I have not split these languages into any particular type, like traditional and scripting, because I wanted to look at everything together. Some of the jobs data is difficult to include because of the amount of noise from other industries. Go and R have a lot of noise in particular and are not included in the graphs. However, they are included due to their origin (Google) and usage (Data Analysis) respectively. First, let’s look at the languages themselves ordered by Tiobe rank (Tiobe ranking and RWW & Dataist Tier included) :
Go (Tiobe: 21 , Tier: 4)
R (Tiobe: 26, Tier:3)
Lua (Tiobe: 27, Tier:3)
Scheme (Tiobe: 29, Tier:3)
ActionScript (Tiobe: 37, Tier:2)
Erlang (Tiobe: 49, Tier:3)
Groovy (Tiobe: 50-100, Tier: 3)
Scala (Tiobe: 50-100, Tier:2)
Clojure (Tiobe: 100+, Tier:3)
Interestingly enough, there does not seem to be a correlation between the Tiobe rank and the Dataist Tier. If anything, it almost looks like a reverse correlation, but I am going to ignore correlation for now. So, how does the ranking data compare to the job demand data?
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