Emily Riederer Writes:

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

Installation: pyenv
IDE: VS Code

Analysis

Wrangling: polars
Visualization: seaborn

Communication

Tables: Great Tables
Notebooks: Quarto

Miscellaneous

Environment Management: pdm
Code Quality: ruff

Read Python Rgonomics

  • Isoprenoid@programming.dev
    ·
    edit-2
    6 months ago

    Two issues with this article:

    1. There is no easy option for selecting strictly necessary cookies.
    2. Rgonomics reminds me of Rogernomics, which has bad connotations (Wikipedia article)

    [Due to Rogernomics], over 15 years, New Zealand's economy and social capital faced serious problems: the proliferation of food banks increased dramatically to an estimated 365 in 1994; the number of New Zealanders estimated to be living in poverty grew by at least 35% between 1989 and 1992 while child poverty doubled from 14% in 1982 to 29% in 1994.

    Edit: Downvote if you love child poverty, I guess. ¯\_(ツ)_/¯