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docs: fix formatting inconsistencies in DataFrame user guide
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docs/source/user-guide/dataframe.rst

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@@ -26,10 +26,10 @@ It offers a familiar API similar to pandas and other DataFrame libraries, but wi
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and Arrow.
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A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation.
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The actual execution happens when terminal operations like `collect()` or `show()` are called.
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The actual execution happens when terminal operations like ``collect()`` or ``show()`` are called.
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Basic Usage
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.. code-block:: python
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@@ -55,17 +55,17 @@ Basic Usage
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df.show()
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HTML Rendering
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When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will
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automatically display as formatted HTML tables, making it easier to visualize your data.
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The `_repr_html_` method is called automatically by Jupyter to render a DataFrame. This method
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The ``_repr_html_`` method is called automatically by Jupyter to render a DataFrame. This method
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controls how DataFrames appear in notebook environments, providing a richer visualization than
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plain text output.
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Customizing HTML Rendering
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You can customize how DataFrames are rendered in HTML by configuring the formatter:
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@@ -87,7 +87,7 @@ You can customize how DataFrames are rendered in HTML by configuring the formatt
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The formatter settings affect all DataFrames displayed after configuration.
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Custom Style Providers
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For advanced styling needs, you can create a custom style provider:
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configure_formatter(style_provider=MyStyleProvider())
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Creating a Custom Formatter
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For complete control over rendering, you can implement a custom formatter:
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custom_html = formatter.format_html(batches, schema)
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Managing Formatters
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Reset to default formatting:
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print(formatter.theme)
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Contextual Formatting
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You can also use a context manager to temporarily change formatting settings:
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