BUG: Fix #57608: queries on categorical string columns in HDFStore.select() return unexpected results. (#61225)

* BUG: Fix #57608: queries on categorical string columns in
HDFStore.select() return unexpected results.
In function __init__() of class Selection (pandas/core/io/pytables.py),
the method self.terms.evaluate() was not returning the correct value
for the where condition. The issue stemmed from the function
convert_value() of class BinOp (pandas/core/computation/pytables.py),
where the function searchedsorted() did not return the correct index
when matching the where condition in the metadata (categories table).
Replacing searchsorted() with np.where() resolves this issue.

* BUG: Follow-up for #57608: check if metadata is sorted before search

* BUG: Follow-up for #57608: use direct match via np.flatnonzero

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Author: SofiaSM45

doc/source/whatsnew/v3.0.0.rst

@@ -775,6 +775,7 @@ I/O
 - Bug in :meth:`DataFrame.to_stata` when writing more than 32,000 value labels. (:issue:`60107`)
 - Bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames. (:issue:`16098`)
 - Bug in :meth:`HDFStore.get` was failing to save data of dtype datetime64[s] correctly (:issue:`59004`)
+- Bug in :meth:`HDFStore.select` causing queries on categorical string columns to return unexpected results (:issue:`57608`)
 - Bug in :meth:`read_csv` causing segmentation fault when ``encoding_errors`` is not a string. (:issue:`59059`)
 - Bug in :meth:`read_csv` raising ``TypeError`` when ``index_col`` is specified and ``na_values`` is a dict containing the key ``None``. (:issue:`57547`)
 - Bug in :meth:`read_csv` raising ``TypeError`` when ``nrows`` and ``iterator`` are specified without specifying a ``chunksize``. (:issue:`59079`)

pandas/core/computation/pytables.py

@@ -239,7 +239,8 @@ def stringify(value):
             if conv_val not in metadata:
                 result = -1
             else:
-                result = metadata.searchsorted(conv_val, side="left")
+                # Find the index of the first match of conv_val in metadata
+                result = np.flatnonzero(metadata == conv_val)[0]
             return TermValue(result, result, "integer")
         elif kind == "integer":
             try:

pandas/tests/io/pytables/test_store.py

@@ -23,6 +23,9 @@
     timedelta_range,
 )
 import pandas._testing as tm
+from pandas.api.types import (
+    CategoricalDtype,
+)
 from pandas.tests.io.pytables.common import (
     _maybe_remove,
     ensure_clean_store,
@@ -1107,3 +1110,23 @@ def test_store_bool_index(tmp_path, setup_path):
     df.to_hdf(path, key="a")
     result = read_hdf(path, "a")
     tm.assert_frame_equal(expected, result)
+
+
+@pytest.mark.parametrize("model", ["name", "longname", "verylongname"])
+def test_select_categorical_string_columns(tmp_path, model):
+    # Corresponding to BUG: 57608
+
+    path = tmp_path / "test.h5"
+
+    models = CategoricalDtype(categories=["name", "longname", "verylongname"])
+    df = DataFrame(
+        {"modelId": ["name", "longname", "longname"], "value": [1, 2, 3]}
+    ).astype({"modelId": models, "value": int})
+
+    with HDFStore(path, "w") as store:
+        store.append("df", df, data_columns=["modelId"])
+
+    with HDFStore(path, "r") as store:
+        result = store.select("df", "modelId == model")
+        expected = df[df["modelId"] == model]
+        tm.assert_frame_equal(result, expected)