Creating a new column depending on the observations in another column

Question

I want to create a new column in R dependant on other columns in r. The format would be

new_column 0 1 0 0 1

I have three variables that the new column will be made from

comorbidity
date_of_comorbidity
DOB

I have tried using ifelse but I get an error (this is what I have tried)

newdata$newcolumn<-NA

ifelse(newdata$comorbidity1==10 &newdata$date_of_comorbidity>=DOB, newdata$newcolumn<-1,
    ifelse(newdata$comorbidity1==10 &newdata$date_of_comorbidity<DOB, newdata$newcolumn<-0))

the error message is

Error in ifelse(newdata$comorbidity1==10 &newdata$date_of_comorbidity<DOB,  : 
argument "no" is missing

can this be fixed or is there a better way of solving my problem

Answer 1

It would be helpful if you could expand on the criteria you want to use to create new_column. This link has some good tips on how to get the best answer on SO.

dplyr::mutate is an easy way to create new columns in a dataframe. case_when is useful for defining your criteria.

Create the data:

library(tidyverse)

test_data <- test_data <- structure(list(comorbidity = c(0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 
                                            0L, 1L), date_of_comorbidity = c(93L, 72L, 81L, 52L, 26L, 30L, 
                                                                             80L, 45L, 97L, 96L), DOB = c(123L, 145L, 192L, 176L, 189L, 164L, 
                                                                                                          158L, 170L, 145L, 121L)), row.names = c(NA, -10L), class = c("tbl_df", 
                                                                                                                                                                       "tbl", "data.frame"))

# A tibble: 10 x 3
comorbidity date_of_comorbidity   DOB
<int>               <int> <int>
0                  93   123
0                  72   145
1                  81   192
1                  52   176
1                  26   189
1                  30   164
1                  80   158
1                  45   170
0                  97   145
1                  96   121

Create new_column:

test_data <- test_data %>% 
  mutate(new_column = case_when(comorbidity == 1 & date_of_comorbidity > 50 ~ TRUE,
                                comorbidity == 0 | date_of_comorbidity <= 50 ~ FALSE))

# A tibble: 10 x 4
comorbidity date_of_comorbidity   DOB new_column
<int>       <int>                 <int> <lgl>     
1           1                  99   115 TRUE      
2           1                  89   147 TRUE      
3           1                  55   188 TRUE      
4           0                  63   155 FALSE     
5           1                  38   179 FALSE     
6           1                   1   166 FALSE     
7           1                  17   139 FALSE     
8           1                   9   127 FALSE     
9           1                  96   181 TRUE      
10          1                  61   127 TRUE  

Answer 2

newdata$newcolumn<- ifelse(newdata$comorbidity1==10 & newdata$date_of_comorbidity>=newdata$DOB, 1,
   ifelse(newdata$comorbidity1==10 & newdata$date_of_comorbidity<newdata$DO,0,NA))