Merge pull request #225 from sassoftware/update_imputations

fix: update imputation method to avoid warnings

Author: djm21

src/sasctl/_services/model_repository.py

@@ -18,7 +18,6 @@
 from ..core import current_session, delete, get, sasctl_command, RestObj
 from .service import Service
 
-
 FUNCTIONS = {
     "Analytical",
     "Classification",

src/sasctl/pzmm/write_score_code.py

@@ -766,10 +766,16 @@ def impute_missing_values(data):
         """
     impute_values = \\\n + {"var1": 0, "var2": "", "var3": 125.3}
         """
-        self.score_code += f"\n{'':4}return data.replace('           .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore')\n"
-        """
-        
-    return data.replace('           .', np.nan).fillna(impute_values).apply(pd.to_numeric, errors='ignore')
+        self.score_code += (
+            f"\n\n{'':4}# Specify downcasting behavior for pandas 2.x to avoid warnings\n"
+            + f"{'':4}if int(pd.__version__.split('.')[0]) == 2:\n{'':8}pd.set_option('future.no_silent_downcasting', True)\n"
+            + f"{'':4}return data.replace(r'^\\s*\\.$', np.nan, regex=True).fillna(impute_values).infer_objects()\n"
+        )
+        """      
+    # Specify downcasting behavior for pandas 2.x to avoid warnings
+    if int(pd.__version__.split('.')[0]) == 2:
+        pd.set_option('future.no_silent_downcasting', True)
+    return data.replace(r'^\s*\.$', np.nan, regex=True).fillna(impute_values).infer_objects()
         """
 
     # TODO: Needs unit test

tests/integration/test_pymas.py

@@ -10,7 +10,6 @@
 
 import pytest
 
-
 pytest.skip(
     "PyMAS functionality is deprecated and will be removed in a future release.",
     allow_module_level=True,
@@ -241,9 +240,7 @@ def test_from_pickle(train_data, pickle_file):
     end;
     
 endpackage;
-""".lstrip(
-        "\n"
-    )
+""".lstrip("\n")
 
     assert isinstance(p, PyMAS)
 
@@ -343,9 +340,7 @@ def hello_world():
     end;
     
 endpackage;
-""".lstrip(
-        "\n"
-    )
+""".lstrip("\n")
 
     f = tmpdir.join("model.py")
     f.write(code)