Clean up tests

pyam/core.py

@@ -817,7 +817,7 @@ def timeseries(self, iamc_index=False):
             s = self._data.droplevel(self.extra_cols)
             if s.index.has_duplicates:
                 raise ValueError(
-                    "Data with IAMC-index has duplicated index, use `iamc_index=False`"
+                    "Dropping non-IAMC-index causes duplicated index."
                 )
 
         return (

tests/test_core.py

@@ -48,7 +48,7 @@ def test_init_df_with_non_default_index(test_pd_df, index):
     """Casting to IamDataFrame and returning as `timeseries()` yields original frame"""
 
     # set a value to `nan` to check that timeseries columns are ordered correctly
-    test_pd_df.loc[0, test_pd_df.columns[5]] = np.nan
+    test_pd_df.loc[0, 2010] = np.nan
 
     # any number of columns can be set as index
     df = test_pd_df.copy() if index is None else test_pd_df.set_index(index)
@@ -553,7 +553,7 @@ def test_timeseries_long(test_df, unsort):
         exp.columns.name = None
 
     obs = test_df.timeseries()
-    pdt.assert_frame_equal(obs, exp, check_column_type=False)
+    pdt.assert_frame_equal(obs, exp, check_like=True, check_column_type=False)
 
 
 @pytest.mark.parametrize("unsort", [False, True])
@@ -588,11 +588,11 @@ def test_timeseries_time_iamc_raises(test_df_time):
 def test_timeseries_to_iamc_index(test_pd_df, test_df_year):
     """Reducing timeseries() of an IamDataFrame with extra-columns to IAMC-index"""
     test_pd_df["foo"] = "bar"
-    exta_col_df = IamDataFrame(test_pd_df)
-    assert exta_col_df.extra_cols == ["foo"]
+    extra_col_df = IamDataFrame(test_pd_df)
+    assert extra_col_df.extra_cols == ["foo"]
 
     # assert that reducing to IAMC-columns (dropping extra-columns) with timeseries()
-    obs = exta_col_df.timeseries(iamc_index=True)
+    obs = extra_col_df.timeseries(iamc_index=True)
     exp = test_df_year.timeseries()
     pdt.assert_frame_equal(obs, exp)
 
@@ -602,13 +602,14 @@ def test_timeseries_to_iamc_index_duplicated_raises(test_pd_df):
     test_pd_df = pd.concat([test_pd_df, test_pd_df])
     # adding an extra-col creates a unique index
     test_pd_df["foo"] = ["bar", "bar", "bar", "baz", "baz", "baz"]
-    exta_col_df = IamDataFrame(test_pd_df)
-    assert exta_col_df.extra_cols == ["foo"]
+
+    extra_col_df = IamDataFrame(test_pd_df)
+    assert extra_col_df.extra_cols == ["foo"]
 
     # dropping the extra-column by setting `iamc_index=True` creates duplicated index
-    match = "Index contains duplicate entries, cannot reshape"
+    match = "Dropping non-IAMC-index causes duplicated index"
     with pytest.raises(ValueError, match=match):
-        exta_col_df.timeseries(iamc_index=True)
+        extra_col_df.timeseries(iamc_index=True)
 
 
 def test_pivot_table(test_df):

tests/test_feature_append_concat.py

@@ -92,18 +92,22 @@ def test_concat(test_df, reverse, iterable):
     if iterable:
         dfs = iter(dfs)
 
-    result = concat(dfs)
+    obs = concat(dfs)
 
     # check that the original object is not updated
     assert test_df.scenario == ["scen_a", "scen_b"]
     assert other.scenario == ["scen_c"]
 
     # assert that merging of meta works as expected
-    pdt.assert_frame_equal(result.meta[EXP_META.columns], EXP_META, check_like=True)
+    pdt.assert_frame_equal(obs.meta, EXP_META, check_like=True)
 
     # assert that appending data works as expected
-    ts = result.timeseries()
-    npt.assert_array_equal(ts.iloc[2].values, ts.iloc[3].values)
+    ts = obs.timeseries()
+    print(ts)
+    pdt.assert_frame_equal(
+        ts.iloc[0:1].droplevel("scenario"),
+        ts.iloc[3:].droplevel("scenario")
+    )
 
 
 def test_concat_non_default_index():