Convert from lowercase to uppercase all values in all character variables in dataframe

Question

I have a mixed dataframe of character and numeric variables.

city,hs_cd,sl_no,col_01,col_02,col_03
Austin,1,2,,46,Female
Austin,1,3,,32,Male
Austin,1,4,,27,         


        

Answer 1

If you need to deal with data.frames that include factors you can use:

df = data.frame(v1=letters[1:5],v2=1:5,v3=letters[10:14],v4=as.factor(letters[1:5]),v5=runif(5),stringsAsFactors=FALSE)

df
    v1 v2 v3 v4        v5
    1  a  1  j  a 0.1774909
    2  b  2  k  b 0.4405019
    3  c  3  l  c 0.7042878
    4  d  4  m  d 0.8829965
    5  e  5  n  e 0.9702505


sapply(df,class)
         v1          v2          v3          v4          v5
"character"   "integer" "character"    "factor"   "numeric"

Use mutate_each_ to convert factors to character then convert all to uppercase

   upper_it = function(X){X %>% mutate_each_( funs(as.character(.)), names( .[sapply(., is.factor)] )) %>%
   mutate_each_( funs(toupper), names( .[sapply(., is.character)] ))}   # convert factor to character then uppercase

Gives

  upper_it(df)
      v1 v2 v3 v4
    1  A  1  J  A
    2  B  2  K  B
    3  C  3  L  C
    4  D  4  M  D
    5  E  5  N  E

While

sapply( upper_it(df),class)
         v1          v2          v3          v4          v5
"character"   "integer" "character" "character"   "numeric"

Answer 2

From the dplyr package you can also use the mutate_all() function in combination with toupper(). This will affect both character and factor classes.

library(dplyr)
df <- mutate_all(df, funs=toupper)

Answer 3

Alternatively, if you just want to convert one particular row to uppercase, use the code below:

df[[1]] <- toupper(df[[1]])

Answer 4

Starting with the following sample data :

df <- data.frame(v1=letters[1:5],v2=1:5,v3=letters[10:14],stringsAsFactors=FALSE)

  v1 v2 v3
1  a  1  j
2  b  2  k
3  c  3  l
4  d  4  m
5  e  5  n

You can use :

data.frame(lapply(df, function(v) {
  if (is.character(v)) return(toupper(v))
  else return(v)
}))

Which gives :

  v1 v2 v3
1  A  1  J
2  B  2  K
3  C  3  L
4  D  4  M
5  E  5  N

Answer 5

A side comment here for those using any of these answers. Juba's answer is great, as it's very selective if your variables are either numberic or character strings. If however, you have a combination (e.g. a1, b1, a2, b2) etc. It will not convert the characters properly.

As @Trenton Hoffman notes,

library(dplyr)
df <- mutate_each(df, funs(toupper))

affects both character and factor classes and works for "mixed variables"; e.g. if your variable contains both a character and a numberic value (e.g. a1) both will be converted to a factor. Overall this isn't too much of a concern, but if you end up wanting match data.frames for example

df3 <- df1[df1$v1 %in% df2$v1,]

where df1 has been has been converted and df2 contains a non-converted data.frame or similar, this may cause some problems. The work around is that you briefly have to run

df2 <- df2 %>% mutate_each(funs(toupper), v1)
#or
df2 <- df2 %>% mutate_each(df2, funs(toupper))
#and then
df3 <- df1[df1$v1 %in% df2$v1,]

If you work with genomic data, this is when knowing this can come in handy.

Answer 6

It simple with apply function in R

f <- apply(f,2,toupper)

No need to check if the column is character or any other type.