milenkovicm commented on code in PR #1399:
URL:
https://github.com/apache/datafusion-ballista/pull/1399#discussion_r2718957618
##########
docs/source/user-guide/python.md:
##########
@@ -144,6 +144,105 @@ assert result.column(0) == pyarrow.array([5, 7, 9])
assert result.column(1) == pyarrow.array([-3, -3, -3])
```
+## Jupyter Notebook Support
+
+Ballista works well in Jupyter notebooks. DataFrames automatically render as
formatted HTML tables when displayed
+in a notebook cell.
+
+### Basic Usage
+
+```python
+from ballista import BallistaSessionContext
+
+# Connect to a Ballista cluster
+ctx = BallistaSessionContext("df://localhost:50050")
+
+# Register a table
+ctx.register_parquet("trips", "/path/to/nyctaxi.parquet")
+
+# Run a query - the result renders as an HTML table
+ctx.sql("SELECT * FROM trips LIMIT 10")
+```
+
+When a DataFrame is the last expression in a cell, Jupyter automatically calls
its `_repr_html_()` method,
+which renders a styled table with:
+
+- Formatted column headers
+- Expandable cells for long text content
+- Scrollable display for wide tables
+
+### Converting Results
+
+DataFrames can be converted to various formats for further analysis:
+
+```python
+df = ctx.sql("SELECT * FROM trips WHERE fare_amount > 50")
+
+# Convert to Pandas DataFrame
+pandas_df = df.to_pandas()
+
+# Convert to PyArrow Table
+arrow_table = df.to_arrow_table()
+
+# Convert to Polars DataFrame
+polars_df = df.to_polars()
+
+# Collect as PyArrow RecordBatches
+batches = df.collect()
+```
+
+### Example Notebook Workflow
+
+A typical notebook workflow might look like:
+
+```python
+# Cell 1: Setup
+from ballista import BallistaSessionContext
+from datafusion import col, lit
Review Comment:
Not used in this example
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