# pandas “transform” using the tidyverse

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**R – Stat Bandit**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Chris Moffit has a nice blog on how to use the `transform`

function in `pandas`

. He provides some (fake) data on sales and asks the question of what fraction of each order is from each SKU.

Being a R nut and a `tidyverse`

fan, I thought to compare and contrast the code for the `pandas`

version with an implementation using the tidyverse.

First the `pandas`

code:

import pandas as pd dat = pd.read_excel('sales_transactions.xlsx') dat['Percent_of_Order'] = dat['ext price']/dat.groupby('order')['ext price'].transform('sum')

A similar implementation using the tidyverse:

library(tidyverse) library(readxl) dat <- read_excel('sales_transactions.xlsx') dat <- dat %>% group_by(order) %>% mutate(Percent_of_Order = `ext price`/sum(`ext price`))

To

**leave a comment**for the author, please follow the link and comment on their blog:**R – Stat Bandit**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.