The Demise of Matlab in Data Science

The Demise of Matlab in Data Science

My personal interest in Data Science spans back to 2011. I was learning more about Economies and wanted to experiment with some of the ‘classic’ theories and whilst many of them held ground, at a micro level, many were also purely fictitious.

My personal interest in Data Science spans back to 2011. I was learning more about Economies and wanted to experiment with some of the ‘classic’ theories and whilst many of them held ground, at a micro level, many were also purely fictitious. Many of the themes that you learn: on how savings and Investment are directly related, or even on how Supply and Demand are directly related to price just didn’t hold true.

To be fully conclusive on my research though, I had to be sure that any conclusion I drew was purely unadulterated and spoke from the data. It’s all good and well that some notable academic from some notable University informs us about a theory, but is it actually true? Is it true everywhere?

Collecting data wasn’t too hard but from there I had to teach myself programming. Python was free, easy to use, and the ‘new thing’ that people said to learn to ‘future proof’ my knowledge. However, after learning it and persuading a company to let me join their Graduate Scheme, I began to use Matlab at work.

From here, I’ve always had this conflict where Matlab feels like a better language to work in but Python has always been my, you could say, ‘mother tongue’.

The following article will highlight why after almost 10 years of experience in both languages, I feel that Python absolutely dominates Matlab in Data Science and also, why new Data Scientists should focus on solely on Python.

Python and Matlab are similar and different at the same time. Matlab was created as a private enterprise and as a closed form platform solution with a high price tag. On the other side, Python was created with ‘openness’ in mind to be easy and simple to use for all general tasks.

Matlab got a head start in the popularity contest as it was released in 1984 and despite me not being around back then, the various permutations and iterations of the language lent themselves well to the discipline of Mathematics. This is because vectors and multi-dimensional matrices are super simple to use in Matlab — a feature which only came in later at the time of Numpy (which was still kind of annoying) but Pandas has made using Python infinitely easier. Given that change, does my thesis hold true?

Was Pandas the reason why Python began to overtake Matlab?

So we know that Pandas was first an internal library at AQR Capital and written my Wes McKinney and looking at Trends on Stack Overflow, we can see that from 2012 onwards, the percentage of questions with a Tag of Pandas began to increase where from 2015, there was a sharpe inflection point.

Image for post

Now notice here that since 2013/2014, the number of questions for Python as a langauge began to increase as well. Makes sense right? Pandas is a subset of Python, so naturally, the two are related, however …

Image for post

Insight derived from Stack Overflow Trends [source]

…since 2015, Matlab has been on a downward spiral. The proportion of questions which have a tag of Matlab has seriously been going down and why is that?

Image for post

data-science python programming machine-learning software-development

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Data Science With Python Training | Python Data Science Course | Intellipaat

🔵 Intellipaat Data Science with Python course: this Data Science With Python Training video, you...

ML Optimization pt.1 - Gradient Descent with Python

In this article, we explore gradient descent - the grandfather of all optimization techniques and it’s variations. We implement them from scratch with Python.

Hire Machine Learning Developers in India

We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.

Applied Data Analysis in Python Machine Learning and Data Science | Scikit-Learn

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.