cross-posted from: https://programming.dev/post/8257343

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

cross-posted from: https://discuss.online/post/4110869

Conda (@conda@fosstodon.org) writes:

Conda is moving our social media presence from Twitter/X to Mastodon and LinkedIn at the start of 2024. It's past time to move into spaces that are welcoming and more in line with our community values. Going forward, you can find us at 🐘 @conda@fosstodon.org (https://fosstodon.org/@conda) 🔗 Conda Community on LinkedIn

Read Conda is moving to Mastodon & LinkedIn | conda.org/blog

Conda (Software)

Conda provides package, dependency, and environment management for any language.

Using conda provides a streamlined approach to package management, platform compatibility, environment isolation, and access to an extensive package ecosystem. It is particularly beneficial for data scientists, researchers, and developers working with diverse software requirements across different projects.

Conda Community

The "conda" community is made up of millions of users, packaging maintainers and tool developers. Conda is not a single organization but rather a concerted effort of many different organizations, all devoted to the mission of providing easy access to various types of free software regardless of the operating system or programming language.

We firmly believe that everyone belongs in open-source, and we want to start by thanking you for taking the time to read this page. What follows is a high level summary of all the projects and organizations which make up the conda community with links provided where you can learn more or get involved yourself. The many meanings of "conda"

Traditionally associated with the Anaconda distribution, nowadays the term "conda" refers to more than just a package manager or a software repository. Its many definitions also encompass community packaging efforts like conda-forge and bioconda, as well as new tools developed in the Mamba and conda-incubator organizations. All these efforts show that the conda ecosystem is no longer defined by a single actor and continues to grow and thrive.

Organizations on GitHub include:

• @conda, plus Anaconda, Inc. efforts like @AnacondaRecipes, @anaconda-distribution, @ContinuumIO
• @conda-forge, @regro
• @conda-incubator & @conda-tools
• @mamba-org
• @bioconda

Some tools you might be familiar with are conda or conda-build themselves but also community efforts like mamba, boa, setup-miniconda, conda-lock or conda-tree, among many more.

Read more about the conda community.

2023-12-29 by Novica Nakov:

I notice that Ctrl+Enter for running the code in Python and in R is not the same thing.

Read the whole article

If you are looking for a free R Manual in german language, check out my Book. The PDF-Version has about 450pages.