Dealing with Spaces and "Weird" Characters in Column Names with Dplyr::Rename()

Dealing with spaces and weird characters in column names with dplyr::rename()

To refer to variables that contain non-standard characters or start with a number, wrap the name in back ticks, e.g., `Instruction..Mode!`

How to deal with nonstandard column names (white space, punctuation, starts with numbers)

You may select the variable by using backticks `.

select(df, `a a`)
#   a a
# 1   1
# 2   2
# 3   3

However, if your main objective is to rename the column, you may use rename in plyr package, in which you can use both "" and ``.

rename(df, replace = c("a a" = "a"))
rename(df, replace = c(`a a` = "a"))

Or in base R:

names(df)[names(df) == "a a"] <- "a"

For a more thorough description on the use of various quotes, see ?Quotes. The 'Names and Identifiers' section is especially relevant here:

other [syntactically invalid] names can be used provided they are quoted. The preferred quote is the backtick".

See also ?make.names about valid names.

See also this post about renaming in dplyr

How to fix spaces in column names of a data.frame (remove spaces, inject dots)?

UDPDATE 2022 Aug:

df %>% rename_with(make.names)

OLD code was: (still works though)
as of Jan 2021: drplyr solution that is brief and uses no extra libraries is

df %<>% dplyr::rename_all(make.names)

credit goes to commenter.

Select columns with spaced heading in R

We can use backquotes to select those unusual names i.e. column names that doesn't start with letters

subset(df, select = c(height, `80% height`))

-output

#   height 80% height
#1   1020      816.0
#2   2053     1642.4
#3   1840     1472.0
#4   3301     2640.8
#5   2094     1675.2

Also, the dplyr use with specifying df twice is not needed. We can have select function from dplyr

library(dplyr)
df %>%
     select(height, `80% height`)

-output

#   height 80% height
#1   1020      816.0
#2   2053     1642.4
#3   1840     1472.0
#4   3301     2640.8
#5   2094     1675.2

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It may be also better to remove spaces and append a letter for those column names that start with numbers. clean_names from janitor does

library(janitor)
df %>%
    clean_names()

compute sum for space string column

Does this work?

df %>% group_by(`a 1`) %>% summarise(tx = sum(`t t`))

renaming columns in R with `-` symbol

This can be done using rename. You just have to put the column names with special charcters inside the "`" sign:

temp <- temp %>% dplyr::rename(`Re-ply` = re_ply,
                                total_id = total_ID,
                                `Re-ask` = re_ask)
names(temp)
[1] "Re-ply"   "total_id" "Re-ask" 

R: Import CSV with column names that contain spaces

Unless you specify check.names=FALSE, R will convert column names that are not valid variable names (e.g. contain spaces or special characters or start with numbers) into valid variable names, e.g. by replacing spaces with dots. Try names(s_data). If you do use check.names=TRUE, then use single back-quotes (`) to surround the names.

I would also recommend using rename from the reshape package (or, these days, dplyr::rename).

s_data <- read.csv2( file=f_name )
library(reshape)
s_df <- rename(s_data,ID="scada_id",
               PlantNo="plant",DateTime="date",Main.status="main_code",
               Additional.status="seco_code",MainStatustext="main_text",
               AddStatustext="seco_test",Duration="duration")

For what it's worth, the tidyverse tools (i.e. readr::read_csv) have the opposite default; they don't transform the column names to make them legal R symbols unless you explicitly request it.

Rename special character / symbols from all variables in the dataset

if you are here and want to check the solution to this questions, I have two options.

First, using dplyr:

ds <- ds %>% setNames(tolower(gsub("\\.","",names(.)))) %>% 
   setNames(tolower(gsub("\\_","",names(.)))) %>% 
   setNames(tolower(gsub("ç","c",names(.)))) %>% 
   setNames(tolower(gsub("ã","a",names(.))))

Second, using the janitor package

library(janitor)
ds <- ds %>% clean_names()

This community is a great place to find answers to our questions and I hope my answer could help you.

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