Deleting multiple columns in R

Question

I have a dataframe df with column names from m1 to m100

I want to delete columns in the range m50 to m100. Is there a faster way to do it than hardcoding it

Answer 1

Assuming you have something like:

mydf <- data.frame(matrix(1:100, ncol = 100, 
                          dimnames = list(NULL, paste0("m", 1:100))))

Simply do:

mydf[paste0("m", 50:100)] <- list(NULL)  ## This is pretty destructive ;-)

---

By the way, you can also do:

subset(mydf, select = m1:m49)

or

subset(mydf, select = -(m50:m100))

Answer 2

With dplyr you could do it like this:

library(dplyr)
df <- select(df, -(M50:M100))

This removes all columns between column "M50" and column "M100".

A different option, that does not depend on the order of columns is to use

df <- select(df, -num_range("M", 50:100))

Answer 3

More eloquently put, without using any external packages or extra function calls, just use R's logical subsets:

mydf <- data.frame(matrix(1:100, ncol = 100, 
                          dimnames = list(NULL, paste0("M", 1:100))))

mydf[,1:49]

yielding:

> mydf[,1:49]
  m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11 m12 m13 m14 m15 m16 m17 m18 m19 m20 m21 m22
1  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22
  m23 m24 m25 m26 m27 m28 m29 m30 m31 m32 m33 m34 m35 m36 m37 m38 m39 m40 m41 m42
1  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42
  m43 m44 m45 m46 m47 m48 m49
1  43  44  45  46  47  48  49

Answer 4

We can assign the columns to NULL in data.table

library(data.table)
setDT(df_cohort)[, paste0('M', 50:100) := NULL]

If we need to subset,

setDT(df_cohort)[, setdiff(names(df_cohort), 
                    paste0('m', 50:100)), with=FALSE]