why do many say 'serious' work gets done in Python? R is great for linear models, but I find it tedious for many other things such as machine learning. However

why do many say 'serious' work gets done in Python? R is great for linear models, but I find it tedious for many other things such as machine learning. However, I wouldn't classify that as 'serious', just that I find one performs better for different tasks. its already been said, but I do NLP a lot. R handles text poorly. humans use a lot of text. tensorflow, neural networks, etc is better in Python between pandas, list comprehensions, python collections library, sklearn, spyder, I feel I have a lot of power at my finger tips and its easy to do most of the machine learning I want. importing a package takes a meaningful amount of time in R. Several seconds, that is just unacceptable. its a personal matter, but R has syntaxes that get on my nerves. python list: a = [1,2,3] a = c(1,2,3). perhaps its because i used other languages before, but my fingers are more adept at hitting [ which requires no shift compared to (. some people love curly braces and lots of parentheses in if/for statements, I appreciate them not being there. I have to fight with R on scientific notation, always copy - pasting into my code: options(scipen=999) that said, spyder is buggy, and R studio is fantastic. I still haven't come across a good python IDE that is par with R studio. edit: I forgot to say, I feel pyspark is far superior to sparkr. last i seen, sparkr only works with a VERY old version of spark. I dont even think that version is supported anymore. this is a bit of a big deal to me