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1. Commits on Apr 24, 2025

   • Simplifies requirements.txt

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2. Commits on Oct 24, 2024

   • Modernizes typing

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   • Removes unrelated content

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   • Iterating/grouping exercise rewrite

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3. Commits on Feb 9, 2024

   • Adds typing clarification for decorator examples

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4. Commits on Oct 9, 2023

   • Makes more explicit which (pipeline) functions need a decorator

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   • Replaces example by exercise

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   • Adds requirements.txt for non-pipenv users

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5. Commits on Aug 6, 2023

   • Adds reference to OO design tutorial

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   • Unhides cell

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   • Adds more explicit test cases for exercise

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   • Minor reordering to prevent confusion

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   • Bumps dependencies

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6. Commits on Jun 7, 2022

   • Adds prompt to investigate label-based indexing

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   • Adds exercise to get used to class and method definitions

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7. Commits on May 23, 2022

   • Adds minor clarification about purpose of lambda expressions

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   • Upgrades to recent verions of python and used packages

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8. Commits on May 31, 2021

   • Adds (optional) plotly dependency for notebook 4

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   • Improves variable name by making it clear what is unpacked

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   • Prevents confusion by changing prefix in exercise to something other than **

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9. Commits on Oct 19, 2020

   • Lowers confusion by using conventional casing for classes

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   • Clarifies expectation of exercise

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   • Optimizes code layout for display in big font

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10. Commits on Oct 15, 2020

    • Typos + minor additions

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11. Commits on Oct 7, 2020

    • Minor edits

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    • Removes unused import

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    • Corrects column name

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    • Creates a single appendix, no need for separate notebook-package

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    • Adds explanation of Git sync

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12. Commits on Oct 6, 2020

    • Adds overview of Git

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13. Commits on Oct 3, 2020

    • Adds explaining text about pipelines and preventing joins using transform()

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    • Adds explaining text (+ exercise) to section about decluttering

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14. Commits on Oct 2, 2020

    • Adds explaining text to examples of separation of concerns

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    • Adds explaining text and code to functional programming module

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    • Details reflection about DataFrame method chaining

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