- cross-posted to:
- python
- machine_learning
- cross-posted to:
- python
- machine_learning
cross-posted from: https://programming.dev/post/8257343
Switching languages is about switching mindsets - not just syntax. New developments in python data science toolings, like polars and seaborn’s object interface, can capture the ‘feel’ that converts from R/tidyverse love while opening the door to truly pythonic workflows
Just to be clear:
- This is not a post about why python is better than R so R users should switch all their work to python
- This is not a post about why R is better than python so R semantics and conventions should be forced into python
- This is not a post about why python users are better than R users so R users need coddling
- This is not a post about why R users are better than python users and have superior tastes for their toolkit
- This is not a post about why these python tools are the only good tools and others are bad tools
The Stack
WIth that preamble out of the way, below are a few recommendations for the most ergonomic tools for getting set up, conducting core data analysis, and communication results.
To preview these recommendations:
Set Up
Analysis
Communication
- Tables: Great Tables
- Notebooks: Quarto
Miscellaneous
Read Python Rgonomics
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