diff --git a/tests/fixtures/config/datasets.py b/tests/fixtures/config/datasets.py
index c6220d10..7f24eb84 100644
--- a/tests/fixtures/config/datasets.py
+++ b/tests/fixtures/config/datasets.py
@@ -87,6 +87,54 @@
     }
 )
 
+regrhouse_prices_datamodule_cfg_w_target = DictConfig(
+    {
+        "task": ["table-regression"],
+        "name": "house prices",
+        "description": "",
+        "markup_info": "",
+        "date_time": "01.07.2022",
+        "_target_": "innofw.core.datamodules.pandas_datamodules.RegressionPandasDataModule",
+        "train": {
+            "source": str(
+                get_test_folder_path()
+                / "data/tabular/regression/house_prices/train/train.csv"
+            )
+        },
+        "test": {
+            "source": str(
+                get_test_folder_path()
+                / "data/tabular/regression/house_prices/test/test.csv"
+            )
+        },
+        "target_col": "price",
+    }
+)
+
+clusthouse_prices_datamodule_cfg_w_target = DictConfig(
+    {
+        "task": ["table-clustering"],
+        "name": "house prices",
+        "description": "",
+        "markup_info": "",
+        "date_time": "01.07.2022",
+        "_target_": "innofw.core.datamodules.pandas_datamodules.ClusteringPandasDataModule",
+        "train": {
+            "source": str(
+                get_test_folder_path()
+                / "data/tabular/regression/house_prices/train/train.csv"
+            )
+        },
+        "test": {
+            "source": str(
+                get_test_folder_path()
+                / "data/tabular/regression/house_prices/test/test.csv"
+            )
+        },
+        "target_col": "price",
+    }
+)
+
 wheat_datamodule_cfg_w_target = DictConfig(
     {
         "task": ["image-detection"],
diff --git a/tests/unit/datamodules/pandas_datamodules/test_pandas_dm.py b/tests/unit/datamodules/pandas_datamodules/test_pandas_dm.py
index 1b95ea1e..275841a1 100644
--- a/tests/unit/datamodules/pandas_datamodules/test_pandas_dm.py
+++ b/tests/unit/datamodules/pandas_datamodules/test_pandas_dm.py
@@ -3,10 +3,12 @@
 from innofw.constants import Stages
 from innofw.core.datamodules import PandasDataModule
 from innofw.utils.framework import get_datamodule
-from tests.fixtures.config.datasets import house_prices_datamodule_cfg_w_target
+from tests.fixtures.config.datasets import house_prices_datamodule_cfg_w_target, \
+regrhouse_prices_datamodule_cfg_w_target,\
+clusthouse_prices_datamodule_cfg_w_target
 
 
-def test_save_preds(tmp_path):
+def test_classsave_preds(tmp_path):
     # create a house price dm
     fw = Frameworks.sklearn
     task = "table-regression"
@@ -17,6 +19,7 @@ def test_save_preds(tmp_path):
     stage = Stages.train
     # get target col values
     df = dm.get_stage_dataloader(stage)
+    df = dm.get_stage_dataloader(Stages.test)
     y = df["y"]
     # pass "preds", stage, path to the function
     dm.save_preds(y, stage, tmp_path)
@@ -28,3 +31,52 @@ def test_save_preds(tmp_path):
         "regression.csv",
         "clustering.csv",
     ]
+
+def test_regrsave_preds(tmp_path):
+    # create a house price dm
+    fw = Frameworks.sklearn
+    task = "table-regression"
+    dm: PandasDataModule = get_datamodule(
+        regrhouse_prices_datamodule_cfg_w_target, fw, task=task
+    )
+    # for stage train
+    stage = Stages.train
+    # get target col values
+    df = dm.get_stage_dataloader(stage)
+    df = dm.get_stage_dataloader(Stages.test)
+    y = df["y"]
+    # pass "preds", stage, path to the function
+    dm.save_preds(y, stage, tmp_path)
+    # check if a file has been created
+    files = list(tmp_path.iterdir())
+    assert len(files) == 1
+    assert files[0].name in [
+        "prediction.csv",
+        "regression.csv",
+        "clustering.csv",
+    ]
+
+
+def test_clustsave_preds(tmp_path):
+    # create a house price dm
+    fw = Frameworks.sklearn
+    task = "table-clustering"
+    dm: PandasDataModule = get_datamodule(
+        clusthouse_prices_datamodule_cfg_w_target, fw, task=task
+    )
+    # for stage train
+    stage = Stages.train
+    # get target col values
+    df = dm.get_stage_dataloader(stage)
+    df = dm.get_stage_dataloader(Stages.test)
+    y = df["y"]
+    # pass "preds", stage, path to the function
+    dm.save_preds(y, stage, tmp_path)
+    # check if a file has been created
+    files = list(tmp_path.iterdir())
+    assert len(files) == 1
+    assert files[0].name in [
+        "prediction.csv",
+        "regression.csv",
+        "clustering.csv",
+    ]
\ No newline at end of file