Deprecate set_weight_col() in favor of set_weights()

- Add deprecation warning to set_weight_col() (Fixes #208)
- Add test for set_weights() with string column name argument
- set_weights() already handles both array and string inputs
- Users should use set_weights(column_name) instead of set_weight_col(column_name)

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>

Author: MaxGhenis

changelog_entry.yaml

@@ -8,3 +8,6 @@
     - __getattr__ method to MicroDataFrame for intuitive column access via dot notation (Fixes #220)
     - Full pandas argument support to drop() and merge() methods (Addresses #212)
     - nullify_weights() method to both MicroDataFrame and MicroSeries to set all weights to 1 (Fixes #176)
+    - Test coverage for set_weights() with string column name argument
+    deprecated:
+    - set_weight_col() method - use set_weights() with a string argument instead (Fixes #208)

microdf/microdataframe.py

@@ -225,11 +225,23 @@ def set_weight_col(
         """Sets the weights for the MicroDataFrame by specifying the name of
         the weight column.
 
-        :param weights: Array of weights.
+        .. deprecated:: 1.0.2
+            Use :meth:`set_weights` with a string argument instead.
+            This method will be removed in a future version.
+
+        :param column: Name of the column to use as weights.
         :param preserve_old: If True, keeps the old weights as a column when
             new weights are provided.
-        :type weights: np.array
+        :type column: str
         """
+        import warnings
+        warnings.warn(
+            "set_weight_col is deprecated and will be removed in a future version. "
+            "Use set_weights(column_name) instead.",
+            DeprecationWarning,
+            stacklevel=2
+        )
+        
         if preserve_old and self.weights_col is not None:
             self["old_" + self.weights_col] = self.weights
 

microdf/tests/test_microseries_dataframe.py

@@ -22,6 +22,14 @@ def test_df_init() -> None:
     df["w"] = w
     df.set_weight_col("w")
     assert df.a.mean() == np.average(arr, weights=w)
+    
+    # Test set_weights with string (column name)
+    df2 = mdf.MicroDataFrame()
+    df2["a"] = arr
+    df2["w"] = w
+    df2.set_weights("w")  # Using string column name instead of set_weight_col
+    assert df2.a.mean() == np.average(arr, weights=w)
+    assert np.array_equal(df2.weights.values, w)
 
 
 def test_handles_empty_index() -> None: