diff --git a/api/api_v1/endpoints/query.py b/api/api_v1/endpoints/query.py
index b5fb180..f748234 100644
--- a/api/api_v1/endpoints/query.py
+++ b/api/api_v1/endpoints/query.py
@@ -137,7 +137,7 @@ async def event_model(
             q['groups'].append(groupby)
             q['values'].append(df['values'].to_list())
             q['sum'].append(float(df['values'].sum()))
-            q['avg'].append(float(df['values'].mean()))
+            q['avg'].append(round(float(df['values'].mean()),2))
             for last_value in df['values'].values[::-1]:
                 if last_value > 0:
                     q['last_value'] = float(last_value)
@@ -166,7 +166,7 @@ async def event_model(
                 df_group.sort_values('date', inplace=True)
                 q['values'].append(df_group['values'].to_list())
                 q['sum'].append(float(df_group['values'].sum()))
-                q['avg'].append(float(df_group['values'].mean()))
+                q['avg'].append(round(float(df_group['values'].mean()),2))
                 for last_value in df['values'].values[::-1]:
                     if last_value > 0:
                         q['last_value'] = float(last_value)
@@ -189,7 +189,7 @@ async def event_model(
                     q['last_value'] = float(last_value)
                     break
             q['sum'].append(float(df['values'].sum()))
-            q['avg'].append(float(df['values'].mean()))
+            q['avg'].append(round(float(df['values'].mean()),2))
         if item['time_particle'] in ('P1D', 'P1W'):
             q['date_range'] = [d.strftime('%Y-%m-%d') for d in q['date_range']]
         elif item['time_particle'] in ('P1M',):