Replacing column names with another data frame if matches - r

Question

Hi I am looking into figuring out how to match data frames together by column, then renaming it. If there is no name that matches, then I would want to drop that column instead.
For example, I would use this main dataset, call it DF1:
Name
Reference
Good
Fair
Bad
Great
Poor
George
Hill
34
21
33
21
32
Frank
Stairs
29
28
29
30
29
Bertha
Trail
25
25
24
21
26
Then another DF, call this DF2, that allows me to replace the names of the columns of DF1
Name
Adjusted_Name
Good
good_run
Great
very_great_work
Bad
bad run
Fair
fair run decent
Essentially, the words that would be substituted would not be any pattern of any sort, and I would try to match this first column in DF2 and match to DF1, and if there is a match in DF2$Name and DF(whatever column), then I would replace that name with the same row of DF2$Adjusted_Name. If there is no match, then the value in DF1 is dropped.
So the final goal would be to achieve:
Name
Reference
good_run
fair run decent
Bad run
very_great_work
George
Hill
34
21
33
21
Frank
Stairs
29
28
29
30
Bertha
Trail
25
25
24
21
In this case, "poor" was dropped because it didnt match the column name of DF1.
How should I go about this? How would I account if there thousands of columns? Does that change anything in how i Code? I am a bit new to R, and would appreciate any tips. Thank you!

Answer 1

If you are open to a tidyverse solution, you could use
library(dplyr)
library(tibble)
df %>%
rename_with(~deframe(df2)[.x], .cols = df2$Name) %>%
select(Name, Reference, any_of(df2$Adjusted_Name))
This returns
# A tibble: 3 x 6
Name Reference good_run very_great_work bad_run fair_run_decent
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 George Hill 34 21 33 21
2 Frank Stairs 29 30 29 28
3 Bertha Trail 25 21 24 25
Data
df <- structure(list(Name = c("George", "Frank", "Bertha"), Reference = c("Hill",
"Stairs", "Trail"), Good = c(34, 29, 25), Fair = c(21, 28, 25
), Bad = c(33, 29, 24), Great = c(21, 30, 21), Poor = c(32, 29,
26)), class = c("spec_tbl_df", "tbl_df", "tbl", "data.frame"), row.names = c(NA,
-3L), spec = structure(list(cols = list(Name = structure(list(), class = c("collector_character",
"collector")), Reference = structure(list(), class = c("collector_character",
"collector")), Good = structure(list(), class = c("collector_double",
"collector")), Fair = structure(list(), class = c("collector_double",
"collector")), Bad = structure(list(), class = c("collector_double",
"collector")), Great = structure(list(), class = c("collector_double",
"collector")), Poor = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1L), class = "col_spec"))
df2 <- structure(list(Name = c("Good", "Great", "Bad", "Fair"), Adjusted_Name = c("good_run",
"very_great_work", "bad_run", "fair_run_decent")), class = c("spec_tbl_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -4L), spec = structure(list(
cols = list(Name = structure(list(), class = c("collector_character",
"collector")), Adjusted_Name = structure(list(), class = c("collector_character",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), skip = 1L), class = "col_spec"))

Answer 2

Try the following - using the list of adjusted names, you can grep the list of desired words against column names and subset the data frame on it:
Data
df <- read.table(header = TRUE, text = "Name Reference Good Fair Bad Great Poor
George Hill 34 21 33 21 32
Frank Stairs 29 28 29 30 29
Bertha Trail 25 25 24 21 26")
adj_name <- c("good_run","very_great_run","bad run","fair run decent")
Index the columns based on grep from the string of desired names (note the tolower() on the column names as well)
desired_words <- paste(unlist(strsplit(adj_name, "_| ")), collapse = "|")
df[,c(1:2,grep(desired_words, tolower(names(df))))]
Output
# Name Reference Good Fair Bad Great
#1 George Hill 34 21 33 21
#2 Frank Stairs 29 28 29 30
#3 Bertha Trail 25 25 24 21