With the ever increasing numbers of programming languages, frameworks, databases and other technologies, there isn’t a way for you to know everything, or be anywhere close to that. So, if you are starting out in the industry, what do you learn?
If you’ve come from university (or a bootcamp), they already made that decision for you and did so hopefully based on some solid data, but how about if you are self taught? It can be pretty overwhelming and just because your friend Derek told you or you found a popular YouTube channel, you can’t be sure. Time is money as they say and it would be pretty frustrating to spend months on something that is trending out of favour or is considered old technology.
One option to you the learner, is to take a look at the TIOBE index which is “an indicator of the popularity of programming languages.” Produced by TIOBE (a software quality company, no less), they have been producing this rating since June of 2001 in a monthly format, although to see all of that, you will need to pay them some $$$.
What we can do though is take a look at this month’s to get a flavour of how things have been, at least retrospectively.
Let’s start by taking a look at the top 10 languages and compare them to a year ago.
The first four haven’t budged, being Java, C, C++, Python and C#. C surprised me a little because that is a pretty low-level language but that possibly might be connected to developers using it for embedded IOT devices. Java is and was at the top spot but you can see that it has dropped by almost 5% in popularity. Places 3-5 only just about account for a third of the total of the top 5, but no shocks to see C# there, certainly.
How about over time?
OK, what’s the take away from this? Well, if you were a chart analyst you would be giving serious consideration to both Java and C. If it were me, I’d go with Java if I were starting out. C, despite the numbers feels a bit niche, but I could be wrong.
If maths is your thing, then R over MATLAB would be my choice, mixed in with some Python since that is popular in data science circles.
Written by Stephen Moon
email: stephen at logicalmoon.com