA   V16  
21 30760 Jul    2018      NA   V16

Upvotes: 3

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