Can't unite columns in R

[VictorOfili-01]

Hi,

I am a newbie to R.

I was trying to unite columns in R using the unite(employee,'name',first_name,last_name,sep=' ') but got the following:
Error in chr_as_locations():
! Can't subset columns that don't exist.
x Column first_name doesn't exist.
Run rlang::last_error() to see where the error occurred.

Please how should I resolve this?

[nirgrahamuk]

Hi, welcome!

We don't really have enough info to help you out. Could you ask this with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[VictorOfili-01]

Thank you nirgrahamuk,

This is my data frame which was manually done:

id first_name last_name job_title
1 1 John Mendes Professional
2 2 Rob Stewart Programmer
3 3 Rachel Abrahamson Management
4 4 Christy Hickman Clerical
5 5 Johnson Harper Developer
6 6 Candace Miller Programmer
7 7 Carlson Landy Management
8 8 Pansy Jordan Clerical
9 9 Darius Berry Developer
10 10 Claudia Garcia Programmer

These are the variables and their vectors:

id <- c(1:10)
name <- c("John Mendes", "Rob Stewart", "Rachel Abrahamson", "Christy Hickman", "Johnson Harper", "Candace Miller", "Carlson Landy", "Pansy Jordan", "Darius Berry", "Claudia Garcia")
job_title <- c("Professional", "Programmer", "Management", "Clerical", "Developer", "Programmer", "Management", "Clerical", "Developer", "Programmer")

This is the data frame code chunk:

employee <- data.frame(id,name,job_title)

I had originally separated the name column into first name and last name columns. Then I wanted to unite the first name and last name columns into a single name column and that was when I encountered the error I posted inititally.

[andresrcs]

I can't reproduce your issue, the code works as expected with your sample data, and you are not actually showing a reproducible example of your issue.

library(dplyr)
library(tidyr)

employee <- data.frame(
  stringsAsFactors = FALSE,
                id = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),
        first_name = c("John","Rob","Rachel",
                       "Christy","Johnson","Candace","Carlson","Pansy","Darius",
                       "Claudia"),
         last_name = c("Mendes","Stewart",
                       "Abrahamson","Hickman","Harper","Miller","Landy","Jordan",
                       "Berry","Garcia"),
         job_title = c("Professional","Programmer",
                       "Management","Clerical","Developer","Programmer",
                       "Management","Clerical","Developer","Programmer")
)

employee %>%
    unite(name, first_name, last_name, sep = " ")
#>    id              name    job_title
#> 1   1       John Mendes Professional
#> 2   2       Rob Stewart   Programmer
#> 3   3 Rachel Abrahamson   Management
#> 4   4   Christy Hickman     Clerical
#> 5   5    Johnson Harper    Developer
#> 6   6    Candace Miller   Programmer
#> 7   7     Carlson Landy   Management
#> 8   8      Pansy Jordan     Clerical
#> 9   9      Darius Berry    Developer
#> 10 10    Claudia Garcia   Programmer

^{Created on 2022-06-23 by the reprex package (v2.0.1)}

Can you try again to make a reproducible example that actually shows your problem?

[VictorOfili-01]

These are the steps I took:

id <- c(1:10)
name <- c("John Mendes", "Rob Stewart", "Rachel Abrahamson", "Christy Hickman", "Johnson Harper", "Candace Miller", "Carlson Landy", "Pansy Jordan", "Darius Berry", "Claudia Garcia")
job_title <- c("Professional", "Programmer", "Management", "Clerical", "Developer", "Programmer", "Management", "Clerical", "Developer", "Programmer")
employee <- data.frame(id,name,job_title)
employee
id name job_title
1 1 John Mendes Professional
2 2 Rob Stewart Programmer
3 3 Rachel Abrahamson Management
4 4 Christy Hickman Clerical
5 5 Johnson Harper Developer
6 6 Candace Miller Programmer
7 7 Carlson Landy Management
8 8 Pansy Jordan Clerical
9 9 Darius Berry Developer
10 10 Claudia Garcia Programmer

install.packages("dplyr")

separate(employee,name,into=c('first_name','last_name'),sep=' ')
id first_name last_name job_title
1 1 John Mendes Professional
2 2 Rob Stewart Programmer
3 3 Rachel Abrahamson Management
4 4 Christy Hickman Clerical
5 5 Johnson Harper Developer
6 6 Candace Miller Programmer
7 7 Carlson Landy Management
8 8 Pansy Jordan Clerical
9 9 Darius Berry Developer
10 10 Claudia Garcia Programmer

unite(employee,'name',first_name,last_name,sep=' ')
Error in chr_as_locations():
! Can't subset columns that don't exist.
x Column first_name doesn't exist.
Run rlang::last_error() to see where the error occurred.

[andresrcs]

tidyverse packages do not perform in-place modifications, the dataframe you are showing has a name column, when you separate it into first_name and last_name , you are not saving the changes back to the original data frame so when you try to apply tidyr::unite() on the original data frame, those columns do not exist. If you want changes to persist, you have to explicitly assign them. For example:

employee <- separate(employee,name,into=c('first_name','last_name'),sep=' ')

[VictorOfili-01]

Thank you andresrcs. Troubleshooting was successful. I appreciate!

employee<- separate(employee,name,into=c('first_name','last_name'),sep=' ')

unite(employee,'name',first_name,last_name,sep=' ')

id name job_title
1 1 John Mendes Professional
2 2 Rob Stewart Programmer
3 3 Rachel Abrahamson Management
4 4 Christy Hickman Clerical
5 5 Johnson Harper Developer
6 6 Candace Miller Programmer
7 7 Carlson Landy Management
8 8 Pansy Jordan Clerical
9 9 Darius Berry Developer
10 10 Claudia Garcia Programmer