Added Pandas Feature Split To Pt and Pandas Replace Advanced nodes.

tests/pandas_wrapper/pandas_feture_split_to_pt_test.py

@@ -0,0 +1,50 @@
+import os
+import sys
+import unittest
+import numpy as np
+import pandas as pd
+import torch
+
+PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
+sys.path.append(MODULE_ROOT)
+
+from pandas_wrapper.pandas_feature_split_to_pt import PandasFeatureSplitToPt
+
+class TestPandasFeatureSplitToPt(unittest.TestCase):
+    def setUp(self):
+        """Set up test data."""
+        self.node = PandasFeatureSplitToPt()
+
+        # Sample DataFrame
+        self.df = pd.DataFrame({
+            'A': [1, 2, 3],
+            'B': [4, 5, 6],
+            'C': [7, 8, 9]
+        })
+
+    def test_feature_split(self):
+        """Test splitting with different label positions."""
+        test_cases = [
+            (0, True, [[4, 7], [5, 8], [6, 9]], [1, 2, 3]),
+            (1, True, [[1, 7], [2, 8], [3, 9]], [4, 5, 6]),
+            (2, True, [[1, 4], [2, 5], [3, 6]], [7, 8, 9]),
+            (-1, True, [[1, 4], [2, 5], [3, 6]], [7, 8, 9]),
+        ]
+        
+        data_types = ["float32", "float16", "bfloat16", "float64", "int8", "uint8", "int16", "int32", "int64"]
+        for feature_dtype in data_types:
+            for label_dtype in data_types:
+                for label_pos, output_1d, expected_features, expected_labels in test_cases:
+                    with self.subTest(label_pos=label_pos, output_1d=output_1d, feature_dtype=feature_dtype, label_dtype=label_dtype):
+                        features, labels = self.node.f(self.df, label_pos, output_1d, feature_dtype, label_dtype)
+                        torch.testing.assert_close(features, torch.tensor(expected_features, dtype=getattr(torch, feature_dtype)))
+                        torch.testing.assert_close(labels, torch.tensor(expected_labels, dtype=getattr(torch, label_dtype)))
+
+    def test_invalid_label_position(self):
+        """Test invalid label positions."""
+        with self.assertRaises(ValueError):
+            self.node.f(self.df, 3, True, "float32", "int64")
+
+if __name__ == "__main__":
+    unittest.main()

tests/pandas_wrapper/pandas_replace_advanced_test.py

@@ -0,0 +1,60 @@
+import os
+import sys
+import unittest
+import pandas as pd
+import ast
+from typing import Any, Dict
+
+PROJECT_ROOT = os.path.realpath(os.path.join(os.path.dirname(__file__), "..", ".."))
+MODULE_ROOT = os.path.join(PROJECT_ROOT, "modules")
+sys.path.append(MODULE_ROOT)
+
+from pandas_wrapper.pandas_replace_advanced import PandasReplaceAdvanced
+
+
+class TestPandasReplaceAdvanced(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.node = PandasReplaceAdvanced()
+        cls.df = pd.DataFrame(
+            {
+                "col1": ["cat", "dog", "fish"],
+                "col2": ["mountain", "ocean", "forest"],
+            }
+        )
+
+    def test_valid_replacement(self):
+        test_cases = [
+            ('{"cat": 1, "dog": 2.34}', {"col1": [1, 2.34, "fish"], "col2": ["mountain", "ocean", "forest"]}),
+            ('{"mountain": "hill", "forest": "jungle"}', {"col1": ["cat", "dog", "fish"], "col2": ["hill", "ocean", "jungle"]}),
+        ]
+        for replacements, expected_data in test_cases:
+            with self.subTest(replacements=replacements):
+                result_df = self.node.f(self.df, replacements)[0]
+                expected_df = pd.DataFrame(expected_data)
+                pd.testing.assert_frame_equal(result_df, expected_df)
+
+    def test_invalid_replacement_value_error(self):
+        invalid_cases = [
+            '["cat", "lion"]',  # List is not allowed
+            '{"cat": ["lion", "tiger"]}',  # List is not allowed
+            '{"dog": {"wolf": "coyote"}}'  # Nested dict is not allowed
+        ]
+        for invalid_pairs in invalid_cases:
+            with self.subTest(invalid_pairs=invalid_pairs):
+                with self.assertRaises(ValueError):
+                    self.node.f(self.df, invalid_pairs)
+
+    def test_invalid_replacement_syntax_error(self):
+        invalid_cases = [
+            '{"mountain": ()"hill", "ocean")}',  # Syntax error
+        ]
+        for invalid_pairs in invalid_cases:
+            with self.subTest(invalid_pairs=invalid_pairs):
+                with self.assertRaises(SyntaxError):
+                    self.node.f(self.df, invalid_pairs)
+
+
+
+if __name__ == "__main__":
+    unittest.main()