For other options to this approach see the programming with dplyr vignette. Where !!sym(cc) is a way to use the column name stored in cc and := is equivalent to = but allows us to use !!sym(cc) on the left-hand side. Mutate(!!sym(cc) := ifelse(any_large_codes, NA, !!sym(cc)))
![r rename column r rename column](https://vrzkj25a871bpq7t1ugcgmn9-wpengine.netdna-ssl.com/wp-content/uploads/2018/07/rename-columns-in-R_old-to-new_v2.png)
If you want to handle multiple columns, I would suggest something like this: all_columns_to_handle = c( Mutate(this_one_column = ifelse(any_large_codes, NA, this_one_column)) Both functions will rename the columns in a data frame, but the rename function can save the new data frame to a new object, while the names.
![r rename column r rename column](https://blog.rsquaredacademy.com/img/rename_1.png)
There is the names function, which is a base r function, and the rename function is from the dplyr package.
#R rename column code#
Step 2: The following code sets the values in a single column to NA where there are any large codes: df = df %>% When you need to rename multiple columns in r there are two different formulas you can use. You can use dplyr to add it into the dataframe if you wish, but this is not necessary: df = df %>% mutate(na_indicator = any_large_codes) I have not used dplyr for this as I am not aware of any row-wise operators in dplyr. Step 1: The following code produces an indicator for whether a row contains any codes greater than 8887: any_large_codes = apply(df, MARGIN = 1, function(row) checks if any value in its input (each row) is larger than 8887.
#R rename column how to#
I need to be able to apply the code across multiple columns, rather than just one. How to Rename a Column Name in R 3 Examples to Change Colnames of a Data Frame ( ) ( ) OldName the solution needs to be applicable to a dataframe of 250 columns.If the maximum value in the row is above 8887, then I would like it to return the row but with the value of all prices set to NA. I'm not able to recalculate all the values, so instead I would like to find some code, which takes in as an argument each row of the dataframe. These values have been incorrectly used to calculate other columns (such as the value of pricepergram) as they have not been signaled as NA prior to calculation.
![r rename column r rename column](https://i.stack.imgur.com/Yo0bx.png)
The issues come where there are values of 88 which constitute NA or refused to answer respectively. #> "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.I have a large data frame which has multiple columns calculated from other columns. Otherwise, like mentioned in a previous post, using the %>% pipe should work with setnames but you may have difficulties to continue the chain without %>% library(data.table) Iris_dt "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width" You can "pipe" it using the := operator using one of the multiple column syntax to create a new column with a new name then deleting the old one. Iris_dt Sepal.Length Sepal.Width Petal.Length Petal.Width Species is_setosa
Pipe operators are a way to chain operation without making an assignment. If the name of the column should be different from the expression used, you can rename it by using ASCan I asked why you want it chained "like a pipe" absolutely ?Īs data.table is working by reference, there is no assignment and it is like it is chained by default without any pipe-like operator.