First impressions apply to languages too. A lot of mathematicians went into AI but didn't start out with any programming experience. They dabbled in some languages and gravitated toward the one(s) they found most useful.
Paraphrasing Guy Steele [1]:
> It's important that when you design a language that does a familiar thing, that you do the familiar thing exactly... it's criminal that you can write 1/2 and get values nowhere near one-half.
Python
>>> 1/2
0.5
Ruby
irb(main):001> 1/2
0
To a novice programmer, ruby's result makes no sense, and introduces an incredible degree of doubt into the mind of the user. Sure, they could explore why it gives that result, but if that's not helping them get toward solving the problem they're using the programming language for in the first place, then it could seem like an indulgent tangent.
Paraphrasing Guy Steele [1]:
> It's important that when you design a language that does a familiar thing, that you do the familiar thing exactly... it's criminal that you can write 1/2 and get values nowhere near one-half.
Python
>>> 1/2
0.5
Ruby
irb(main):001> 1/2
0
To a novice programmer, ruby's result makes no sense, and introduces an incredible degree of doubt into the mind of the user. Sure, they could explore why it gives that result, but if that's not helping them get toward solving the problem they're using the programming language for in the first place, then it could seem like an indulgent tangent.
[1] https://www.youtube.com/watch?v=agw-wlHGi0E&t=19m27s