重命名 R 中列中的所有值

Question

I have a dataset, df, with the following values:

ID                                        Duration   
abcdefghijklmnopqrstuvwxyz                1 sec
abcdefghijklmnopqrstuvwxyz1               0 sec
abcdefghijklmnopqrstuvwxyz2               0 sec                    
abcdefghijklmnopqrstuvwxyz3               1 sec
abcdefghijklmnopqrstuvwxyz4               0 sec

Goal: I am plotting a histogram, and the values are just too lengthy. I would like to convert the values within the column ID to a shorter value such as:

ID                                        Duration   
A                                         1 sec
B                                         0 sec
C                                         0 sec                    
D                                         1 sec
E                                         0 sec

To do this, would I have to specify and write out every value within the row? (there are 100's of them)

rename.values(df, abcdefghijklmnopqrstuvwxyz="A")...

Answer 1

Without the use of dplyr , if you want to rename all values in your column ID to a shorter ID (and assuming that all of your IDs are different), you can write:

df$ID <- paste0("A",1:nrow(df))

Alternative: Using gsub

Alternatively, if you have a very long pattern that you wish to replace (such abcdef....), you can use gsub :

df$ID <- gsub("abcdefghijklmnopqrstuvwxyz","A",df$ID)

The advantage with gsub is that if you have an ID repeted multiple times, it will conserve this repetition because it will replace only the first part of the ID string.

Example

a <- paste0(letters[1:26], collapse = "")
df <- data.frame(ID = paste0(a,1:100),
                value = rnorm(100))

So, your df looks like:

  ID      value
1 A1  2.6977546
2 A2  1.9434639
3 A3  0.4191808
4 A4 -0.1545246
5 A5  2.0112518
6 A6  0.5877203
...

Now, if you replace character strings of ID by the following command:

df$ID <- paste0("A",1:100)

or with gsub :

df$ID <- gsub("abcdefghijklmnopqrstuvwxyz","A",df$ID)

And you get:

  ID      value
1 A1  2.6977546
2 A2  1.9434639
3 A3  0.4191808
4 A4 -0.1545246
5 A5  2.0112518
6 A6  0.5877203
...

So, you conserved all of your columns and values in the same order and you just modify the ID column.

Answer 2

You could simply create a new ID column, which would solve your issue and also preserve your original IDs (this assumes no duplicate IDs).

df <- df %>%
   mutate(ID2 = 1:nrow(df)) %>%
   select(ID2, Duration)        #  OR       select(-ID) : deselects ID, keeps everything else.