Add Episode 68 - pandas & polars by @MarcoGorelli (#151)

_posts/2023-09-19-067-effect.md

@@ -25,7 +25,7 @@ podcast_duration: "53:05"
 podcast_length: 21010321
 ---
 
-<iframe src="https://open.spotify.com/embed-podcast/show/4jV6Yoz7D38sZJlYMzJm3k" width="100%" height="232" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>
+<iframe style="border-radius:12px" src="https://open.spotify.com/embed/episode/0z7foJZlCUwMJa9Tt7Qs9l?utm_source=generator" width="100%" height="352" frameBorder="0" allowfullscreen="" allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture" loading="lazy"></iframe>
 
 It's time to talk again about Functional Programming (or maybe not?!) with today's episode! I'm glad to have on stage [**Michael Arnaldi**](https://twitter.com/MichaelArnaldi), author and maintainer of [**Effect**](https://github.com/Effect-TS/effect).
 

_posts/2023-10-10-068-pandas-and-polars.md

@@ -0,0 +1,86 @@
+---
+title: "#68 - Pandas and Polars with Marco Gorelli"
+excerpt: "Data science and dataframes with pandas, polars and Marco Gorelli"
+author_profile: true
+
+description: "Data science and dataframes with pandas, polars and Marco Gorelli"
+
+header:
+  teaser: "/assets/images/header-single-episode.png"
+  overlay_image: "/assets/images/header-single-episode.png"
+  show_overlay_excerpt: false
+  overlay_filter: "0.6"
+  og_image: "/assets/images/episodes/68-cover.png"
+
+date: 2023-10-10
+permalink: /68/
+redirect_from:
+- /68/pandas-and-polars/
+- /68/pandas-and-polars-with-marco-gorelli/
+
+podcast_image: "/assets/images/episodes/68-cover.png"
+podcast_episode_number: 68
+podcast_link: https://dts.podtrac.com/redirect.m4a/hosting.thebakery.dev/68-thedevelopersbakery-pandas-and-polars.m4a
+podcast_duration: "54:40"
+podcast_length: 21633967
+---
+
+<iframe src="https://open.spotify.com/embed-podcast/show/4jV6Yoz7D38sZJlYMzJm3k" width="100%" height="232" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>
+
+Time for a brand-new topic today here at The Developers' Bakery: **Data Science**! We're really excited to have on stage [Marco Gorelli](https://github.com/MarcoGorelli), core contributor of both [pandas](https://pandas.pydata.org/) and [polars](https://pola.rs/), two of the most popular data science libraries in the Python ecosystem.
+
+In this episode, we'll talk about how pandas became so popular in the data science space. Then we'll move on to talk about polars, a new data science library written in Rust, and how its performances compare to pandas. 
+
+Finally, we'll have the opportunity to touch on a very interesting and unique topic: the **Dataframe Consortium**, a multi-company effort to standardize the data science API across the ecosystem.
+
+Enjoy the show 👨‍🍳
+
+# Show Notes
+
+- **00.14** Intro
+- **01.00** Episode Start
+- **01.30** Marco's Introduction
+- **02.14** What is pandas?
+- **03.27** Why do I need pandas?
+- **05.19** pandas' competitors
+- **07.24** pandas' popularity
+- **10.12** What's your role with pandas?
+- **12.39** How to become a pandas maintainer?
+- **13.50** From data scientist to open source maintainer
+- **16.02** What is polars?
+- **21.22** Can pandas and polars co-exist?
+- **24.25** Performance benchmarks
+- **26.21** The learning curve
+- **29.11** Naming anecdotes
+- **30.51** The Dataframe Consortium?
+- **40.12** Marco's role in the consortium
+- **43.40** What's next for polars?
+- **46.50** How to start contributing?
+- **50.56** Further reading
+- **53.33** Where people can find you online?
+
+# Resources
+
+* <i class="fab fa-github"></i> [pandas-dev/pandas on GitHub](https://github.com/pandas-dev/pandas)
+* <i class="fab fa-github"></i> [pola-rs/polars on GitHub](https://github.com/pola-rs/polars)
+* <i class="fas fa-link"></i> [Pandas Official Website](https://pandas.pydata.org/)
+* <i class="fas fa-link"></i> [Polars Official Website](https://pola.rs/)
+* <i class="fas fa-link"></i> [Dataframe API Consortium Official Website](https://data-apis.org/)
+* Mentioned Resources:
+    * <i class="fas fa-link"></i> [Pandas User Guide](https://pandas.pydata.org/docs/user_guide/index.html)
+    * <i class="fas fa-link"></i> [Polars User Guide](https://pola-rs.github.io/polars/user-guide/)
+    * <i class="fas fa-link"></i> [Dataframe API Standard definition](https://data-apis.org/dataframe-api/draft/)
+    * <i class="fab fa-youtube"></i> What polars does for you - [Video from EuroPython](https://youtu.be/UwRlFtSd_-8)
+    * <i class="fas fa-link"></i> [H2O Benchmark](https://duckdblabs.github.io/db-benchmark/)
+    * <i class="fas fa-link"></i> [Polars - TPCH Benchmark](https://www.pola.rs/benchmarks.html)
+* <i class="fab fa-github"></i> [@MarcoGorelli on GitHub](https://github.com/MarcoGorelli)
+* <i class="fab fa-linkedin"></i> [Marco Gorelli on LinkedIn](https://www.linkedin.com/in/marcogorelli/)
+
+# Show links
+
+* <i class="fas fa-link"></i> [Podcast Website](https://thebakery.dev)
+* <i class="fab fa-spotify"></i> [The Developers' Bakery on Spotify](https://open.spotify.com/show/4jV6Yoz7D38sZJlYMzJm3k?si=AL3ske_0R_CKlEScMhYhug)
+* <i class="fas fa-podcast"></i> [The Developers' Bakery on Apple Podcasts](https://podcasts.apple.com/us/podcast/the-developers-bakery/id1542849034)
+* <i class="fab fa-google-play"></i> [The Developers' Bakery on Google Podcasts](https://podcasts.google.com/feed/aHR0cHM6Ly90aGViYWtlcnkuZGV2L3BvZGNhc3QueG1s)
+* <i class="fab fa-twitter"></i> [@thebakerydev on Twitter](https://twitter.com/thebakerydev)
+* <i class="fab fa-twitter"></i> [@cortinico on Twitter](https://twitter.com/cortinico)