A Python-R Dictionary for Data Science

Welcome

I personally consider R and Python to be two very powerful programming languages (and ecosystems) to make data science. Being mainly an R user for three years, I had to learn (quickly) Python and its modules for data science due to a change of career. Starting to learn a programming language from scratch and getting familiar with the APIs of lots of packages can be overwhelming. Hence, I started looking for similarities across the R and Python ecosystems and I’ve decided to create this book as a personal reference to be able to switch from one language to another seamlessly.

This book must not be intended as an in-depth guide into any of the concepts exposed. Instead, it should be considered as a dictionary aimed at translating many common data science problems from R to Python and viceversa. The current version of this dictionary covers the following macro-areas of data science:

• Data Collection
• Data Manipulation
• Data Visualization
• Machine Learning

Obviously, data science is a broader topic and you can find links to external useful resources throughout the book. I chose to translate the most common and useful commands with code snippets which needed to be both concise and as accurate as possible.

This project was created with the language-agnostic publishing system Quarto, which can be considered as a younger (yet very ambitious) brother of rmarkdown.

Hopefully, this resource may help someone else in their journey through data science with R and Python. Enjoy.