Introducing Data Wrangling with Polars

[koushikkhan]

📝 Summary

This PR is introducing a course on data wrangling with Polars using marimo notebooks. It is linked to the following issue #18 .

📋 Checklist

• I have included package dependencies in the notebook file using --sandbox
• If adding a course, include a README.md
• Keep language direct and simple.

[Haleshot]

Just explored the .py file via the open-notebooks feature and it looks great!

Was going to mention to include polars in the inline dependencies (start of the notebook) as suggested in our README instructions but it isn't required as the library isn't imported actually in the file.

Thanks for kicking off the Polars series!

[koushikkhan]

@Haleshot Unfortunately I am not able to view my notebook via the open-notebooks. I am trying with the following URL: https://marimo.app/github.com/koushikkhan/learn/blob/feat/issue%2318/polars-data-wrangling/polars/01_why_polars.py.

Definitely I am missing something here.

[akshayka]

Thanks so much for the PR! This is a great start. The content is good, and makes me excited for the rest of the notebooks.

I have left some comments and suggestions. High level feedback:

• Let's aim to be concise, and avoid repeating ourselves often.
• Let's get to code examples sooner rather than later.
• Notebooks are meant to be presented in edit mode, so there is no need to duplicate the code in the markdown.
• Let's make sure the basics are explained explicitly, such as giving an example of a DataFrame early on.
• Let's tone the language down a little bit — the style should be educational and informative.

Again, great start and thanks so much!

[akshayka]

nit: for consistency throughout future notebooks, let's use lowercase keys: "gender", "height_cm".

[koushikkhan]

Alright, will continue with lower case letter while defining column names.

[koushikkhan]

Thanks so much for the PR! This is a great start. The content is good, and makes me excited for the rest of the notebooks.

I have left some comments and suggestions. High level feedback:

• Let's aim to be concise, and avoid repeating ourselves often.
• Let's get to code examples sooner rather than later.
• Notebooks are meant to be presented in edit mode, so there is no need to duplicate the code in the markdown.
• Let's make sure the basics are explained explicitly, such as giving an example of a DataFrame early on.
• Let's tone the language down a little bit — the style should be educational and informative.

Again, great start and thanks so much!

@akshayka I will work on the change requests.

[akshayka]

The suggestion was to split this markdown into two cells, and insert a block of Python in between that creates a DataFrame (for example, the gender, age, and height dataframe) which is reused in subsequent cells. Perhaps

    import polars as pl

    df_pl = pl.DataFrame(
        { 
            "gender": ["Male", "Female", "Male", "Female", "Male", "Female", 
                       "Male", "Female", "Male", "Female"],
            "age": [13, 15, 17, 19, 21, 23, 25, 27, 29, 31],
            "height_cm": [150.0, 170.0, 146.5, 142.0, 155.0, 165.0, 170.8, 130.0, 132.5, 162.0]
        }
    )
    df_pl

[akshayka]

@koushikkhan would you like any help finishing this PR?