Problem collapsing levels of a factor in R

user_14671004 0
Viewed 83

I have a messy factor variable with more levels than it should have. The cases come from an open survey and many participants wrote with typos or just responded a similar answer in different ways.

This is a sample df that represent my problem:


df <- data.frame(ID=seq(1:10),
                 Nationality=c("espanol", "spaniol", "ESPANOL",
                               "spanish", "colombia", "Colombian",
                               "British", "brit", "ESPanol", "UK")
                               )

The output I would like is this:

> df
   ID Nationality
1   1     Spanish
2   2     Spanish
3   3     Spanish
4   4     Spanish
5   5   Colombian
6   6   Colombian
7   7     British
8   8     British
9   9     Spanish
10 10     British

This is what I have tried to do in order to reduce this 10 artificial levels of the factor to just 3 (Spanish, Colombian, British) as it should be:

library(forcats) 
                              
levels(df$Nationality) <- fct_collapse(df$Nationality, Spanish = c("espanol", "spaniol", "ESPANOL",
                                                                  "spanish", "ESPanol"),
                                                       Colombian = c("colombia", "Colombian"),
                                                       British = c("British", "brit", "UK")
                                        )

This effectively reduces my "nationality" factor to 3 levels, but the output is looks like this and does not correspond to anything similar to the first one:

> df
   ID Nationality
1   1   Colombian
2   2     British
3   3     British
4   4     Spanish
5   5     Spanish
6   6     Spanish
7   7     Spanish
8   8     Spanish
9   9   Colombian
10 10     British

In the bigger dataset I am working with, it does not work either, but the output is worse in the sense that all cases become "Spanish" and I have no single cue about why this could be happening.

Thanks in advance for any help! Best, Lucas

r-factor r
2 Answers

Have you tried making Nationality a factor first?

df <- data.frame(ID=seq(1:10),
                 Nationality=c("espanol", "spaniol", "ESPANOL",
                               "spanish", "colombia", "Colombian",
                               "British", "brit", "ESPanol", "UK")
)
library(forcats) 


df2 <- df %>% 
  mutate(Nationality = factor(Nationality)) %>% 
 mutate(Nationality = fct_collapse(Nationality, Spanish = c("espanol", "spaniol", "ESPANOL", "spanish", "ESPanol"),
                                       Colombian = c("colombia", "Colombian"),
                                       British = c("British", "brit", "UK")))



#more concise

mutate(across(Nationality, ~ fct_collapse(factor(.), 
Spanish = c("espanol", "spaniol", "ESPANOL", "spanish", "ESPanol"), 
Colombian = c("colombia", "Colombian"), 
British = c("British", "brit", "UK")
)))
user_115358160

Here are some solutions using built-in functions:

Solution 1

This solution assumes that column Nationality is a character variable

cases <- c(espanol = "Spanish", spaniol = "Spanish", ESPANOL = "Spanish", spanish = "Spanish", 
           British = "British", brit = "British", ESPanol = "Spanish", UK = "British",
           colombia = "Colombian", Colombian = "Colombian")

df$Nationality <- factor(cases[df$Nationality])

solution 2

df$Nationality <- as.factor(df$Nationality)

levels(df$Nationality) <- list(Spanish = c("espanol", "spaniol", "ESPANOL", "spanish", "ESPanol"),
                               Colombian = c("colombia", "Colombian"),
                               British = c("British", "brit", "UK"))

output data

#    ID Nationality
# 1   1     Spanish
# 2   2     Spanish
# 3   3     Spanish
# 4   4     Spanish
# 5   5   Colombian
# 6   6   Colombian
# 7   7     British
# 8   8     British
# 9   9     Spanish
# 10 10     British
user_108488980
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