diff --git a/media/20161030-141212-annika2o.csv b/media/20161030-141212-annika2o.csv
index 369aa359..6aa8446b 100644
--- a/media/20161030-141212-annika2o.csv
+++ b/media/20161030-141212-annika2o.csv
@@ -1,1235 +1,1235 @@
-index, AverageDriveForce (lbs), Cadence (stokes/min), DriveLength (meters), DriveTime (ms), ElapsedTime (sec), HRCur (bpm), Horizontal (meters), PeakDriveForce (lbs), Power (watts), Stroke500mPace (sec/500m), StrokeDistance (meters), StrokeRecoveryTime (ms), lapIdx, latitude, longitude,TimeStamp (sec),cum_dist,originalvelo
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diff --git a/rowers/dataprep.py b/rowers/dataprep.py
new file mode 100644
index 00000000..2da4538f
--- /dev/null
+++ b/rowers/dataprep.py
@@ -0,0 +1,142 @@
+from rowers.models import Workout, User, Rower
+from rowingdata import rowingdata as rrdata
+
+from rowingdata import rower as rrower
+from rowingdata import main as rmain
+
+from pandas import DataFrame,Series
+
+import pandas as pd
+import numpy as np
+
+from scipy.signal import savgol_filter
+
+import datetime
+
+def niceformat(values):
+    out = []
+    for v in values:
+	formattedv = strfdelta(v)
+	out.append(formattedv)
+	
+    return out
+
+def strfdelta(tdelta):
+    try:
+	minutes,seconds = divmod(tdelta.seconds,60)
+	tenths = int(tdelta.microseconds/1e5)
+    except AttributeError:
+	minutes,seconds = divmod(tdelta.view(np.int64),60e9)
+	seconds,rest = divmod(seconds,1e9)
+	tenths = int(rest/1e8)
+    res = "{minutes:0>2}:{seconds:0>2}.{tenths:0>1}".format(
+	minutes=minutes,
+	seconds=seconds,
+	tenths=tenths,
+	)
+    
+    return res
+
+def nicepaceformat(values):
+    out = []
+    for v in values:
+	formattedv = strfdelta(v)
+	out.append(formattedv)
+	
+
+    return out
+
+def timedeltaconv(x):
+    dt = datetime.timedelta(seconds=x)
+
+    return dt
+
+def rdata(file,rower=rrower()):
+    try:
+	res = rrdata(file,rower=rower)
+    except IOError:
+	res = 0
+
+    return res
+
+def getrowdata(id=0):
+
+    # check if valid ID exists (workout exists)
+    row = Workout.objects.get(id=id)
+
+    f1 = row.csvfilename
+	
+    # get user
+
+    r = row.user
+    u = r.user
+
+    rr = rrower(hrmax=r.max,hrut2=r.ut2,
+		hrut1=r.ut1,hrat=r.at,
+		hrtr=r.tr,hran=r.an)
+
+    rowdata = rdata(f1,rower=rr)
+
+    return rowdata,row
+
+def dataprep(rowdatadf):
+    rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
+    t = rowdatadf.ix[:,'TimeStamp (sec)']
+    t = pd.Series(t-rowdatadf.ix[0,'TimeStamp (sec)'])
+
+    row_index = rowdatadf.ix[:,' Stroke500mPace (sec/500m)'] > 3000
+    rowdatadf.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
+
+    p = rowdatadf.ix[:,' Stroke500mPace (sec/500m)']
+    hr = rowdatadf.ix[:,' HRCur (bpm)']
+    spm = rowdatadf.ix[:,' Cadence (stokes/min)']
+    cumdist = rowdatadf.ix[:,'cum_dist']
+
+    power = rowdatadf.ix[:,' Power (watts)']
+    averageforce = rowdatadf.ix[:,' AverageDriveForce (lbs)']
+    drivelength = rowdatadf.ix[:,' DriveLength (meters)']
+
+
+    peakforce = rowdatadf.ix[:,' PeakDriveForce (lbs)']
+
+
+    f = rowdatadf['TimeStamp (sec)'].diff().mean()
+    windowsize = 2*(int(10./(f)))+1
+    if windowsize <= 3:
+	windowsize = 5
+
+    if windowsize > 3:
+	spm = savgol_filter(spm,windowsize,3)
+	hr = savgol_filter(hr,windowsize,3)
+	drivelength = savgol_filter(drivelength,windowsize,3)
+
+    t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
+
+    
+    p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
+
+
+    drivespeed = drivelength/rowdatadf[' DriveTime (ms)']*1.0e3
+    driveenergy = drivelength*averageforce*4.44822
+    distance = rowdatadf.ix[:,'cum_dist']
+
+    data = DataFrame(
+	dict(
+	    time = t2,
+	    hr = hr,
+	    pace = p2,
+	    spm = spm,
+	    cumdist = cumdist,
+	    ftime = niceformat(t2),
+	    fpace = nicepaceformat(p2),
+	    driveenergy=driveenergy,
+	    power=power,
+	    averageforce=averageforce,
+	    drivelength=drivelength,
+	    peakforce=peakforce,
+	    distance=distance,
+	    drivespeed=drivespeed
+	    )
+	)
+
+    return data
diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py
index e8be7f27..8de6985c 100644
--- a/rowers/interactiveplots.py
+++ b/rowers/interactiveplots.py
@@ -4,8 +4,6 @@ from rowingdata import main as rmain
 from rowingdata import cumcpdata,histodata
 
