update vectorfeature graphing

client/src/components/TabularData/TableSummary.vue

@@ -1,6 +1,6 @@
 <script lang="ts">
 import {
-  Ref, defineComponent, onMounted, ref, computed,
+  Ref, computed, defineComponent, onMounted, ref,
 } from 'vue';
 import { TableSummary, VectorFeatureTableGraph } from '../../types';
 import UVdatApi from '../../api/UVDATApi';
@@ -87,13 +87,29 @@ export default defineComponent({
     };
 
     const availableColumns = computed(() => {
-      const baseColumns = selectedTableType ? summaryData?.tables[selectedTableType]?.columns : [];
-      if (baseColumns.length) {
+      const baseColumns = selectedTableType.value && summaryData.value?.tables[selectedTableType.value]?.columns
+        ? summaryData.value?.tables[selectedTableType.value]?.columns : [];
+      const mappedColumns = baseColumns.map((item) => {
+        const summary = selectedTableType.value && summaryData.value?.tables[selectedTableType.value].summary[item];
+        let subtitle = '';
+        if (summary && summary.description) {
+          subtitle = summary.description;
+        } else if (summary && summary.type === 'number') {
+          subtitle = `${summary.min} to ${summary.max}`;
+        } else if (summary && summary.type === 'string') {
+          subtitle = `${summary.value_count} unique values`;
+        }
+        return {
+          title: item,
+          subtitle,
+        };
+      });
+      if (mappedColumns.length) {
         const takenVals = [selectedXColumn.value, selectedYColumn.value, selectedIndexerColumn].filter((item) => item !== null);
-        return baseColumns.filter((item) => !takenVals.includes(item))
+        return mappedColumns.filter((item) => !takenVals.includes(item.title));
       }
-      return baseColumns;
-    })
+      return mappedColumns;
+    });
 
     const editGraph = (index: number) => {
       const graph = graphs.value[index];
@@ -209,16 +225,19 @@ export default defineComponent({
             <v-select
               v-model="selectedXColumn"
               :items="availableColumns"
+              :item-props="true"
               label="Select X Axis"
             />
             <v-select
               v-model="selectedYColumn"
               :items="availableColumns"
+              :item-props="true"
               label="Select Y Axis"
             />
             <v-select
               v-model="selectedIndexerColumn"
               :items="availableColumns"
+              :item-props="true"
               label="Select Indexer Column"
             />
             <v-btn :disabled="!selectedTableType || !selectedXColumn || !selectedYColumn" color="primary" @click="addSaveGraph">

client/src/types.ts

@@ -749,7 +749,7 @@ interface TableInfo {
 
 type ColumnSummary =
   | NumberColumnSummary
-  | StringColumnSummary
+  | StringColumnSummary;
 
 interface NumberColumnSummary {
   type: 'number';

scripts/nwis/getStats.py

@@ -226,7 +226,7 @@ def generate_summary(df, param_desc, rows):
                 summary[header] = {'type': None, 'values': set(), 'value_count': 0}
                 parameter_cd = param_desc.get(header, None)
                 if parameter_cd:
-                    summary[header]["description"] = parameter_cd,
+                    summary[header]["description"] = parameter_cd[0] if isinstance(parameter_cd, tuple) else parameter_cd
             for value in df[header].unique():
                 if isinstance(value, bool):
                     summary[header]['type'] = 'bool'

uvdat/core/rest/vector_feature_table_data.py

@@ -97,10 +97,8 @@ def table_summary(self, request, *args, **kwargs):
             # Ensure all tables of the same type have consistent columns
             if len(type_columns_map[table_type]) == 0:
                 type_columns_map[table_type] = set(table.columns)
-            elif type_columns_map[table_type] != set(table.columns):
-                raise ValidationError(
-                    f'Table Columns do not match for all tables: {type_columns_map[table_type]} vs {set(table.columns)}'
-                )
+            for column in table.columns:
+                type_columns_map[table_type].add(column)
 
             table_count_map[table_type] += 1
 
@@ -133,7 +131,7 @@ def table_summary(self, request, *args, **kwargs):
                     ][column].get('value_count', 0) + stats.get('value_count', 0)
 
                 if stats.get('description', None):
-                    column_summaries[table_type][column]['desciption'] = stats.get('description', 'Unknown')
+                    column_summaries[table_type][column]['description'] = stats.get('description', 'Unknown')
         # Construct the response
         output = {'vectorFeatureCount': feature_count, 'tables': {}}
         for table_type in type_columns_map:
@@ -146,12 +144,19 @@ def table_summary(self, request, *args, **kwargs):
 
         return Response(output, status=status.HTTP_200_OK)
 
-    def get_graphs(table_type, vector_ids, x_axis, y_axis, indexer='vectorFeatureId'):
+    def get_graphs(self, table_type, vector_ids, x_axis, y_axis, indexer='vectorFeatureId'):
         tables = VectorFeatureTableData.objects.filter(
             type=table_type, vector_feature__in=vector_ids
         )
-        table_data = {'tableName': table.name, 'graphs': {}}
+        if tables.count() == 0:
+            return {'error': f'No tables found for the given vector features {table_type} - {vector_ids}'}
+        table_data = {'tableName': tables.first().name, 'graphs': {}}
         for table in tables:
+            if y_axis not in table.columns or x_axis not in table.columns:
+                logger.warning(
+                    f'Columns {x_axis} and {y_axis} not found in table {table.name} with id: {table.pk}'
+                )
+                continue
             x_axis_index = table.columns.index(x_axis)
             y_axis_index = table.columns.index(y_axis)
             vector_feature_id = table.vector_feature.pk
@@ -163,13 +168,14 @@ def get_graphs(table_type, vector_ids, x_axis, y_axis, indexer='vectorFeatureId'
                 'indexer': index_val,
                 'vectorFeatureId': vector_feature_id,
                 'data' : []
-             }
+            }
             rows = VectorFeatureRowData.objects.filter(vector_feature_table=table)
             for row in rows:
                 row_data = row.row_data
                 x_val = row_data[x_axis_index]
                 y_val = row_data[y_axis_index]
-                table_data['graphs'][vector_feature_id]['data'].append([x_val, y_val])
+                if y_val is not None:
+                    table_data['graphs'][vector_feature_id]['data'].append([x_val, y_val])
         return table_data
 
 
@@ -184,7 +190,7 @@ def feature_graph(self, request, *args, **kwargs):
         if not table_type:
             return Response({'error': 'tableType is required'}, status=status.HTTP_400_BAD_REQUEST)
 
-        graphs = self.get_graphs([vector_feature], x_axis, y_axis, indexer)
+        graphs = self.get_graphs(table_type, [vector_feature], x_axis, y_axis, indexer)
         return Response(graphs, status=status.HTTP_200_OK)
 
     @action(detail=False, methods=['get'], url_path='map-layer-feature-graph')
@@ -212,7 +218,7 @@ def map_layer_feature_graph(self, request, *args, **kwargs):
         if not table_type:
             return Response({'error': 'tableType is required'}, status=status.HTTP_400_BAD_REQUEST)
 
-        graphs = self.get_graphs(vector_features, x_axis, y_axis, indexer)
+        graphs = self.get_graphs(table_type, vector_features, x_axis, y_axis, indexer)
         return Response(graphs, status=status.HTTP_200_OK)
 
     @action(detail=False, methods=['post'], url_path='generate-layer')