Add multiple new columns to the dataset, based on another dataset's elements

Question

I have the following products list

> products
# A tibble: 311 x 1
   value                    
   <fct>                    
 1 NA                       
 2 Alternativ Economy
 3 Ambulant Balance  
 4 Ambulant Economy  
 5 Ambulant Premium  
 6 Ambulant 2               
 7 Ambulant 3               
 8 Ambulant 1               
 9 COMPLETA                 
10 HOSPITAL ECO             
# ... with 301 more rows

and the following df

> df <- data.frame(employee = c('John Doe','Peter Gynn','Jolie Hope'), 
+           salary = c(21000, 23400, 26800), 
+           startdate = as.Date(c('2010-11-1','2008-3-25','2007-3-14')))
> df
    employee salary  startdate
1   John Doe  21000 2010-11-01
2 Peter Gynn  23400 2008-03-25
3 Jolie Hope  26800 2007-03-14

Now, I want to add the elements of the former (i.e. products) as variables of the latter (i.e. the df). I use

cbind(df, setNames(lapply(products, function(x) x = NA), products))

but I get an error. Can you suggest another way of doing this? What is wrong with my solution? thanks in advance

Maybe you want `df[na.omit(as.character(products$value))] <- NA`. — Ritchie Sacramento, Oct 28 '20 at 21:33
then the solution proposed by 27 ϕ 9 is what you're looking for. — Edo, Oct 28 '20 at 21:35
Possible duplicate https://stackoverflow.com/questions/25357194/how-to-add-multiple-columns-to-a-data-frame-in-one-go — Ronak Shah, Oct 29 '20 at 04:07

score 0 · Answer 1 · answered Oct 28 '20 at 21:47

Here is one solution.

df <- data.frame(employee = c('John Doe','Peter Gynn','Jolie Hope'), 
                 salary = c(21000, 23400, 26800), 
                 startdate = as.Date(c('2010-11-1','2008-3-25','2007-3-14')))

products <- data.frame(value = c(NA, "Alternativ Economy", "COMPLETA"))
#products$value <- ifelse(is.na(products$value), "not_available", as.character(products$value))

cbind(df, `colnames<-`(data.frame(matrix(ncol = nrow(products), nrow = nrow(df))), products$value))

    employee salary  startdate NA Alternativ Economy COMPLETA
1   John Doe  21000 2010-11-01 NA                 NA       NA
2 Peter Gynn  23400 2008-03-25 NA                 NA       NA
3 Jolie Hope  26800 2007-03-14 NA                 NA       NA

I question the wisdom of having NAs as column names, so I'd uncomment that one line of code in there to replace NAs with some character string instead.

Add multiple new columns to the dataset, based on another dataset's elements

1 Answers1