[BUG] Cannot use 'Value' as the column name for observation column

src/csvcubed/utils/csvdataset.py

@@ -306,15 +306,29 @@ def _melt_data_set(
     ]
     id_cols = list(set(data_set.columns) - set(value_cols))
 
+    # Checking for any columns with the title "Value" and changing the value_name
+    # parameter passed to the melt function to "Not-Value" so that we don't
+    # trigger a pandas ValueError.
+    value_name = "Value"
+    for col_title in value_cols:
+        if col_title == "Value":
+            value_name = "Not-Value"
+
     # Melting the data set using pandas melt function.
-    return pd.melt(
+    melted_df = pd.melt(
         data_set,
         id_vars=id_cols,
         value_vars=value_cols,
-        value_name="Value",
+        value_name=value_name,
         var_name="Observation Value",
     )
 
+    # Renaming columns in the returned melted df to their original title "Value"
+    if value_name == "Not-Value":
+        melted_df.rename(columns={"Not-Value": "Value"}, inplace=True)
+
+    return melted_df
+
 
 def _get_unit_measure_col_for_standard_shape_cube(
     qube_components: List[QubeComponentResult],

tests/unit/inspect/test_inspectdatasetmanager.py

@@ -263,6 +263,16 @@
     ]
 ).replace("", np.NAN)
 
+_expected_by_measure_and_unit_val_counts_df_with_column_titled_value = DataFrame(
+    [
+        {
+            "Measure": "gas emissions(gwp-ar4)",
+            "Unit": "millions of tonnes of carbon dioxide (mt co2)",
+            "Count": 19,
+        }
+    ]
+).replace("", np.NAN)
+
 
 def get_arguments_qb_dataset(
     data_cube_repository: DataCubeRepository,
@@ -589,6 +599,7 @@ def test_get_val_counts_info_multi_unit_single_measure_dataset():
         / "new"
         / "multi-unit-single-measure-dataset.csv-metadata.json"
     )
+
     data_cube_repository = get_data_cube_repository(csvw_metadata_json_path)
 
     (dataset, qube_components, csv_url) = get_arguments_qb_dataset(data_cube_repository)
@@ -829,3 +840,45 @@ def test_get_concepts_hierarchy_info_hierarchy_with_depth_more_than_one():
     assert isinstance(result.tree, Tree)
     assert result.tree.depth() == 2
     assert len(result.tree.all_nodes_itr()) == 10
+
+
+def test_melt_works_when_column_titled_value_exists():
+    """
+    When a df with a column titled "Value" is passed to the melt function in
+    pandas 2.0 a ValueError is produced because of the column title. This test
+    uses a dataset with a "Value" titled column and should be melted when
+    transform_dataset_to_canonical_shape is called. In this case, the "value_name
+    parameter of melt() is given a different string (default is "Value") and then
+    we rename this column back to "Value" in the returned melted df.
+    """
+    csvw_metadata_json_path = (
+        _test_case_base_dir
+        / "multi-unit_single-measure"
+        / "final-uk-greenhouse-gas-emissions-national-statistics-1990-to-2019.csv-metadata.json"
+    )
+
+    data_cube_repository = get_data_cube_repository(csvw_metadata_json_path)
+
+    (dataset, qube_components, csv_url) = get_arguments_qb_dataset(data_cube_repository)
+
+    (
+        canonical_shape_dataset,
+        measure_col,
+        unit_col,
+    ) = transform_dataset_to_canonical_shape(
+        data_cube_repository,
+        dataset,
+        csv_url,
+        qube_components,
+    )
+
+    result: DatasetObservationsByMeasureUnitInfoResult = get_dataset_val_counts_info(
+        canonical_shape_dataset, measure_col, unit_col
+    )
+
+    assert result is not None
+    assert set(dataset.columns).issubset(set(canonical_shape_dataset.columns))
+    assert_frame_equal(
+        result.by_measure_and_unit_val_counts_df,
+        _expected_by_measure_and_unit_val_counts_df_with_column_titled_value,
+    )