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.
IPython notebooks have become a defacto standard for presenting Python-based analyses and talks, as evidenced by recent Pycon and PyData events. As anyone who has used them knows, they are great for “reproducible research”, presentations, and sharing via the nbviewer. There are extensions connecting IPython to R, Octave, Matlab, Mathematica, SQL, among others.
However, the brilliance of the design of IPython is in the modularity of the underlying engine (3 cheers to Fernando Perez and his team).