DSLC Python for Data Analysis Book Club

Welcome to the DSLC Python for Data Analysis Book Club!

We are working together to read Python for Data Analysis by Wes McKinney (O'Reilly Media, Inc., copyright 2022, 9781098104030). Join the #book_club-py4da channel on the DSLC Slack to participate. As we read, we are producing notes about the book.

Meeting Schedule

If you would like to present, please see the sign-up sheet for your cohort (linked below, and pinned in the #book_club-py4da channel on Slack)!

• Cohort 1 (started 2022-08-05, finished 2022-11-11): meeting videos

---

How to Present

This repository is made with Quarto.

To present, follow these instructions:

Do these steps once:

• Setup Github Locally (also see Happy Git and GitHub for the useR)
• Fork and clone this repository to your local computer.
• Install Quarto and follow the Get Started chapter.

Do these steps each time you present another chapter:

• Open your project for this book.
• Create a new file in the folder. For example, to create a new file called 01_exercises.qmd, navigate to the folder then run touch 01_exercises.qmd in the Terminal.
• Write in what you would like in the file.
• Then, in the _quarto.yml file, under chapters, add a section with your chapter. The file listed after part is the first page of chapter; the ones under chapters will be subpages.

  - part: 01_main.qmd
      chapters: 
      - 01_notes.qmd
      - 01_video.qmd
      - 01_exercises.qmd

• Once you have added and edited your files, don’t forget to render the book. Run this in the terminal:

quarto render --to html

Once you are ready to finalize your changes:

• Commit your changes.
• Push your changes to your forked repo and then create a pull request for the DSLC admins to merge your changes.
• (If they request changes, make them)
• When your PR has been accepted ("merged"), close out your branch and prepare your local repository for future work.

On Using Quarto

Quarto is an open-source scientific and technical publishing system built on Pandoc.

You can weave together narrative text and code to produce elegantly formatted output. Quarto documents are fully reproducible. You can use plain .md files, Quarto .qmd, or Jupyter .ipynb files. Check out the files under Examples to see the various options.