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Build Captivating Display Tables in Python With Great Tables
Manage episode 430841129 series 2637014
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:
- Great Tables - Intro
- Examples – great_tables
- great-tables: Make awesome display tables using Python. - GitHub
- siuba: Python library for using dplyr like syntax with pandas and SQL
- The Design Philosophy of Great Tables – great_tables
- Richard Iannone - Using Great Tables to Make Presentable Tables in Python - YouTube
- Evaluation of the players of #LigaEndesa this week in Europe - Great Tables Example - X
- quartodoc: Generate API documentation with quarto
- Tidy Tuesday R Screencasts - YouTube
- Polars — DataFrames for the new era
- narwhals-dev/narwhals: Lightweight and extensible compatibility layer between dataframe libraries!
- A Grammar of Graphics for Python – plotnine 0.13.6
- Richard Iannone - GitHub
- Michael Chow - GitHub)
- Richard Iannone - LinkedIn
- Michael Chow - LinkedIn
Level up your Python skills with our expert-led courses:
233集单集
Manage episode 430841129 series 2637014
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:
- Great Tables - Intro
- Examples – great_tables
- great-tables: Make awesome display tables using Python. - GitHub
- siuba: Python library for using dplyr like syntax with pandas and SQL
- The Design Philosophy of Great Tables – great_tables
- Richard Iannone - Using Great Tables to Make Presentable Tables in Python - YouTube
- Evaluation of the players of #LigaEndesa this week in Europe - Great Tables Example - X
- quartodoc: Generate API documentation with quarto
- Tidy Tuesday R Screencasts - YouTube
- Polars — DataFrames for the new era
- narwhals-dev/narwhals: Lightweight and extensible compatibility layer between dataframe libraries!
- A Grammar of Graphics for Python – plotnine 0.13.6
- Richard Iannone - GitHub
- Michael Chow - GitHub)
- Richard Iannone - LinkedIn
- Michael Chow - LinkedIn
Level up your Python skills with our expert-led courses:
233集单集
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