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Update Polars README.md
Link to tracking issue for source of truth
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polars/README.md

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@@ -4,26 +4,9 @@ _🚧 This collection is a work in progress. Please help us add notebooks!_
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This collection of marimo notebooks is designed to teach you the basics of data wrangling using a Python library called Polars.
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**Planned notebooks.**
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Any notebook with the status "🚧" needs a contributor! Please file an issue if you plan to contribute.
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| Notebook | Description | Status |
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| ---------------------- | ---------------------------------------------------------------------------- | ------ |
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| Why Polars | An introduction to Polars and its advantages over other Dataframe libraries. ||
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| Series | Homogenous columns of data | 🚧 |
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| DataFrames | The central datastructure for structured data | 🚧 |
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| Loading data | Loading data from various different sources | 🚧 |
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| Basic operations | Basic operations on data | 🚧 |
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| Working with columns | Expression expansion and columns | 🚧 |
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| Data types | Basic types and casting | 🚧 |
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| Strings | Working with strings | 🚧 |
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| Missing data | Handling missing data | 🚧 |
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| Aggregations | Group bys and aggregations | 🚧 |
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| Window functions | Advanced expressions with windowing functions | 🚧 |
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| User-defined functions | Using custom Python operations | 🚧 |
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| NumPy functions | Applying NumPy functions to DataFrames | 🚧 |
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| Lazy execution | Lazily process queries with LazyFrames | 🚧 |
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**Help us build this course! ⚒️**
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We're seeking contributors to help us build these notebooks. Every contributor will be acknowledged as an author in this README and in their contributed notebooks. Head over to the [tracking issue](https://github.com/marimo-team/learn/issues/40) to sign up for a planned notebook or propose your own.
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**Running notebooks.** To run a notebook locally, use
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