BUG: Fix TypeError in json_normalize with non-str meta key and record_path

Author: dongwonmoon

pandas/io/json/_normalize.py

@@ -552,7 +552,12 @@ 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 = []
+    for val in _meta:
+        if len(val) == 1:
+            meta_keys.append(val[0])
+        else:
+            meta_keys.append(sep.join(str(x) for x in val))
 
     def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
         if isinstance(data, dict):
@@ -568,9 +573,11 @@ def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
             for obj in data:
                 recs = _pull_records(obj, path[0])
                 recs = [
-                    nested_to_record(r, sep=sep, max_level=max_level)
-                    if isinstance(r, dict)
-                    else r
+                    (
+                        nested_to_record(r, sep=sep, max_level=max_level)
+                        if isinstance(r, dict)
+                        else r
+                    )
                     for r in recs
                 ]
 

pandas/tests/io/json/test_normalize.py

@@ -593,6 +593,34 @@ 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_int_key_with_record_path(self):
+        # 63019
+        data = [
+            {
+                "a": 1,
+                12: "meta_value_1",
+                "nested": [{"b": 2, "c": 3}],
+            },
+            {
+                "a": 6,
+                12: "meta_value_2",
+                "nested": [{"b": 7, "c": 8}],
+            },
+        ]
+
+        result = json_normalize(data, record_path=["nested"], meta=[12, "a"])
+
+        expected_data = {
+            "b": [2, 7],
+            "c": [3, 8],
+            12: ["meta_value_1", "meta_value_2"],
+            "a": [1, 6],
+        }
+        expected_columns = ["b", "c", 12, "a"]
+        expected = DataFrame(expected_data, columns=expected_columns)
+
+        tm.assert_frame_equal(result, expected)
+
 
 class TestNestedToRecord:
     def test_flat_stays_flat(self):