CODEWITHSUNDEEP
r
rmuc8
rmuc8

Reputation: 2989

Change the value of a column, based on another column (for certain rows)

I have a dataframe df

ID <- c(1,2,3,4,5)
category <- c("Shirts", "Shirts", "Shirts", "Sweaters", "Sweaters")
subcategory <- c("V-Neck","V-Neck","Round","Striped","Striped")
df <- data.frame(ID,category,subcategory)

ID  category   subcategory
1   Shirts     V-Neck
2   Shirts     V-Neck
3   Shirts     Round
4   Sweaters   Striped
5   Sweaters   Striped

I want to assign the name of the column "subcategory" to the column "category" for all rows, where category == "Shirts"

My result should look like this:

ID  category   subcategory
1   V-Neck     V-Neck
2   V-Neck     V-Neck
3   Round      Round
4   Sweaters   Striped
5   Sweaters   Striped

I tried

library(dplyr)
res <- df %>% 
  filter(category=="Shirts") %>% 
  mutate(category=subcategory)

and the result is close to what I am looking for, but it does not contain the rows 4 and 5.

Can someone help me with this issue?

Upvotes: 3

Views: 10244

Answers (3)

zetieum
zetieum

Reputation: 151

df$category <- ifelse(df$category=="Shirts",
                      as.character(df$subcategory),
                      as.character(df$category)) 
df
#   ID category subcategory
# 1  1        V           V
# 2  2        V           V
# 3  3    Round       Round
# 4  4 Sweaters     Striped
# 5  5 Sweaters     Striped

Upvotes: 2

JoeArtisan
JoeArtisan

Reputation: 145

I know it's probably a long way round (and nowhere near as elegant as Amanda Mahto's solution) but you can convert your category and subcategory columns to characters, do your indexing and updating, then convert them back to a factor.

df$category <- as.character(df$category); df$subcategory <- as.character(df$subcategory)
indx <- category == "Shirts" ; df$category[indx] <- df$subcategory[indx]
df$category <- as.factor(df$category); df$subcategory <- as.factor(df$subcategory)

Upvotes: 1

A5C1D2H2I1M1N2O1R2T1
A5C1D2H2I1M1N2O1R2T1

Reputation: 193517

Not sure if you are looking for a "dplyr" only answer (your question isn't tagged as such) but this is very straightforward with "data.table":

library(data.table)
as.data.table(df)[category == "Shirts", category := subcategory][]
#    ID category subcategory
# 1:  1        V           V
# 2:  2        V           V
# 3:  3    Round       Round
# 4:  4 Sweaters     Striped
# 5:  5 Sweaters     Striped

I suppose with "dplyr", you could try ifelse (and possibly replace):

df[-1] <- lapply(df[-1], as.character)  ## Convert factors to characters
df %>%
  mutate(category = ifelse(category == "Shirts", 
                           subcategory, category))

Upvotes: 6

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