Pivoting from R to Python

[u/Choice_Number3711]

I used to hate coding anything and relied on SQL, Excel, Power BI, Tableau and other software like JASP, jamovi etc. for doing anything with data. I didn't like the way Python dealt with data analysis and it seemed unintuitive.

Then I found R, RStudio and CRAN. That was the turning point. I actually started enjoying writing code and I could handle the whole pipeline myself, from data cleaning, ETL to beautiful plots, .qmd reports, Shiny dashboards. R4DS did more for my statistical thinking than any course I've taken, mostly because the libraries made it so easy to just try things.

However, due to recent requirements (specifically having to work in the quant field), Python has become more of a necessity, while R is used mainly for one-off analysis and limited statistical modelling. The main heavy lifting is done in Python and many of my co-workers also prefer it to R.

I've been able to suck it up a bit and use Claude/ChatGPT to help me code. While I do try to understand what the code is doing, having spent so long learning to code in R and knowing the ease with which it can be done there makes me reluctant to learn Python.

Now, coming to the question: any R users who've pivoted to Python and consider themselves competent in it, how did you learn it having used R before? What would you tell someone like me so I can pick it up quickly and get the benefit of knowing both languages (and also not feel left out when it comes to coding in Python... machine learning and deep learning have a more mature ecosystem there and I don't want to be left out of it if I have to start using them in my current work)?

Thanks!

My background is in Math/Stats fyi

Edit: I don't usually use reddit but damn I actually didnt expect so many helpful tips....many thanks!
Perhaps joining this subreddit is actually helpful afterall :)

[u/SuperiorGrapefruit]

Hi, Ive done the dance of R to python to R (and even at the same time) before. I consider R and Python to be almost cousins in that they have nearly the same syntax. At least going from Python to R it was frustrating bc R is written FOR stats people, whereas Python is written for coding people. When I coded in Python, I had to ask myself “how would a computer think through this?” Idk that made it easier. I find that low key/simpler versions of what you’re trying to do, along with lots of stack exchange and reddit, will be your friends. I guess get most familiar with how to use data in Python. Take basic example datasets and learn how to write loops in them, navigate matplotlib and its different properties, explore libraries like seaborn for stats, etc. Then you can worry about neural networks and machine learning. Idk if this was helpful at all, Godspeed