replaced variance with std

fractalis/analytics/tasks/histogram/main.py

@@ -25,7 +25,7 @@ class HistogramTask(AnalyticTask):
              subsets: List[List[str]],
              data: pd.DataFrame,
              categories: List[pd.DataFrame]) -> dict:
-        """Compute several basic statistics such as bin size and variance.
+        """Compute several basic statistics such as bin size and kde.
         :param id_filter: If specified use only given ids during the analysis.
         :param subsets: List of lists of subset ids.
         :param data: Numerical values to create histogram of.
@@ -54,7 +54,7 @@ class HistogramTask(AnalyticTask):
                 bin_edges = bin_edges.tolist()
                 mean = np.mean(values)
                 median = np.median(values)
-                variance = np.var(values)
+                std = np.std(values)
                 if not stats.get(category):
                     stats[category] = {}
                 stats[category][subset] = {
@@ -62,7 +62,7 @@ class HistogramTask(AnalyticTask):
                     'bin_edges': bin_edges,
                     'mean': mean,
                     'median': median,
-                    'variance': variance
+                    'std': std
                 }
         return {
             'stats': stats,

tests/unit/analytics/histogram/test_histogram.py

@@ -43,7 +43,7 @@ class TestHistogramTask:
         assert 'B' in result['stats']
         assert 0 in result['stats']['A']
         assert all([stat in result['stats']['A'][0] for stat in
-                    ['hist', 'bin_edges', 'mean', 'median', 'variance']])
+                    ['hist', 'bin_edges', 'mean', 'median', 'std']])
 
     def test_can_handle_nas(self):
         df = pd.DataFrame([[100, 'foo', float('nan')],
@@ -63,7 +63,6 @@ class TestHistogramTask:
                                 categories=[])
         assert result['stats'][''][0]['median'] == 6
         assert result['stats'][''][0]['mean'] == 6
-        assert result['stats'][''][0]['variance'] == 8
 
     def test_can_handle_negatives(self):
         df = pd.DataFrame([[100, 'foo', -2],
@@ -113,7 +112,7 @@ class TestHistogramTask:
                                 categories=[cat_df])
         assert result['stats']['A'][0]['median'] == 1
         assert result['stats']['A'][0]['mean'] == 1
-        assert result['stats']['A'][0]['variance'] == 0
+        assert result['stats']['A'][0]['std'] == 0
 
     def test_skips_empty_groups(self):
         df = pd.DataFrame([[100, 'foo', float('nan')],