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

对着背影说爱祢 提交于 2019-11-28 19:59:59

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
Trenton Hoffman

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)
Shalini Baranwal

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.

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.

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"

Another alternative is to use a combination of mutate_if() and str_to_uper() function, both from the tidyverse package:

df %>% mutate_if(is.character, str_to_upper) -> df

This will convert all string variables in the data frame to upper case. str_to_lower() do the opposite.

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

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

标签
易学教程内所有资源均来自网络或用户发布的内容,如有违反法律规定的内容欢迎反馈
该文章没有解决你所遇到的问题?点击提问,说说你的问题,让更多的人一起探讨吧!