diff --git a/daft/dataframe/__init__.py b/daft/dataframe/__init__.py
index b3287bc24c..e2f916d8a4 100644
--- a/daft/dataframe/__init__.py
+++ b/daft/dataframe/__init__.py
@@ -1,5 +1,5 @@
 from __future__ import annotations
 
-from .dataframe import DataFrame
+from .dataframe import DataFrame, GroupedDataFrame
 
-__all__ = ["DataFrame"]
+__all__ = ["DataFrame", "GroupedDataFrame"]
diff --git a/docs/source/api_docs/groupby.rst b/docs/source/api_docs/groupby.rst
index e1a25a150c..9b2804ae0f 100644
--- a/docs/source/api_docs/groupby.rst
+++ b/docs/source/api_docs/groupby.rst
@@ -5,14 +5,5 @@ When performing aggregations such as sum, mean and count, you may often want to
 
 Calling :meth:`df.groupby() <daft.DataFrame.groupby>` returns a ``GroupedDataFrame`` object which is a view of the original DataFrame but with additional context on which keys to group on. You can then call various aggregation methods to run the aggregation within each group, returning a new DataFrame.
 
-.. currentmodule:: daft
-
-.. autosummary::
-    :nosignatures:
-    :toctree: doc_gen/dataframe_methods
-
-    daft.dataframe.dataframe.GroupedDataFrame.sum
-    daft.dataframe.dataframe.GroupedDataFrame.mean
-    daft.dataframe.dataframe.GroupedDataFrame.min
-    daft.dataframe.dataframe.GroupedDataFrame.max
-    daft.dataframe.dataframe.GroupedDataFrame.agg
+.. autoclass:: daft.dataframe.GroupedDataFrame
+    :members: