How to Add a Prefix to Several Variable Names Using Dplyr

How do I add a prefix to several variable names using dplyr?

Indeed, you can use rename_ (NSE rename itself doesn’t work):

data %>% rename_(.dots = setNames(names(.), paste0('cars.', names(.))))

… but honestly, why? Just assigning names directly is shorter and more readable:

data %>% setNames(paste0('cars.', names(.)))

Adding prefix or suffix to most data.frame variable names in piped R workflow

You can pass functions to rename_at, so do

 means14 <- dat14 %>%
  group_by(class) %>%
  select(-ID) %>%
  summarise_all(funs(mean(.))) %>% 
  rename_at(vars(-class),function(x) paste0(x,"_2014"))

Rename all columns except id column by adding a prefix using dplyr

library(dplyr)

df %>% 
  dplyr::rename_with(~ paste0("source_", .), -id)

The third argument to rename_with is .cols, where you can use tidyselect syntax to select the columns. Here -id excludes this column.

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Per the comments the . syntax is a cleaner/simpler style than an writing an anonymous function, but you could accomplish this equivalently as:

df %>% 
  dplyr::rename_with(function(x) paste0("source_", x), -id)

Add a prefix to column names

You have misread the help file. Here's the argument to look at:

do.NULL: logical. If FALSE and names are NULL, names are created.

Notice the and in that description. Your names are no longer NULL, so using prefix won't work.

Instead, use something like this:

> m2 <- cbind(1,1:4)
> colnames(m2) <- c("x","Y")
> colnames(m2) <- paste("Sub", colnames(m2), sep = "_")
> m2
     Sub_x Sub_Y
[1,]     1     1
[2,]     1     2
[3,]     1     3
[4,]     1     4

Adding a suffix to a selection of column names in tidyverse

You may select columns in rename_with -

library(dplyr)

df %>% rename_with(~paste0("a", .x), c(x, y))

#  ax ay z
#1  1  3 5
#2  2  4 6

Adding a prefix to a column name using the value of different column using dplyr

Here is a workaround solution. It only looks at the first row of time_period and takes what ever value it finds there:

df %>% {rename_at(., vars(sum), function(x) paste(pull(., time_period)[1], x, sep = "_"))}

# A tibble: 3 x 2
  year_sum time_period
     <dbl> <chr>      
1      150 year       
2      175 year       
3      200 year 

Adding a prefix to certain column names

Try this:

colnames(m2)[1] <- paste0("Sub", "_", colnames(m2)[1])
# or if you prefer paste
#colnames(m2)[1] <- paste("Sub", colnames(m2)[1], sep = "_")

How to rename mutliples columns names (with prefix) according to respective dataframe name [R]

First, refer to elements of the list with double square brackets, like so List_df_EU[[i]] (List_df_EU[i] is a sub-list of 1 element, not the element itself).

Second, we could create List_df_EU with tibble::lst() instead of list(), so that elements are automatically named. Then, "AS" can be replaced with names(List_df_EU)[i].

List_df_EU <- tibble::lst(....)

for(i in 1:length(List_df_EU)) {                              
  colnames(List_df_EU[[i]]) <- paste(
    names(List_df_EU)[i], colnames(List_df_EU[[i]]), sep = "_")
}

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Edit

To allow the subsequent join on OBJECTID, we could rename all columns but OBJECTID, for instance using dplyr that has a nice interface for this:

for(i in 1:length(List_df_EU)) {                              
  List_df_EU[[i]] <- dplyr::rename_with(
    List_df_EU[[i]],
    ~ paste(names(List_df_EU)[i], .x, sep = "_"),
    .cols = - OBJECTID
  )
}

How to use rename_with() in pipe to change all column names from vector

It doesn't seem like rename_with is the right function for this. I guess you could do

iris %>% 
  rename_with(~newcolnames)

as kind of a hack. You can also use rename

iris %>% 
  rename(!!!setNames(names(.), newcolnames))

But the setNames method just seems much more apt.

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