Codex CI R2: DiD front-door conley_coords validation

P1 [new in R2] — DiD.fit() didn't validate conley_coords shape or
column existence; malformed tuples or missing column names fell through
to opaque IndexError/KeyError downstream. Mirrors the unit-column guard
from R1.

Adds two checks in the DiD Conley block:
  - conley_coords must be a 2-element tuple/list of strings (raises if
    arity wrong or any element non-string).
  - Each named column must exist in `data` (raises ValueError naming
    the missing column).

Adds two regression tests in TestConleyEstimatorIntegration:
  - test_did_conley_unknown_coord_column_raises
  - test_did_conley_malformed_coord_tuple_raises (covers 1-element
    tuple and non-string element)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: igerber

diff_diff/estimators.py

@@ -413,6 +413,22 @@ def fit(
                     "conley_coords=(lat_col, lon_col) and conley_cutoff_km "
                     "on the constructor."
                 )
+            # Validate conley_coords is a 2-element tuple/list of strings
+            # and both columns exist on `data`. Without these guards, a
+            # malformed tuple or missing column fell through to an opaque
+            # IndexError / pandas KeyError downstream. Codex CI R2 P1.
+            if (
+                not isinstance(self.conley_coords, (tuple, list))
+                or len(self.conley_coords) != 2
+                or not all(isinstance(c, str) for c in self.conley_coords)
+            ):
+                raise ValueError(
+                    "conley_coords must be a 2-element tuple/list of column "
+                    f"names (lat_col, lon_col); got {self.conley_coords!r}."
+                )
+            for _coord_col in self.conley_coords:
+                if _coord_col not in data.columns:
+                    raise ValueError(f"conley_coords column '{_coord_col}' not found in data.")
             if survey_design is not None:
                 raise NotImplementedError(
                     "DifferenceInDifferences(vcov_type='conley') + survey_design "

tests/test_conley_vcov.py

@@ -1099,6 +1099,61 @@ def test_did_conley_unknown_unit_column_raises(self, two_period_panel):
                 unit="missing_unit",
             )
 
+    def test_did_conley_unknown_coord_column_raises(self, two_period_panel):
+        """vcov_type='conley' with `conley_coords=(<absent>, <col>)` raises
+        a clear estimator-level ValueError before downstream column access.
+        Codex CI R2 P1."""
+        from diff_diff import DifferenceInDifferences
+
+        with pytest.raises(ValueError, match="conley_coords column 'missing_lat' not found"):
+            DifferenceInDifferences(
+                vcov_type="conley",
+                conley_coords=("missing_lat", "lon"),
+                conley_cutoff_km=2000.0,
+                conley_lag_cutoff=1,
+            ).fit(
+                two_period_panel,
+                outcome="y",
+                treatment="treated",
+                time="time",
+                unit="unit",
+            )
+
+    def test_did_conley_malformed_coord_tuple_raises(self, two_period_panel):
+        """vcov_type='conley' with a malformed conley_coords (wrong arity or
+        non-string elements) raises ValueError before downstream access.
+        Codex CI R2 P1."""
+        from diff_diff import DifferenceInDifferences
+
+        # Wrong arity (1-element tuple)
+        with pytest.raises(ValueError, match="2-element tuple/list of column"):
+            DifferenceInDifferences(
+                vcov_type="conley",
+                conley_coords=("lat",),  # type: ignore[arg-type]
+                conley_cutoff_km=2000.0,
+                conley_lag_cutoff=1,
+            ).fit(
+                two_period_panel,
+                outcome="y",
+                treatment="treated",
+                time="time",
+                unit="unit",
+            )
+        # Non-string element
+        with pytest.raises(ValueError, match="2-element tuple/list of column"):
+            DifferenceInDifferences(
+                vcov_type="conley",
+                conley_coords=("lat", 0),  # type: ignore[arg-type]
+                conley_cutoff_km=2000.0,
+                conley_lag_cutoff=1,
+            ).fit(
+                two_period_panel,
+                outcome="y",
+                treatment="treated",
+                time="time",
+                unit="unit",
+            )
+
     def test_did_conley_missing_lag_cutoff_raises(self, two_period_panel):
         """vcov_type='conley' without conley_lag_cutoff raises ValueError."""
         from diff_diff import DifferenceInDifferences