Fill in empty values in column of dataframe by condition

Question

I have the followin dataframe. Now I want to fill in the empty values in "product" by determining the value of the code 44 and 90. 44 should be "shirt" and 90 "sweater".

What's the best way to do this? With a for loop?

data = data.frame("code" = c(44,78,21,90,100,44,90), "product" = c("","hat","shoe","","umbrella","",""))
> data
  code  product
1   44         
2   78      hat
3   21     shoe
4   90         
5  100 umbrella
6   44         
7   90      

Answer 1

Using dplyr first convert the product variable to character (from factor), then use case_when

library(dplyr)
data %>% 
  mutate_if(is.factor, as.character) %>% 
  mutate(product = case_when(product == "" & code == 44 ~ "shirt",
                             product == "" & code == 90 ~ "sweater",
                             TRUE ~ product))

  code  product
1   44    shirt
2   78      hat
3   21     shoe
4   90  sweater
5  100 umbrella
6   44    shirt
7   90  sweater

Using base , same idea - first convert factors to character than then use ifelse

i <- sapply(data, is.factor)
data[i] <- lapply(data[i], as.character)

data$product[data$product == ""] <- ifelse(data$code[data$product == ""] == 44, "shirt", "sweater")
data
  code  product
1   44    shirt
2   78      hat
3   21     shoe
4   90  sweater
5  100 umbrella
6   44    shirt
7   90  sweater

Also worth noting, if you use data.frame with stringsAsFactors = FALSE all the factor converting becomes unnecessary.

Answer 2

You can use match and use the indices for subsetting.

i <- match(data$code, c(44, 90))
j <- !is.na(i)
data$product[j] <- c("shirt", "sweater")[i[j]]
data
#  code  product
#1   44    shirt
#2   78      hat
#3   21     shoe
#4   90  sweater
#5  100 umbrella
#6   44    shirt
#7   90  sweater