The Tidyverse is more coherent and is generally bigger than what’s just in Pandas (R’s Tidyverse; I haven’t used the Python port).
If you already have a good grasp of Python, sure why not learn Pandas too? In my case, I’m reasonably ambidextrous in Python and R but find myself not reaching for Python unless there are colleague / deployment considerations that remove R as an option. The reason? R’s Tidyverse is pretty awesome, and reflects one of the better parts of the R language, namely the meta programming that is a holdover from Scheme’s influence on R.
Now, if you don’t already know Python and don’t have some other reason (such as specific deployment considerations or a team of Python collaborators) to learn? I don’t think so. Python is a fine language, just as R is a fine language. You’re already getting things done in R.
If you want a mental challenge, or to get in on the ground floor of something that might be the future, learn Julia, or F#, or (my favorite) Racket. Or heck, learn Spark, or a new modeling method.
If you already have a good grasp of Python, sure why not learn Pandas too? In my case, I’m reasonably ambidextrous in Python and R but find myself not reaching for Python unless there are colleague / deployment considerations that remove R as an option. The reason? R’s Tidyverse is pretty awesome, and reflects one of the better parts of the R language, namely the meta programming that is a holdover from Scheme’s influence on R.
Now, if you don’t already know Python and don’t have some other reason (such as specific deployment considerations or a team of Python collaborators) to learn? I don’t think so. Python is a fine language, just as R is a fine language. You’re already getting things done in R.
If you want a mental challenge, or to get in on the ground floor of something that might be the future, learn Julia, or F#, or (my favorite) Racket. Or heck, learn Spark, or a new modeling method.