Packaging Data Analyses & Using pandas GroupBy | Real Python Podcast
What are the best practices for organizing data analysis projects in Python? What are the advantages of a more package-centric approach to data science? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.
👉 Links from the show: https://realpython.com/podcasts/rpp/217/
We discuss Joshua Cook's recent article "How I Use Python to Organize My Data Analyses." The article covers how his process for building data analysis projects has evolved and now incorporates modern Python packaging techniques.
Christopher shares his recent video course on grouping real-world data with pandas. The course offers a quick refresher before digging into how to use pandas GroupBy to manipulate, transform, and summarize data.
We also share several other articles and projects from the Python community, including a news roundup, working with JSON data in Python, running an Asyncio event loop in a separate thread, knowing the why behind a system's code, a retro game engine for Python, and a project for vendorizing packages from PyPI.
This episode is sponsored by Mailtrap.
Topics:
00:00:00 -- Introduction
00:02:18 -- Setuptools Breaks Things, Then Fixes Them
00:04:57 -- PEP 751: A File Format to List Python Dependencies
00:07:04 -- Python 3.13.0 Release Candidate 1 Released
00:07:15 -- Python Insider: Python 3.12.5 released
00:07:22 -- Django 5.1 released - Django Weblog
00:07:27 -- Django security releases issued: 5.0.8 and 4.2.15
00:07:49 -- How I Use Python to Organize My Data Analyses
00:13:45 -- Sponsor: Mailtrap
00:14:21 -- pandas GroupBy: Grouping Real World Data in Python
00:20:33 -- Working With JSON Data in Python
00:25:01 -- Asyncio Event Loop in Separate Thread
00:30:33 -- Video Course Spotlight
00:31:47 -- Habits of great software engineers
00:49:17 -- pyxel: A Retro Game Engine for Python
00:52:36 -- python-vendorize: Vendorize Packages From PyPI
00:54:18 -- Thanks and goodbye
👉 Links from the show: https://realpython.com/podcasts/rpp/217/
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