no subset means select everything

fractalis/analytics/tasks/correlation/main.py

@@ -19,8 +19,6 @@ class CorrelationTask(AnalyticTask):
             raise ValueError("X or Y are malformed.")
         if method not in ['pearson', 'spearman', 'kendall']:
             raise ValueError("Unknown method '{}'".format(method))
-        if len(subsets) == 0:
-            raise ValueError("No subsets specified.")
 
         df = pd.merge(x, y, on='id')
         df = df.dropna()
@@ -32,6 +30,9 @@ class CorrelationTask(AnalyticTask):
         if df.shape[0] == 0:
             raise ValueError("The current selection does not match any data.")
 
+        if not subsets:
+            subsets = [df['id']]
+
         output = {
             'subsets': {}
         }
@@ -55,6 +56,7 @@ class CorrelationTask(AnalyticTask):
         output.update(global_stats)
         output['method'] = method
         output['data'] = df.to_json()
+        df = df.drop('id', 1)
         output['x_label'] = list(df)[0]
         output['y_label'] = list(df)[1]
         return output

tests/correlation/test_correlation.py

@@ -23,10 +23,10 @@ class TestCorrelation:
         assert result['slope']
         assert result['intercept']
         assert result['subsets']
-        assert result['method']
+        assert result['method'] == 'pearson'
         assert result['data']
-        assert result['x_label']
-        assert result['y_label']
+        assert result['x_label'] == 'A'
+        assert result['y_label'] == 'B'
 
     def test_returns_expected_output_2(self):
         task = CorrelationTask()
@@ -45,9 +45,11 @@ class TestCorrelation:
         arr_2 = np.c_[range(20), np.random.randint(0, 100, size=(20, 1))]
         x = pd.DataFrame(arr_1, columns=['id', 'A'])
         y = pd.DataFrame(arr_2, columns=['id', 'B'])
-        with pytest.raises(ValueError):
-            task.main(x=x, y=y, id_filter=list(range(20)),
-                      method='pearson', subsets=[])
+        result_1 = task.main(x=x, y=y, id_filter=list(range(20)),
+                             method='pearson', subsets=[])
+        result_2 = task.main(x=x, y=y, id_filter=list(range(20)),
+                             method='pearson', subsets=[list(range(20))])
+        assert result_1 == result_2
 
     def test_returns_expected_output_4(self):
         task = CorrelationTask()