CODEWITHSUNDEEP
rlogical-operators
TestGuest
TestGuest

Reputation: 603

Insert column based on logical conditions in R

I am selecting rows from my data based on either one of the conditions with the "filter" function:

Subset_data <- filter(Data, company_type == 3 & annualturnover %in% c(1,2,3) | company_type == 2 & annualturnover %in% c(1,2))

Now I want to add a column which has the value "0" when the row fulfills the first condition (company_type == 3 & annualturnover %in% c(1,2,3)), and the value "1" if the second condition is fulfilled (company_type == 2 & annualturnover %in% c(1,2)).

How can I do that efficiently (no looping if possible)?

Upvotes: 1

Views: 383

Answers (2)

jay.sf
jay.sf

Reputation: 72803

You could simply use ifelse then exclude NA cases.

dat$cat <- with(dat, ifelse(company_type == 3 & annualturnover %in% 1:3, 0,
                            ifelse(company_type == 2 & annualturnover %in% 1:2, 1, NA)))
dat <- dat[!is.na(dat$cat), ]
dat
#   company_type annualturnover cat
# 2            3              3   0
# 3            2              2   1

(Using @JonSpring's data.)

Upvotes: 1

Jon Spring
Jon Spring

Reputation: 66480

library(dplyr)
Subset_data <- Data %>%
  filter(company_type == 3 & annualturnover %in% c(1,2,3) | 
           company_type == 2 & annualturnover %in% c(1,2)) %>%
  mutate(category = case_when(
    company_type == 3 & annualturnover %in% c(1,2,3) ~ 0L,
    company_type == 2 & annualturnover %in% c(1,2)   ~ 1L,
    TRUE ~ NA_integer_))

Subset_data
## A tibble: 2 x 3
#  company_type annualturnover category
#         <int>          <int>    <int>
#1            3              3        0
#2            2              2        1

using this fake data

Data <- tribble(
  ~company_type, ~annualturnover,
  1L, 2L,
  3L, 3L,
  2L, 2L,
  2L, 3L)

Upvotes: 2

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