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Real Python에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Real Python 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Build Captivating Display Tables in Python With Great Tables

1:10:59
 
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Manage episode 430841129 series 2637014
Real Python에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Real Python 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Do you need help making data tables in Python look interesting and attractive? How can you create beautiful display-ready tables as easily as charts and graphs in Python? This week on the show, we speak with Richard Iannone and Michael Chow from Posit about the Great Tables Python library.

Michael and Richard discuss the design philosophy and history behind creating display tables. We dig into the grammar of tables, the background of the project, and an ingenious way to build a collection of examples for a library.

We briefly cover how Richard and Michael started contributing to open source. We also discuss practicing data skills with challenges and resources like Tidy Tuesday.

This episode is sponsored by Mailtrap.

Course Spotlight: Graph Your Data With Python and ggplot

In this course, you’ll learn how to use ggplot in Python to build data visualizations with plotnine. You’ll discover what a grammar of graphics is and how it can help you create plots in a very concise and consistent way.

Topics:

  • 00:00:00 – Introduction
  • 00:02:00 – Michael’s background in open source
  • 00:04:07 – Rich’s background in open source
  • 00:05:27 – Advice for someone starting out
  • 00:08:55 – What do you mean by the term “display” table
  • 00:11:32 – What components were missing from other tables?
  • 00:13:31 – Using examples to explain features
  • 00:16:09 – Why was there an absence of this functionality in Python?
  • 00:19:35 – A progressive approach and the grammar of tables
  • 00:21:26 – Sponsor: Mailtrap
  • 00:22:01 – The design philosophy of great tables
  • 00:25:31 – Nanoplots, spark lines, and column spanners
  • 00:27:06 – Building a gallery of examples
  • 00:28:56 – Heat mapping cells and automatically adjusting text color
  • 00:32:54 – Output formats for the tables
  • 00:34:46 – Building in accessibility
  • 00:36:55 – Dependencies
  • 00:37:42 – What is the common workflow?
  • 00:41:39 – Video Course Spotlight
  • 00:43:15 – Adding graphics
  • 00:46:41 – Using a table contest to get examples
  • 00:49:47 – quartodoc and documenting the project
  • 00:55:00 – Tidy Tuesday and data science community
  • 01:00:29 – What are you excited about in the world of Python?
  • 01:03:46 – What do you want to learn next?
  • 01:08:05 – How can people follow the work you do online?
  • 01:09:57 – Thanks and goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

264 에피소드

Artwork
icon공유
 
Manage episode 430841129 series 2637014
Real Python에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Real Python 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Do you need help making data tables in Python look interesting and attractive? How can you create beautiful display-ready tables as easily as charts and graphs in Python? This week on the show, we speak with Richard Iannone and Michael Chow from Posit about the Great Tables Python library.

Michael and Richard discuss the design philosophy and history behind creating display tables. We dig into the grammar of tables, the background of the project, and an ingenious way to build a collection of examples for a library.

We briefly cover how Richard and Michael started contributing to open source. We also discuss practicing data skills with challenges and resources like Tidy Tuesday.

This episode is sponsored by Mailtrap.

Course Spotlight: Graph Your Data With Python and ggplot

In this course, you’ll learn how to use ggplot in Python to build data visualizations with plotnine. You’ll discover what a grammar of graphics is and how it can help you create plots in a very concise and consistent way.

Topics:

  • 00:00:00 – Introduction
  • 00:02:00 – Michael’s background in open source
  • 00:04:07 – Rich’s background in open source
  • 00:05:27 – Advice for someone starting out
  • 00:08:55 – What do you mean by the term “display” table
  • 00:11:32 – What components were missing from other tables?
  • 00:13:31 – Using examples to explain features
  • 00:16:09 – Why was there an absence of this functionality in Python?
  • 00:19:35 – A progressive approach and the grammar of tables
  • 00:21:26 – Sponsor: Mailtrap
  • 00:22:01 – The design philosophy of great tables
  • 00:25:31 – Nanoplots, spark lines, and column spanners
  • 00:27:06 – Building a gallery of examples
  • 00:28:56 – Heat mapping cells and automatically adjusting text color
  • 00:32:54 – Output formats for the tables
  • 00:34:46 – Building in accessibility
  • 00:36:55 – Dependencies
  • 00:37:42 – What is the common workflow?
  • 00:41:39 – Video Course Spotlight
  • 00:43:15 – Adding graphics
  • 00:46:41 – Using a table contest to get examples
  • 00:49:47 – quartodoc and documenting the project
  • 00:55:00 – Tidy Tuesday and data science community
  • 01:00:29 – What are you excited about in the world of Python?
  • 01:03:46 – What do you want to learn next?
  • 01:08:05 – How can people follow the work you do online?
  • 01:09:57 – Thanks and goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

264 에피소드

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