Fix default report X and Y axis selectors (#4542)

* fix default reports and code duplication in inventory_filter

* fix default dropdown selections

* remove old test

---------

Co-authored-by: Hannah Eslinger <[email protected]>

seed/static/seed/partials/inventory_reports.html

@@ -39,12 +39,12 @@ <h2 style="font-size: 18px"><i class="fa-solid fa-bar-chart pull-left"></i> {$::
                 <div style="display: flex; flex-direction: column;">
                   <div class="form-group pad-bottom-10">
                     <label for="xAxisSelector">{$:: 'X Axis' | translate $}:</label>
-                    <sd-dropdown is-button id="xAxisSelector" ng-model="xAxisSelectedItem" items="xAxisVars"></sd-dropdown>
+                    <select class="form-control" id="xAxisSelector" ng-model="xAxisSelectedItem" ng-options="x.name for x in xAxisVars track by x.varName"></select>
                   </div>
 
                   <div class="form-group">
                     <label for="yAxisSelector">{$:: 'Y Axis' | translate $}:</label>
-                    <sd-dropdown is-button id="yAxisSelector" ng-model="yAxisSelectedItem" items="yAxisVars"></sd-dropdown>
+                    <select class="form-control" id="yAxisSelector" ng-model="yAxisSelectedItem" ng-options="y.name for y in yAxisVars track by y.varName"></select>
                   </div>
                 </div>
                 <div class="form-group">

seed/utils/generic.py

@@ -45,6 +45,9 @@ def split_model_fields(obj, fields):
 def median(lst):
     if not lst:
         return
+    # ensure list of not a bunch of "None"
+    if set(lst) is {None}:
+        return
     index = (len(lst) - 1) // 2
     if len(lst) % 2:
         #

seed/views/v3/organizations.py

@@ -997,7 +997,6 @@ def report_aggregated(self, request, pk=None):
         # get data
         cycles = Cycle.objects.filter(id__in=params["cycle_ids"])
         data = self.get_raw_report_data(pk, access_level_instance, cycles, params["x_var"], params["y_var"])
-
         chart_data = []
         property_counts = []
         for datum in data:
@@ -1035,13 +1034,15 @@ def aggregate_property_type(self, yr_e, x_var, buildings):
             grouped_uses[str(b['y']).lower()].append(b)
 
         # Now iterate over use groups to make each chart item
+        # Only include non-None values
         for use, buildings_in_uses in grouped_uses.items():
-            x = [b['x'] for b in buildings_in_uses]
-            chart_data.append({
-                'x': sum(x) if x_var == "Count" else median(x),
-                'y': use.capitalize(),
-                'yr_e': yr_e
-            })
+            x = [b['x'] for b in buildings_in_uses if b['x'] is not None]
+            if x:
+                chart_data.append({
+                    'x': sum(x) if x_var == "Count" else median(x),
+                    'y': use.capitalize(),
+                    'yr_e': yr_e
+                })
         return chart_data
 
     def aggregate_year_built(self, yr_e, x_var, buildings):
@@ -1053,7 +1054,7 @@ def aggregate_year_built(self, yr_e, x_var, buildings):
 
         # Now iterate over decade groups to make each chart item
         for decade, buildings_in_decade in grouped_decades.items():
-            x = [b['x'] for b in buildings_in_decade]
+            x = [b['x'] for b in buildings_in_decade if b['x'] is not None]
             chart_data.append({
                 'x': sum(x) if x_var == "Count" else median(x),
                 'y': '%s-%s' % (decade, '%s9' % str(decade)[:-1]),  # 1990-1999
@@ -1081,6 +1082,8 @@ def aggregate_gross_floor_area(self, yr_e, x_var, buildings):
         # Group buildings in this year_ending group into ranges
         grouped_ranges = defaultdict(list)
         for b in buildings:
+            if b['y'] is None:
+                continue
             area = b['y']
             # make sure anything greater than the biggest bin gets put in
             # the biggest bin
@@ -1089,7 +1092,7 @@ def aggregate_gross_floor_area(self, yr_e, x_var, buildings):
 
         # Now iterate over range groups to make each chart item
         for range_floor, buildings_in_range in grouped_ranges.items():
-            x = [b['x'] for b in buildings_in_range]
+            x = [b['x'] for b in buildings_in_range if b['x'] is not None]
             chart_data.append({
                 'x': sum(x) if x_var == "Count" else median(x),
                 'y': y_display_map[range_floor],