Include timestamp and value label so that those columns appear in the output.

diff --git a/web/seepark_web.py b/web/seepark_web.py
index 368f208f9e79cfbe800d0f8165fdc6c8c68a0fc3..cbe55f85f174ecc253868e52aa36c30d76ffc56d 100644 (file)
--- a/web/seepark_web.py
+++ b/web/seepark_web.py
@@ -94,7 +94,9 @@ def select_sensordata_grouped(sensor_id, sensor_type, begin, end):
 
     # Let the database do the grouping. Example in SQL (MySQL):
     # select to_seconds(datetime) DIV (60*60*24) as interval_id, min(datetime), max(datetime), min(temp), avg(temp), max(temp), count(temp) from openweathermap group by interval_id order by interval_id;
 
     # Let the database do the grouping. Example in SQL (MySQL):
     # select to_seconds(datetime) DIV (60*60*24) as interval_id, min(datetime), max(datetime), min(temp), avg(temp), max(temp), count(temp) from openweathermap group by interval_id order by interval_id;

-    query = db.session.query(func.to_seconds(Sensors.timestamp).op('div')(resolution).label('g'), func.min(Sensors.timestamp), func.mean(Sensors.value),
+    query = db.session.query(func.to_seconds(Sensors.timestamp).op('div')(resolution).label('g'),
+            func.min(Sensors.timestamp).label('timestamp'),
+            func.avg(Sensors.value).label('value'),

             Sensors.sensor_id, Sensors.value_type, Sensors.sensor_name)
     if sensor_id is not None:
         query = query.filter(Sensors.sensor_id == sensor_id)
             Sensors.sensor_id, Sensors.value_type, Sensors.sensor_name)
     if sensor_id is not None:
         query = query.filter(Sensors.sensor_id == sensor_id)