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
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?
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.
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 …
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?
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