Changing Names in a List of Dataframes

Changing names in a list of dataframes

You can try setNames

data.list <- lapply(data.list, setNames, new.names)

Changing Column Names in a List of Data Frames in R

With lapply you can do it as follows.

Create sample data:

df1 <- data.frame(A = 1, B = 2, C = 3)
df2 <- data.frame(X = 1, Y = 2, Z = 3)
dfList <- list(df1,df2)
colnames <- c("USAF","WBAN","YR--MODAHRMN") 

Then, lapply over the list using setNames and supply the vector of new column names as second argument to setNames:

lapply(dfList, setNames, colnames)
#[[1]]
#  USAF WBAN YR--MODAHRMN
#1    1    2            3
#
#[[2]]
#  USAF WBAN YR--MODAHRMN
#1    1    2            3

---

Edit

If you want to assign the data.frames back to the global environment, you can modify the code like this:

dfList <- list(df1 = df1, df2 = df2)
list2env(lapply(dfList, setNames, colnames), .GlobalEnv)

Change column names of data frames stored in a list by condition

dplyr::rename_with() applies a function to each column name. In that function we can check if the name contains “abund” or “individuals” with grepl() and then those columns get renamed. The columns that don’t contain the strings we are looking for technically also get renamed, but they receive their old name again, so nothing is changed there.

library(dplyr)
library(purrr)

map(lst, ~ rename_with(., ~ ifelse(
  grepl("abund|individuals", .), "abundance", .
)))
#> $spiders
#>   plot abundance habitat
#> 1    1         1  forest
#> 2    2         4  forest
#> 3    3         8  forest
#> 
#> $bugs
#>   plot abundance
#> 1    1         1
#> 2    2         4
#> 3    3         8
#> 
#> $birds
#>   plot abundance habitat
#> 1    1         1  forest
#> 2    2         4  forest
#> 3    3         8  forest
#> 4    1         1  visual
#> 5    2         4  visual
#> 6    3         8  visual

Instead of using tidyverse style anonymous functions we can use the new
base R anonymous function style in order to make the code a bit more comprehensible.

map(lst, \(df) rename_with(df, \(name) ifelse(
  grepl("abund|individuals", name), "abundance", name
)))
#> $spiders
#>   plot abundance habitat
#> 1    1         1  forest
#> 2    2         4  forest
#> 3    3         8  forest
#> 
#> $bugs
#>   plot abundance
#> 1    1         1
#> 2    2         4
#> 3    3         8
#> 
#> $birds
#>   plot abundance habitat
#> 1    1         1  forest
#> 2    2         4  forest
#> 3    3         8  forest
#> 4    1         1  visual
#> 5    2         4  visual
#> 6    3         8  visual

Change column names in list of dataframes

Try this, loop through data.frames, update column name:

# dummy list
my_list <- list(one = data.frame(a = 1:5, b = 1:5), two = data.frame(a = 1:5, b = 1:5))

my_list_updated <-
  lapply(names(my_list), function(i){
  x <- my_list[[ i ]]
  # set 2nd column to a new name
  names(x)[2] <- i
  # return
  x
})

my_list_updated 
# [[1]]
#   a one
# 1 1   1
# 2 2   2
# 3 3   3
# 4 4   4
# 5 5   5
# 
# [[2]]
#   a two
# 1 1   1
# 2 2   2
# 3 3   3
# 4 4   4
# 5 5   5

How to change the column names in all my data frames inside a list?

An easier option is set_names if we are changing the names of all the columns

foo1 <- map(foo, set_names, newNames)
foo1
#$testA
#         Jan        Feb           Mar        Apr       May
#1 -0.2886904  0.7716465  0.7103408795 -0.3209754 0.1580680
#2  0.8776646  0.1441515  1.9820892400 -2.5664872 0.2014593
#3 -1.9172889  1.4930354 -0.0005122859  2.7473145 0.9806701
#4 -0.7642281 -1.7382739  2.8574676114  0.1905533 1.0760523
#5 -0.2753768  0.4712059 -0.8955168101 -0.3923635 1.1017868

#$testB
#         Jan        Feb          Mar        Apr       May
#1 -1.2544946 -0.2131777  0.634624485  1.5436530 0.5811060
#2 -0.8092116  1.6085164  2.607820897  0.5454936 1.3869741
#3 -0.5460344  0.8028537 -0.007151318 -0.1711816 0.0867885
#4 -0.2104260 -1.3580934  0.835981664  1.3725253 0.0037494
#5 -0.6984177  1.2311613 -0.809374023 -0.2487121 0.8129935

#$testC
#         Jan         Feb        Mar         Apr         May
#1  0.3667708 -0.01209575 -0.9314844  0.05995604  0.58699473
#2  1.4171330  0.62793554 -0.2695517  2.21667643  0.90599396
#3  1.7093434 -0.98627309 -1.7552439 -0.96652771 -0.05704485
#4  0.2860338  1.34541312 -1.9608085 -1.23959279  0.19175618
#5 -0.9364102  2.47658828 -1.4883768  0.64809561 -0.99417796

---

or if we use rename_all, make sure to use the ~. According to ?rename_all, the .funs argument would be

.funs - A function fun, a purrr style lambda ~ fun(.) or a list of either form.

foo2 <- map(foo, ~ .x %>%
               rename_all(~ newNames))

identical(foo1, foo2)
#[1] TRUE

---

In the function renameColumn, there are two issues - 1) nothing is returned. 2) argument mismatch - function argument (myData) is different from the one used inside (data)

renameColumn = function(myData, new_names){
     colnames(myData) <- new_names
     myData
 }

map(foo, renameColumn, new_names = newNames)

Using lapply to change column names of list of dataframes with different column names

You can create a dataframe with the information of from and to and with lapply use setNames to match and replace the column names :

lookup_names <- data.frame(from = c("A", "B", "D", "E", "G", "H"), 
                           to = c("this", "that", "he", "she", "him", "her"))

lookup_names
#  from   to
#1    A this
#2    B that
#3    D   he
#4    E  she
#5    G  him
#6    H  her

lapply(my_list, function(x) 
        setNames(x, lookup_names$to[match(names(x), lookup_names$from)]))

#[[1]]
#   this that
#1     1   10
#2     2   11
#3     3   12
#4     4   13
#...
#...

#[[2]]
#   he she
#1  20  30
#2  21  31
#3  22  32
#4  23  33
#5  24  34
#....

---

Related Topics