BUG:#29928 Fix to_json output with 'table' orient for single level MultiIndex.

Index field name in written json was incorrect, so applying read_json resulted in NaN index values. Dataframe to_json with 'table' orient now treats single level MultiIndex like single Index.

Author: LucasG0

doc/source/whatsnew/v1.1.0.rst

@@ -802,6 +802,7 @@ I/O
 - Bug in :meth:`~DataFrame.read_feather` was raising an `ArrowIOError` when reading an s3 or http file path (:issue:`29055`)
 - Bug in :meth:`read_parquet` was raising a ``FileNotFoundError`` when passed an s3 directory path. (:issue:`26388`)
 - Bug in :meth:`~DataFrame.to_parquet` was throwing an ``AttributeError`` when writing a partitioned parquet file to s3 (:issue:`27596`)
+- Bug in :meth:`~DataFrame.to_json` with 'table' orient was writting wrong index field name for MultiIndex Dataframe with a single level. (:issue:`29928`)
 
 Plotting
 ^^^^^^^^

pandas/io/json/_table_schema.py

@@ -21,7 +21,7 @@
 )
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
-from pandas import DataFrame
+from pandas import DataFrame, MultiIndex
 import pandas.core.common as com
 
 loads = json.loads
@@ -230,6 +230,10 @@ def build_table_schema(data, index=True, primary_key=None, version=True):
     'pandas_version': '0.20.0',
     'primaryKey': ['idx']}
     """
+
+    if data.index.nlevels == 1 and isinstance(data.index, MultiIndex):
+        data.index = data.index.get_level_values(0)
+
     if index is True:
         data = set_default_names(data)
 

pandas/tests/io/json/test_json_table_schema.py

@@ -435,6 +435,23 @@ def test_to_json_categorical_index(self):
 
         assert result == expected
 
+    @pytest.mark.parametrize("name", [None, "foo"])
+    def test_multiindex_single_level(self, name):
+        # GH29928
+        index = pd.Index([1, 2, 3, 4], name=name)
+        df = pd.DataFrame(
+            data=[[1, 1], [2, 2], [3, 3], [4, 4]], columns=["A", "B"], index=index
+        )
+        expected = df.to_json(orient="table")
+
+        index = pd.MultiIndex.from_tuples([(1,), (2,), (3,), (4,)], names=[name])
+        df = pd.DataFrame(
+            data=[[1, 1], [2, 2], [3, 3], [4, 4]], columns=["A", "B"], index=index
+        )
+        result = df.to_json(orient="table")
+
+        assert result == expected
+
     def test_date_format_raises(self):
         with pytest.raises(ValueError):
             self.df.to_json(orient="table", date_format="epoch")