diff --git a/rowers/dataprep.py b/rowers/dataprep.py
index c1e4684e..efa2db7f 100644
--- a/rowers/dataprep.py
+++ b/rowers/dataprep.py
@@ -988,7 +988,7 @@ def testdata(time,distance,pace,spm):
 
 # Get data from DB for one workout (fetches all data). If data
 # is not in DB, read from CSV file (and create DB entry)
-def getrowdata_db(id=0,doclean=False):
+def getrowdata_db(id=0,doclean=False,convertnewtons=True):
     data = read_df_sql(id)
     data['x_right'] = data['x_right']/1.0e6
 
@@ -1034,7 +1034,7 @@ 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):
+def getrowdata(id=0,convertnewtons=True):
 
     # check if valid ID exists (workout exists)
     row = Workout.objects.get(id=id)
@@ -1086,7 +1086,7 @@ def prepmultipledata(ids,verbose=False):
 
 # Read a set of columns for a set of workout ids, returns data as a
 # pandas dataframe
-def read_cols_df_sql(ids,columns):
+def read_cols_df_sql(ids,columns,convertnewtons=True):
     # drop columns that are not in offical list
 #    axx = [ax[0] for ax in axes]
     axx = [f.name for f in StrokeData._meta.get_fields()]
@@ -1124,22 +1124,23 @@ def read_cols_df_sql(ids,columns):
     df = pd.read_sql_query(query,engine)
 
     df = df.fillna(value=0)
-    
-    try:
-        df['peakforce'] = df['peakforce']*lbstoN
-    except KeyError:
-        pass
 
-    try:
-        df['averageforce'] = df['averageforce']*lbstoN
-    except KeyError:
-        pass
+    if convertnewtons:
+        try:
+            df['peakforce'] = df['peakforce']*lbstoN
+        except KeyError:
+            pass
+
+        try:
+            df['averageforce'] = df['averageforce']*lbstoN
+        except KeyError:
+            pass
 
     engine.dispose()
     return df
         
 # Read stroke data from the DB for a Workout ID. Returns a pandas dataframe
-def read_df_sql(id):
+def read_df_sql(id,convertnewtons=True):
     engine = create_engine(database_url, echo=False)
 
     df = pd.read_sql_query(sa.text('SELECT * FROM strokedata WHERE workoutid={id}'.format(
@@ -1147,21 +1148,22 @@ def read_df_sql(id):
 
     engine.dispose()
     df = df.fillna(value=0)
-    try:
-        df['peakforce'] = df['peakforce']*lbstoN
-    except KeyError:
-        pass
+    if convertnewtons:
+        try:
+            df['peakforce'] = df['peakforce']*lbstoN
+        except KeyError:
+            pass
 
-    try:
-        df['averageforce'] = df['averageforce']*lbstoN
-    except KeyError:
-        pass
+        try:
+            df['averageforce'] = df['averageforce']*lbstoN
+        except KeyError:
+            pass
 
     return df
 
 # Get the necessary data from the strokedata table in the DB.
 # For the flex plot
-def smalldataprep(therows,xparam,yparam1,yparam2):
+def smalldataprep(therows,xparam,yparam1,yparam2,convertnewtons=True):
     df = pd.DataFrame()
     if yparam2 == 'None':
         yparam2 = 'power'
@@ -1198,15 +1200,16 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
             except IOError:
                 pass
 
-    try:
-        df['peakforce'] = df['peakforce']*lbstoN
-    except KeyError:
-        pass
+    if convertnewtons:
+        try:
+            df['peakforce'] = df['peakforce']*lbstoN
+        except KeyError:
+            pass
 
-    try:
-        df['averageforce'] = df['averageforce']*lbstoN
-    except KeyError:
-        pass
+        try:
+            df['averageforce'] = df['averageforce']*lbstoN
+        except KeyError:
+            pass
     
     return df
 
@@ -1266,8 +1269,23 @@ def datafusion(id1,id2,columns,offset):
     
     return df
 
+def fix_newtons(id=0):
+    # rowdata,row = getrowdata_db(id=id,doclean=False,convertnewtons=False)
+    rowdata = getsmallrowdata_db(['peakforce'],ids=[id],doclean=False)
+    try:
+        avgforce = rowdata['averageforce']
+        peakforce = rowdata['peakforce']
+        if peakforce.mean() > 3000:
+            w = Workout.objects.get(id=id)
+            print "fixing ",id
+            rowdata = rdata(w.csvfilename)
+            if rowdata and len(rowdata.df):
+                update_strokedata(w.id,rowdata.df)
+    except KeyError:
+        pass
+
 def add_efficiency(id=0):
-    rowdata,row = getrowdata_db(id=id,doclean=False)
+    rowdata,row = getrowdata_db(id=id,doclean=False,convertnewtons=False)
     power = rowdata['power']
     pace = rowdata['pace']/1.0e3
     velo = 500./pace