diff --git a/rowers/dataprepnodjango.py b/rowers/dataprepnodjango.py
index 52400767..f41498fb 100644
--- a/rowers/dataprepnodjango.py
+++ b/rowers/dataprepnodjango.py
@@ -715,6 +715,8 @@ def getsmallrowdata_db(columns,ids=[],debug=False):
     data = []
     columns = [c for c in columns if c != 'None']
 
+    df = pd.DataFrame()
+
     if len(ids)>1:
         for id, f in zip(ids,csvfilenames):
             try:
@@ -728,11 +730,13 @@ def getsmallrowdata_db(columns,ids=[],debug=False):
             df =  pd.concat(data,axis=0)
         except ValueError:
             df = pd.DataFrame()
-    else:
+    elif len(ids)==1:
         try:
             df = pd.read_parquet(csvfilenames[0],columns=columns,engine='pyarrow')
         except (OSError,IndexError):
             df = pd.DataFrame()
+    else:
+        df = pd.DataFrame()
 
 
     return df
diff --git a/rowers/tasks.py b/rowers/tasks.py
index ab2c9261..e812a363 100644
--- a/rowers/tasks.py
+++ b/rowers/tasks.py
@@ -1754,15 +1754,15 @@ def handle_updatefitnessmetric(user_id,mode,workoutids,debug=False,
 def handle_updatecp(rower_id,workoutids,debug=False,table='cpdata',**kwargs):
     columns = ['power','workoutid','time']
     df = getsmallrowdata_db(columns,ids=workoutids,debug=debug)
-    dfgrouped = df.groupby(['workoutid'])
 
-    if not df.empty:
-        maxt = 1.05*df['time'].max()/1000.
-    else:
-        maxt = 1000.
+    if df.empty:
+        return 0
+
+    maxt = 1.05*df['time'].max()/1000.
 
     logarr = datautils.getlogarr(maxt)
 
+    dfgrouped = df.groupby(['workoutid'])
 
     delta,cpvalue,avgpower = datautils.getcp(dfgrouped,logarr)