diff --git a/rowers/dataprep.py b/rowers/dataprep.py
index 93d26206..f5e7a775 100644
--- a/rowers/dataprep.py
+++ b/rowers/dataprep.py
@@ -1202,7 +1202,7 @@ def getsmallrowdata_db(columns,ids=[],doclean=True,workstrokesonly=True):
     return data
 
 # Fetch both the workout and the workout stroke data (from CSV file)
-def getrowdata(id=0,convertnewtons=True):
+def getrowdata(id=0):
 
     # check if valid ID exists (workout exists)
     row = Workout.objects.get(id=id)
@@ -1263,7 +1263,7 @@ def read_cols_df_sql(ids,columns,convertnewtons=True):
         if not c in axx:
             columns.remove(c)
     
-    columns = list(columns)+['distance','spm']
+    columns = list(columns)+['distance','spm','workoutid']
     columns = [x for x in columns if x != 'None']
     columns = list(set(columns))
     cls = ''
@@ -1297,14 +1297,14 @@ def read_cols_df_sql(ids,columns,convertnewtons=True):
         funits = ((w.id,w.forceunit) for w in Workout.objects.filter(id__in=ids))
         for id,u in funits:
             if u=='lbs':
-                mask = data['workoutid']==id
+                mask = df['workoutid']==id
                 df.loc[mask,'peakforce'] = data.loc[mask,'peakforce']*lbstoN
     if 'averageforce' in columns:
         funits = ((w.id,w.forceunit) for w in Workout.objects.filter(id__in=ids))
         for id,u in funits:
             if u=='lbs':
-                mask = data['workoutid']==id
-                df.loc[mask,'averageforce'] = data.loc[mask,'averageforce']*lbstoN
+                mask = df['workoutid']==id
+                df.loc[mask,'averageforce'] = df.loc[mask,'averageforce']*lbstoN
 
     engine.dispose()
     return df
@@ -1399,6 +1399,9 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
 
 # data fusion
 def datafusion(id1,id2,columns,offset):
+    workout1 = Workout.objects.get(id=id1)
+    workout2 = Workout.objects.get(id=id2)
+    
     df1,w1 = getrowdata_db(id=id1)
     df1 = df1.drop([#'cumdist',
                     'hr_ut2',
@@ -1412,7 +1415,7 @@ def datafusion(id1,id2,columns,offset):
                     'workoutid',
                     'id'],
                    1,errors='ignore')
-
+    
     # Add coordinates to DataFrame
     latitude,longitude = get_latlon(id1)
     
@@ -1421,6 +1424,18 @@ def datafusion(id1,id2,columns,offset):
             
 
     df2 = getsmallrowdata_db(['time']+columns,ids=[id2],doclean=False)
+
+    forceunit = 'N'
+    # set Force to same units
+    if 'averageforce' in columns or 'peakforce' in columns:
+        forceunit = workout2.forceunit
+        if workout1.forceunit == 'lbs' and workout2.forceunit == 'N':
+            df1['averageforce'] *= lbstoN
+            df1['peakforce'] *= lbstoN
+        if workout1.forceunit == 'N' and workout2.forceunit == 'lbs':
+            df1['averageforce'] /= lbstoN
+            df1['peakforce'] /= lbstoN
+    
     offsetmillisecs = offset.seconds*1000+offset.microseconds/1000.
     offsetmillisecs += offset.days*(3600*24*1000)
     df2['time'] = df2['time']+offsetmillisecs