I have two dataframes.
The first one has thousands of columns which represent a given city followed by the year, like "London_2001", "London_2002", and some measurements in the rows.
The second dataframe has two columns. The first one is a territorial region, and the second one a list of cities. Something like:

df1 <- data.frame(London_2021 = c(3,6,83,25,4),
                  London_2022 = c(3,6,83,25,4),
                  Berlin_2021 = c(3,6,83,25,4),
                  Berlin_2022 = c(3,6,83,25,4),
                  BerlinSuburbs_2021 = c(3,6,83,25,4),
                  BerlinSuburbs_2022 = c(3,6,83,25,4),
                  Tokyo_2021 = c(3,6,83,25,4),
                  Tokyo_2022 = c(3,6,83,25,4))

df2 <- data.frame(TerritorialRegion = c("Pacific", "Europe"),
                  Cities = c("Tokyo", "London, Berlin"))

I want to create a list, where each of the elements of the list will be a dataframe.
This dataframe will be called as the territorial region, and will have as columns each of the cities.

In this case your list will be something like:

List
 [1] Pacific
 [2] Europe

And if you access europe as in list[2] you would get:

London_2021 | London_2022 | Berlin_2021 | Berlin_2022

As you can see, we want strictly the same name, so BerlibSuburbswouldn’t appear in our dataframe,

I tried this, but is not working:

library(dplyr)
library(tidyr)

# step 1
df2 <- df2 %>% 
  separate_rows(Cities, sep = ",\\s*")

# step 2
df1_long <- df1 %>% 
  pivot_longer(cols = everything(), 
               names_to = c("City", "Year"), 
               names_sep = "_")

# step 3
df_merged <- df2 %>% 
  left_join(df1_long, by = c("Cities" = "City"))

# step 4
df_list <- df_merged %>% 
  split(.$TerritorialRegion)

>Solution :

You could get this output using purrr mapping and dplyr::select

purrr::map(df2$Cities, function(x) {
  select(df1, starts_with(paste0(strsplit(x, ",\\s*")[[1]], "_")))
}) |> 
  purrr::set_names(df2$TerritorialRegion)

which returns

$Pacific
  Tokyo_2021 Tokyo_2022
1          3          3
2          6          6
3         83         83
4         25         25
5          4          4

$Europe
  London_2021 London_2022 Berlin_2021 Berlin_2022
1           3           3           3           3
2           6           6           6           6
3          83          83          83          83
4          25          25          25          25
5           4           4           4           4