What are the benefits of using a decoupled data processing system? How do you write reusable queries for a variety of backend data platforms? This week on the show, Phillip Cloud, the lead maintainer of Ibis, will discuss this portable Python dataframe library.

Phillip contrasts Ibis’s workflow with other Python dataframe libraries. We discuss how “getting close to the data” speeds things up and conserves memory.

He describes the different approaches Ibis provides for querying data and how to select a specific backend. We discuss ways to get started with the library and how to access example data sets to experiment with the platform.

Phillip discovered Ibis while looking for a tool that allowed him to reuse SQL queries written for a specific data platform on a different one. He recounts how he got involved with the Ibis project, sharing his background in open source and learning how to contribute to a first project.

This episode is sponsored by Mailtrap.

Course Spotlight: Creating Web Maps From Your Data With Python Folium

You’ll learn how to create web maps from data using Folium. The package combines Python’s data-wrangling strengths with the data-visualization power of the JavaScript library Leaflet. In this video course, you’ll create and style a choropleth world map showing the ecological footprint per country.

Topics:

00:00:00 – Introduction
00:02:18 – How did you get started with Ibis?
00:08:10 – First contribution to open source
00:13:46 – Comparing Ibis to other dataframe libraries
00:20:09 – Sponsor: Mailtrap
00:20:43 – What goes into the selection of backend?
00:27:07 – Database connections vs SQL compilers
00:30:03 – Raw SQL approach
00:34:06 – Dataframe approach
00:38:31 – What does “getting close to the data” mean?
00:41:52 – Video Course Spotlight
00:43:24 – Phillip in the cloud - YouTube channel
00:44:56 – Access to sample data sets
00:50:11 – Additional resources
00:52:50 – What are some of the backends Ibis supports?
00:54:13 – Entry points to the platform
00:55:00 – How are you supported?
00:57:10 – Exporting a SQL query
00:59:23 – What are you excited about in the world of Python?
01:04:28 – What do you want to learn next?
01:07:12 – How can people follow your work online?
01:08:00 – Thanks and goodbye

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