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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`))

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