fix: raise clear errors for missing values in panel index

linearmodels/panel/data.py

@@ -368,6 +368,11 @@ def entity_ids(self) -> linearmodels.typing.data.IntArray:
             2d array containing entity ids corresponding dataframe view
         """
         index = self.index
+        if np.any(index.codes[0] < 0):
+            raise ValueError(
+                "The entity index contains missing values (NaN), which are not "
+                "supported and are encoded as -1 in the entity ids."
+            )
         return np.asarray(index.codes[0])[:, None]
 
     @property
@@ -381,6 +386,11 @@ def time_ids(self) -> linearmodels.typing.data.IntArray:
             2d array containing time ids corresponding dataframe view
         """
         index = self.index
+        if np.any(index.codes[1] < 0):
+            raise ValueError(
+                "The time index contains missing values (NaN), which are not "
+                "supported and are encoded as -1 in the time ids."
+            )
         return np.asarray(index.codes[1])[:, None]
 
     def _demean_both_low_mem(self, weights: PanelData | None) -> PanelData:

linearmodels/panel/model.py

@@ -93,6 +93,12 @@ def _lstsq(
 
 
 def panel_structure_stats(ids: linearmodels.typing.data.IntArray, name: str) -> Series:
+    ids = np.asarray(ids)
+    if np.any(ids < 0):
+        raise ValueError(
+            f"{name} cannot be computed: ids must be non-negative integers. "
+            "Negative ids indicate missing values (NaN) in the panel index."
+        )
     bc = np.bincount(ids)
     bc = bc[bc > 0]
     index = ["mean", "median", "max", "min", "total"]

linearmodels/tests/panel/test_data.py

@@ -4,13 +4,13 @@
 import numpy as np
 from numpy.linalg import lstsq, pinv
 from numpy.testing import assert_allclose, assert_equal
-from pandas import Categorical, DataFrame, Series, date_range, get_dummies
+from pandas import Categorical, DataFrame, MultiIndex, Series, date_range, get_dummies
 from pandas.api.types import is_string_dtype
 from pandas.testing import assert_frame_equal, assert_index_equal
 import pytest
 
 from linearmodels.panel.data import PanelData, _Panel
-from linearmodels.panel.model import PanelOLS
+from linearmodels.panel.model import PanelOLS, panel_structure_stats
 from linearmodels.shared.utility import panel_to_frame
 from linearmodels.tests.panel._utility import MISSING_XARRAY, datatypes, generate_data
 
@@ -223,6 +223,33 @@ def test_ids(mi_df):
         assert np.ptp(tids[i::7]) == 0
 
 
+def test_entity_ids_with_missing_index():
+    n, t = 4, 3
+    index = MultiIndex.from_tuples(
+        [(np.nan if i == 0 else f"e{i}", j) for i in range(n) for j in range(1, t + 1)],
+        names=["entity", "time"],
+    )
+    data = PanelData(DataFrame(np.random.standard_normal((n * t, 2)), index=index))
+    with pytest.raises(ValueError, match="entity index contains missing"):
+        _ = data.entity_ids
+
+
+def test_time_ids_with_missing_index():
+    n, t = 4, 3
+    index = MultiIndex.from_tuples(
+        [(f"e{i}", np.nan if j == 1 else j) for i in range(n) for j in range(1, t + 1)],
+        names=["entity", "time"],
+    )
+    data = PanelData(DataFrame(np.random.standard_normal((n * t, 2)), index=index))
+    with pytest.raises(ValueError, match="time index contains missing"):
+        _ = data.time_ids
+
+
+def test_panel_structure_stats_negative_ids():
+    with pytest.raises(ValueError, match="non-negative"):
+        panel_structure_stats(np.array([0, 1, -1]), "test")
+
+
 def test_str_repr(mi_df):
     data = PanelData(mi_df)
     assert "PanelData" in str(data)