My neck is sore from nodding with all of these points that you made here. I'm very new to data science and am only doing it as a hobby right now, but I've been coding for 27 years and all of these points are universally applicable and will make anybody a better coder.
I think it would be awesome to have some guidelinse/ roadmaps how you would plan a data engineer/ analyst career. From getting your first job until the end of career. In my opinion it is real good to have a plan, also if you never have to stay strict at this.
Great video, good points. Agree with 3, i hate code that runs off far to the right. I work on laptop screen and usually split it, so try to code as pithy as possible on left side, so my code thin and long. Is that bad too? What's worse wide code or long code?
Personally I don't have a big problem with long code! Obviously redundant, repeating code isn't great (that's where writing functions comes in), but in and of itself scrolling down if you have to is a necessary issue.
One that you didn't mention... using vectorized calls instead of writing loops where ever possible to improve performance. Folks that are new to R and Python might not realise how great this concept is. It look me a little time to get my mind round it when I first encountered it with numpy. I think numpy nicked it from matlab. There's nothing new under the sun I suppose.
