Choosing Python for Statistics and Econometrics
As I put the foundational efforts to become an economist, I explore the many tools available for statistical analysis — R, SPSS, Stata and Python.
Right then. I have been pondering this for many, many months. I got the idea for a MA Economics degree about 8 to 10 months ago. I started working towards it seriously in March this year, and as I am typing this, I have admission letters from two universities.
So far so good.
Economics is about math as much as it is about the concepts that need learning and applying.
Math primarily boils down to statistics. This follows analyzing large chunks of data, generating visualizations and writing reports.
Again, all good.
However, there seems to be no single tool that the many authors and guides recommend for an economics student.
Some folks swear by Stata, the very old GUI based tool that seems to be the favorite of academics, professors and such. Although Stata is expensive, it has a student edition with reasonable limitations. It seems to have good documentation, community, books and so on.
Then, there are those who only want to use SPSS. I remember using SPSS during my MBA days, all the way back in my MBA days, 2006 to 2008. The professor who taught us statistics was like a super genius guy with a massive ego and he is all in on SPSS. SPSS is super expensive though. I don’t recall there being much student discounts, but, if there is, I could not find it.
Of course, for the more programming-oriented academics, there is R. It’s been around for decades and economists swear by it. I almost started studying R and wanted to choose this.
Then, I started looking around the usual places I go to learn new stuff. Udemy Courses. edX. Reddit. Books that are popular on Amazon and discussion forums. Python kept popping up every where. Further, Python seems to have other applications as well.
I am already programmer of over 20 plus years. For me Python code would be dead easy, because of its similarity to JavaScript and C#. So, I don’t have spend too much effort learning. In fact, as I type this, I have ran through a couple of courses from Udemy and edX and I can read, type and understand Python like a duck taking to water.
So, I decided, Python will be my go-to statistical tool/programming language for the time being.
One small side note. I have a soft spot for Power BI. I imagine plenty of work related to my Economics journey will involve visualizations. I will try to investigate if I can include Power BI somewhere in this journey.
