In R, conditionally mutate a new column for all of an ID's rows-CodePudding

Background

I've got this dataframe df:

df <- data.frame(ID =    c("a","a","a","b", "c","c","c","c"),
                 event = c("red","black","blue","white", "orange","red","gray","green"),
                 stringsAsFactors=FALSE)

It's got some people in it (ID) and a description of an event. I'd like to make a new variable condition that indicates 1 or 0 based on whether any of the cells for a given ID contain either "red" or "blue".

The Problem

I can get this work, but only for the matching row. What I'd like is that if any of a person's cells in event contain "red" or "blue", all their cells in condition should be marked 1. In other words, I'd like this:

ID  event condition
 a    red         1
 a  black         1
 a   blue         1
 b  white         0
 c orange         1
 c    red         1
 c   gray         1
 c  green         1

What I've tried

So far, I've used this code to get this result:

df <- df %>%
mutate(condition = ifelse(df$event %in% c("red","blue"), 1, 0))

ID  event condition
 a    red         1
 a  black         0
 a   blue         1
 b  white         0
 c orange         0
 c    red         1
 c   gray         0
 c  green         0

In other words, the rows that match are marked 1, but I'd like all rows for an ID with any matching row to be marked 1.

CodePudding user response：

We need any wrapped around the logical vector from %in%- in addition the arguments can be reversed (In the OPs code, it is return 1 where it matches the elements 'red' or 'blue', leaving the others 0.

library(dplyr)
df %>% 
   group_by(ID) %>% 
   mutate(condition =  (any(c('red', 'blue') %in% event))) %>%
   ungroup

-output

# A tibble: 8 × 3
  ID    event  condition
  <chr> <chr>      <int>
1 a     red            1
2 a     black          1
3 a     blue           1
4 b     white          0
5 c     orange         1
6 c     red            1
7 c     gray           1
8 c     green          1

CodePudding user response：

Here is an alternative approach:

library(dplyr)
library(stringr)

df %>% 
  group_by(ID) %>% 
  mutate(condition = if_else(str_detect(event, paste(c("red", "blue"), collapse = "|")), 1, 0))

  ID    event  condition
  <chr> <chr>      <dbl>
1 a     red            1
2 a     black          0
3 a     blue           1
4 b     white          0
5 c     orange         0
6 c     red            1
7 c     gray           0
8 c     green          0