You can optionally choose which columns to apply the transformation to:For a long time, people have asked an easy way to change the order of columns in data frame.

Sometimes, when working with a dataframe, you may want the values of a variable/column of interest in a specific way.

Here's an example using our dummy dataframe, Structurally, this is almost exactly the same as the syntax where we renamed only one variable. It is by design pipe-friendly and imports %>% from magrittr.

Thanks for this!

dplyr is the next iteration of plyr that is specialized for processing data frames with blazing high performance.. For example, FlightNum is changed to FlightNumber !Use rename_all() to change the names of dataframe columns without any logical condition.For example, consider that you would like to change column names, irrespective of it being  a numeric or not , and if they contain Num in the column name, you want to modify it to Number.Post this operation, you can see that FlightNumber got changed to FlightNumberber and TailNum changed to TailNumber.Along with dplyr rename() , you can also rename columns of a dataframe using a logical vector or an index.Let us now modify the column name “Month” of hflights to “month” using logical vector.Another approach to rename columns of a dataframe is by using the appropriate index on the names vector.Let us now modify the column name “Distance” to “distance”. plyr 2.0 if you will.It does less than plyr, but what it does it does more elegantly and much … When you rename a variable using the The issue with this way of doing it is that you need to supply names for There's also a way to rename columns one at a time using the In this post, I've shown you a few ways to rename variables.As it turns out, there are even more ways to rename a column in R. Many of those ways are "old fashioned" ways to rename columns.

dplyr verbs + magrittr pipes), chiefly for its advantageous of being very readable and intuitive. I have modified ArrTime to ArrivalTime, but tbl_times now contains ArrivalTime only ! Although it's true that you could perform the two operations separately without pipes, the piped version is cleaner. Where You can learn more about programming with tidy selection in Much like with renaming variables, there's often many ways to accomplish a given task. Data manipulation is typically performed in a sequential fashion, like a waterfall, and the pipe operator syntax reflects this. We will  now try to modify only those column names from the tbl, where the names end with the string “Time”.First, let us select those specific columns  and save it as tbl_times.Now , tbl_times contains four columns DepTime, ArrTime, ActualElapsedTime and  AirTime.Let’s try to modify DepTime column name to DepartureTime by using r dplyr rename column.Verify the column names after applying the dplyr rename() function.Remember that unless you save the changes back to a variable , the changes made to a dataframe using dplyr operations doesn’t come into effect.So, if you want the renamed column name to be applied to your tibble, you will need to save it back to a variable again.We can use dplyr select to rename a dataframe column  as well.But the main difference is that, dplyr select() keeps only the variable you specify; dplyr rename() keeps all variables of dataframe intact.What I mean is , if my dataframe has col1, col2, col3 and col4, and I am modifying col1 to column1 using select, then only column1 will be present in the resulting dataframe.If I use rename() , then column1, col2, col3, and col4 will be present in the resulting dataframe. 2 minute read R. One of the primary things that slows me down in R is data management. Put the two together and you have one of the most exciting things to happen to R in a long time. This is an example of using several tools in series to quickly perform data manipulation. a) The dplyr package was developed by Hadley Wickham of RStudio b) The dplyr package is an optimized and distilled version of his plyr package c) The dplyr package provides any “new” functionality to R d) The dplyr package does not provide any “new” functionality to R View Answer Using the rename function with pipes One of the advantages of working with the Tidyverse (the set of R packages including dplyr , ggplot2 , stringr , and tidyr ) is that you can perform data manipulation in a "waterfall" pattern by using the pipe operator, %>% . dplyr is Hadley Wickham’s re-imagined plyr package (with underlying C++ secret sauce co-written by Romain Francois). The rest of this post has been updated accordingly. I can rename this ‘assignee.login’ column before removing all the columns that start with ‘assignee’ together. Private self-hosted questions and answers for your enterpriseProgramming and related technical career opportunities@akrun Thanks very much, I will try to do something with Only problem is that some characters are not parsing well within the Please add some explanation to your answer. The only difference is that in this case we have two "pairs" of new/old names separated by a comma. Columns that aren’t mentioned in the rename() call are simply left untouched while using dplyr rename().See an example here below. In this post, we will learn about dplyr rename function.dplyr rename is used to modify dataframe column names or  tibble column names. They rely on using syntax from base R. Unfortunately, they are syntactically more complicated. We are selecting the columns whose names start with “Arr” inside the vars function and then, we are using the str_replace function from stringr R package to replace “Arr” with “Arrival” inside the funs function.The dot as the first argument inside the str_replace function is the placeholder to hold the columns returned by the vars function.So, that means ArrTime and ArrDelay columns will be changed to ArrivalTime and ArrivalDelay.Use rename_if() to change the names of dataframe columns according to a logical condition.Below is an example of choosing the columns whose data types are numeric(such as integer and double ) and implementing str_replace function to alter them.All the numerical columns , which contains the string “Num” , are modified post this operation. In this blog post, I’ll show you how to rename columns in R.This is pretty straightforward if you know how to do it properly, but there are also some little challenges in renaming variables. This makes them harder to learn, harder to use, harder to read, and harder to debug.I'll just say it once more: if you need to rename variables in R, just use the When you're learning data science, there are lots of tools and techniques that are a waste of time. We have updated the syntax for selecting with a function. dplyr verbs.