The biggest thing is probably it’s lack of good debugging tools. Their tracebacks are not very informative. Their handling of arrays is significantly inferior to NumPy. For example, R has a tendency to have separate functions for applying functions along different dimensions of an array whereas numpy almost universally has uses an argument to specify along what axis to apply a function.
Also doing much of anything non-statistics is a royal pain.
Why in python instead of R? R is used much more widely among people actually doing statistics, as far as I know.
I know, but R is really really terrible, and I hate working in it while Python is a joy to use and develop.
out of curiosity, what don’t you like about R?
The biggest thing is probably it’s lack of good debugging tools. Their tracebacks are not very informative. Their handling of arrays is significantly inferior to NumPy. For example, R has a tendency to have separate functions for applying functions along different dimensions of an array whereas numpy almost universally has uses an argument to specify along what axis to apply a function. Also doing much of anything non-statistics is a royal pain.