BUG: json_normalize handles non‑string keys in meta with record_path (GH#62264)

doc/source/whatsnew/v2.3.3.rst

@@ -24,6 +24,7 @@ Bug fixes
 ^^^^^^^^^
 - Fix regression in ``~Series.str.contains``, ``~Series.str.match`` and ``~Series.str.fullmatch``
   with a compiled regex and custom flags (:issue:`62240`)
+- Fixed bug in :func:`pandas.json_normalize` raising ``TypeError`` when non‑string elements were used in ``meta`` with ``record_path``; ``meta`` path elements are now coerced to strings when forming column labels (:issue:`62264`).
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_233.contributors:

pandas/io/json/_normalize.py

@@ -292,6 +292,7 @@ def json_normalize(
         assumed to be an array of records.
     meta : list of paths (str or list of str), default None
         Fields to use as metadata for each record in resulting table.
+        Path elements are converted to strings before joining into column labels.
     meta_prefix : str, default None
         If True, prefix records with dotted path, e.g. foo.bar.field if
         meta is ['foo', 'bar'].
@@ -322,6 +323,12 @@ def json_normalize(
     DataFrame : Two-dimensional, size-mutable, potentially heterogeneous tabular data.
     Series : One-dimensional ndarray with axis labels (including time series).
 
+    Notes
+    -----
+    Column labels are constructed by joining path elements,
+    with sep and are always strings after normalization;
+    non-string elements in meta paths are coerced to strings.
+
     Examples
     --------
     >>> data = [
@@ -540,7 +547,7 @@ def _pull_records(js: dict[str, Any], spec: list | str) -> list:
     lengths = []
 
     meta_vals: DefaultDict = defaultdict(list)
-    meta_keys = [sep.join(val) for val in _meta]
+    meta_keys = [sep.join(str(v) for v in val) for val in _meta]
 
     def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
         if isinstance(data, dict):

pandas/tests/io/json/test_normalize.py

@@ -569,6 +569,23 @@ def test_series_index(self, state_data):
         result = json_normalize(series, "counties")
         tm.assert_index_equal(result.index, idx.repeat([3, 2]))
 
+    def test_json_normalize_meta_int_key_with_record_path(self):
+        # GH#62264
+        data = [{"name": "Alice", 12: 20, "purchases": [{"pid": 301}, {"pid": 302}]}]
+
+        result = json_normalize(data, record_path=["purchases"], meta=[12, "name"])
+
+        expected = DataFrame(
+            {
+                "pid": [301, 302],
+                "12": np.array([20, 20], dtype=object),
+                "name": ["Alice", "Alice"],
+            },
+            columns=["pid", "12", "name"],
+        )
+
+        tm.assert_frame_equal(result[["pid", "12", "name"]], expected)
+
 
 class TestNestedToRecord:
     def test_flat_stays_flat(self):