diff --git a/src/dagster_pyiceberg/io_manager/arrow.py b/src/dagster_pyiceberg/io_manager/arrow.py
index 881bba4..539d225 100644
--- a/src/dagster_pyiceberg/io_manager/arrow.py
+++ b/src/dagster_pyiceberg/io_manager/arrow.py
@@ -57,25 +57,29 @@ class IcebergPyarrowIOManager(_io_manager.IcebergIOManager):
             import pandas as pd
             import pyarrow as pa
             from dagster import Definitions, asset
-            from dagster_pyiceberg import IcebergPyarrowIOManager, IcebergSqlCatalogConfig
+
+            from dagster_pyiceberg.config import IcebergCatalogConfig
+            from dagster_pyiceberg.io_manager.arrow import IcebergPyarrowIOManager
 
             CATALOG_URI = "sqlite:////home/vscode/workspace/.tmp/examples/select_columns/catalog.db"
             CATALOG_WAREHOUSE = (
                 "file:///home/vscode/workspace/.tmp/examples/select_columns/warehouse"
             )
 
+
             resources = {
                 "io_manager": IcebergPyarrowIOManager(
                     name="test",
-                    config=IcebergSqlCatalogConfig(
+                    config=IcebergCatalogConfig(
                         properties={"uri": CATALOG_URI, "warehouse": CATALOG_WAREHOUSE}
                     ),
                     schema="dagster",
                 )
             }
 
+
             @asset
-            def iris_dataset() -> pd.DataFrame:
+            def iris_dataset() -> pa.Table:
                 pa.Table.from_pandas(
                     pd.read_csv(
                         "https://docs.dagster.io/assets/iris.csv",
@@ -89,6 +93,7 @@ def iris_dataset() -> pd.DataFrame:
                     )
                 )
 
+
             defs = Definitions(assets=[iris_dataset], resources=resources)
 
     If you do not provide a schema, Dagster will determine a schema based on the assets and ops using
diff --git a/src/dagster_pyiceberg/io_manager/daft.py b/src/dagster_pyiceberg/io_manager/daft.py
index eb95268..4a1bc4d 100644
--- a/src/dagster_pyiceberg/io_manager/daft.py
+++ b/src/dagster_pyiceberg/io_manager/daft.py
@@ -53,29 +53,33 @@ class IcebergDaftIOManager(_io_manager.IcebergIOManager):
     Examples:
         .. code-block:: python
 
+            import daft as da
             import pandas as pd
-            import pyarrow as pa
             from dagster import Definitions, asset
-            from dagster_pyiceberg import IcebergPyarrowIOManager, IcebergSqlCatalogConfig
+
+            from dagster_pyiceberg.config import IcebergCatalogConfig
+            from dagster_pyiceberg.io_manager.daft import IcebergDaftIOManager
 
             CATALOG_URI = "sqlite:////home/vscode/workspace/.tmp/examples/select_columns/catalog.db"
             CATALOG_WAREHOUSE = (
                 "file:///home/vscode/workspace/.tmp/examples/select_columns/warehouse"
             )
 
+
             resources = {
-                "io_manager": IcebergPyarrowIOManager(
+                "io_manager": IcebergDaftIOManager(
                     name="test",
-                    config=IcebergSqlCatalogConfig(
+                    config=IcebergCatalogConfig(
                         properties={"uri": CATALOG_URI, "warehouse": CATALOG_WAREHOUSE}
                     ),
                     schema="dagster",
                 )
             }
 
+
             @asset
-            def iris_dataset() -> pd.DataFrame:
-                pa.Table.from_pandas(
+            def iris_dataset() -> da.DataFrame:
+                return da.from_pandas(
                     pd.read_csv(
                         "https://docs.dagster.io/assets/iris.csv",
                         names=[
@@ -88,6 +92,7 @@ def iris_dataset() -> pd.DataFrame:
                     )
                 )
 
+
             defs = Definitions(assets=[iris_dataset], resources=resources)
 
     If you do not provide a schema, Dagster will determine a schema based on the assets and ops using
diff --git a/src/dagster_pyiceberg/io_manager/polars.py b/src/dagster_pyiceberg/io_manager/polars.py
index 51b89f1..018699c 100644
--- a/src/dagster_pyiceberg/io_manager/polars.py
+++ b/src/dagster_pyiceberg/io_manager/polars.py
@@ -63,28 +63,32 @@ class IcebergPolarsIOManager(_io_manager.IcebergIOManager):
         .. code-block:: python
 
             import pandas as pd
-            import pyarrow as pa
+            import polars as pl
             from dagster import Definitions, asset
-            from dagster_pyiceberg import IcebergPyarrowIOManager, IcebergSqlCatalogConfig
+
+            from dagster_pyiceberg.config import IcebergCatalogConfig
+            from dagster_pyiceberg.io_manager.polars import IcebergPolarsIOManager
 
             CATALOG_URI = "sqlite:////home/vscode/workspace/.tmp/examples/select_columns/catalog.db"
             CATALOG_WAREHOUSE = (
                 "file:///home/vscode/workspace/.tmp/examples/select_columns/warehouse"
             )
 
+
             resources = {
-                "io_manager": IcebergPyarrowIOManager(
+                "io_manager": IcebergPolarsIOManager(
                     name="test",
-                    config=IcebergSqlCatalogConfig(
+                    config=IcebergCatalogConfig(
                         properties={"uri": CATALOG_URI, "warehouse": CATALOG_WAREHOUSE}
                     ),
                     schema="dagster",
                 )
             }
 
+
             @asset
-            def iris_dataset() -> pd.DataFrame:
-                pa.Table.from_pandas(
+            def iris_dataset() -> pl.DataFrame:
+                return pl.from_pandas(
                     pd.read_csv(
                         "https://docs.dagster.io/assets/iris.csv",
                         names=[
@@ -97,6 +101,7 @@ def iris_dataset() -> pd.DataFrame:
                     )
                 )
 
+
             defs = Definitions(assets=[iris_dataset], resources=resources)
 
     If you do not provide a schema, Dagster will determine a schema based on the assets and ops using