No surprise I use python, but I’ve recently started experimenting with polars instead of pandas. I’ve enjoyed it so far, but Im not sure if the benefits for my team’s work will be enough to outweigh the cost of moving from our existing pandas/numpy code over to polars.
I’ve also started playing with grafana, as a quick dashboarding utility to make some basic visualizations on some live production databases.
I’m not a data scientist but I support a handful. They all use Python for the most part, but a few of them (still?) use R. Then there’s the small group that just throws everything into Excel 🤷🏻♂️
The dplyr pipeline and ggolot tooling is unmatched. Often I mix Python and r to use each for their most optimal
Interesting. Excel is certainly capable enough but I would think data set size limitations would be a frequent issue. Maybe not as frequent as I would have thought though.
Excel kinda chugs when you go over 20MB of data, but once the file is open it works. Sometimes you just need to be patient.
R and tidyverse is really amazing, the syntax is so natural I rarely need to check the docs on anything to quickly do basic data transformation/plotting. Definitely more intuitive than pandas (and I learnt that first).