extra?

Author: kevinjqliu

mkdocs/docs/api.md

@@ -1564,52 +1564,6 @@ print(ray_dataset.take(2))
 ]
 ```
 
-### Bodo
-
-PyIceberg interfaces closely with Bodo Dataframes (see [Bodo Iceberg Quick Start](https://docs.bodo.ai/latest/quick_start/quickstart_local_iceberg/)),
-which provides a drop-in replacement for Pandas that applies query, compiler and HPC optimizations automatically.
-Bodo accelerates and scales Python code from single laptops to large clusters without code rewrites.
-
-<!-- prettier-ignore-start -->
-
-!!! note "Requirements"
-    This requires [`bodo` to be installed](index.md).
-
-```python
-pip install pyiceberg['bodo']
-```
-<!-- prettier-ignore-end -->
-
-A table can be read easily into a Bodo Dataframe to perform Pandas operations:
-
-```python
-df = table.to_bodo()  # equivalent to `bodo.pandas.read_iceberg_table(table)`
-df = df[df["trip_distance"] >= 10.0]
-df = df[["VendorID", "tpep_pickup_datetime", "tpep_dropoff_datetime"]]
-print(df)
-```
-
-This creates a lazy query, optimizes it, and runs it on all available cores (print triggers execution):
-
-```python
-        VendorID tpep_pickup_datetime tpep_dropoff_datetime
-0              2  2023-01-01 00:27:12   2023-01-01 00:49:56
-1              2  2023-01-01 00:09:29   2023-01-01 00:29:23
-2              1  2023-01-01 00:13:30   2023-01-01 00:44:00
-3              2  2023-01-01 00:41:41   2023-01-01 01:19:32
-4              2  2023-01-01 00:22:39   2023-01-01 01:30:45
-...          ...                  ...                   ...
-245478         2  2023-01-31 22:32:57   2023-01-31 23:01:48
-245479         2  2023-01-31 22:03:26   2023-01-31 22:46:13
-245480         2  2023-01-31 23:25:56   2023-02-01 00:05:42
-245481         2  2023-01-31 23:18:00   2023-01-31 23:46:00
-245482         2  2023-01-31 23:18:00   2023-01-31 23:41:00
-
-[245483 rows x 3 columns]
-```
-
-Bodo is optimized to take advantage of Iceberg features such as hidden partitioning and various statistics for efficient reads.
-
 ### Daft
 
 PyIceberg interfaces closely with Daft Dataframes (see also: [Daft integration with Iceberg](https://docs.daft.ai/en/stable/io/iceberg/)) which provides a full lazily optimized query engine interface on top of PyIceberg tables.