Python or R? Hadley Wickham and Wes McKinney are Building Platform Independent Libraries!

Overview

• Ursa Labs is aiming to create libraries that will work on multiple programming languages, including R and Python
• It has been founded by pandas creator Wes McKinney. Hadley Wickham is the technical advisor

Introduction

The debate of R v Python was just getting started when Analytics Vidhya was founded 5 years back. R had the slightly upper hand at that time with it’s awesome community support and Hadley Wickham’s RStudio IDE. Over the years, Python has become the overwhelming leader. But the problem of collaborating between different tools has plagued data scientists since forever!

Ursa Labs, founded by pandas creator Wes McKinney, aims to end the debate once and for all. Hadley Wickham, the chief data scientist at RStudio and creator of some of the most popular R libraries (like ggplot2, the tidyverse suite, etc.), is the technical advisor on this project. Ursa Labs has one specific goal in mind – improve the state-of-the-art open source software for data cleaning, preparation, feature engineering, model building, and other tasks involved in a typical data science project.

But here’s the best part about Ursa Labs – their libraries will be platform independent. Rather than build libraries and packages for individual tools, they are in the process of developing these libraries that will work in multiple programming languages. They languages they are currently working on are shown in the below image:

It’s often been a nightmare for data scientists and organizations when it comes to collaborating on projects that use different tools. Code portability becomes a nuisance. There is the additional problem of code redundancy. Ursa Labs will eliminate these issues. And who knows? It might just end the thriving debate about which language is better for data scientists – Python or R.

Wow! This is one of the most ambitious projects taken up in the machine learning community and who better to do it than Wes and Hadley? This will make the process of sharing projects and collaborating on them so much easier for data scientists. No longer do you have worry about how to run a certain function in R if it was already performed in python, and vice versa.

How excited are you about this release? Use the comments section below to share your thoughts!

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Pranav Dar

Senior Editor at Analytics Vidhya.Data visualization practitioner who loves reading and delving deeper into the data science and machine learning arts. Always looking for new ways to improve processes using ML and AI.