 from rowingdata import rowingdata as rrdata
-from rowingdata import TCXParser,RowProParser,ErgDataParser
-from rowingdata import painsledDesktopParser,speedcoachParser,ErgStickParser
 
 from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc
 from bokeh.models import CustomJS,Slider
@@ -45,14 +43,8 @@ from scipy.signal import savgol_filter
 
 import stravastuff
 
-def rdata(file,rower=rrower()):
-    try:
-	res = rrdata(file,rower=rower)
-    except IOError:
-	res = 0
-
-    return res
-
+from rowers.dataprep import rdata
+import rowers.dataprep as dataprep
 
 def tailwind(bearing,vwind,winddir):
     """ Calculates head-on head/tailwind in direction of rowing
@@ -68,42 +60,9 @@ def tailwind(bearing,vwind,winddir):
     
     return vtail
 
-def niceformat(values):
-    out = []
-    for v in values:
-	formattedv = strfdelta(v)
-	out.append(formattedv)
-	
-    return out
 
-def strfdelta(tdelta):
-    minutes,seconds = divmod(tdelta.seconds,60)
-    tenths = int(tdelta.microseconds/1e5)
-    res = "{minutes:0>2}:{seconds:0>2}.{tenths:0>1}".format(
-	minutes=minutes,
-	seconds=seconds,
-	tenths=tenths,
-	)
-    
-    return res
-
-def nicepaceformat(values):
-    out = []
-    for v in values:
-	formattedv = strfdelta(v)
-	out.append(formattedv)
-	
-
-    return out
-
-def timedeltaconv(x):
-#    if x<=0 or x>1e9:
-#	x=0
-
-    dt = datetime.timedelta(seconds=x)
-
-    return dt
-    
+from rowers.dataprep import nicepaceformat,niceformat
+from rowers.dataprep import timedeltaconv    
 
 
 def interactive_histoall(theworkouts):
@@ -535,66 +494,14 @@ def interactive_chart(id=0,promember=0):
     else:
 	TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
 
-    # check if valid ID exists (workout exists)
-    row = Workout.objects.get(id=id)
-    # g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime")
-
-    f1 = row.csvfilename
-	
-    # create interactive plot
-   # get user
-    # u = User.objects.get(id=row.user.id)
-    r = row.user
-    u = r.user
-
-
-
-    rr = rrower(hrmax=r.max,hrut2=r.ut2,
-		hrut1=r.ut1,hrat=r.at,
-		hrtr=r.tr,hran=r.an)
-
-    rowdata = rdata(f1,rower=rr)
+    rowdata,row = dataprep.getrowdata(id=id)
     if rowdata == 0:
 	return "","CSV Data File Not Found"
 
-    t = rowdata.df.ix[:,'TimeStamp (sec)']
-    t = pd.Series(t-rowdata.df.ix[0,'TimeStamp (sec)'])
-
-    row_index = rowdata.df.ix[:,' Stroke500mPace (sec/500m)'] > 3000
-    rowdata.df.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
-
-    p = rowdata.df.ix[:,' Stroke500mPace (sec/500m)']
-    hr = rowdata.df.ix[:,' HRCur (bpm)']
-    spm = rowdata.df.ix[:,' Cadence (stokes/min)']
-    cumdist = rowdata.df.ix[:,'cum_dist']
-
-    f = rowdata.df['TimeStamp (sec)'].diff().mean()
-    windowsize = 2*(int(10./(f)))+1
-    if windowsize <= 3:
-	windowsize = 5
-
-    if windowsize > 3:
-	spm = savgol_filter(spm,windowsize,3)
-
-
-
-    t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
-
-    
-    p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
+    datadf = dataprep.dataprep(rowdata.df)
 
     source = ColumnDataSource(
-	data = dict(
-	    x=t2,
-	    y=hr,
-	    y2=p2,
-	    tf = niceformat(t2),
-	    pace = nicepaceformat(p2),
-	    heartrate = hr,
-	    spm=spm,
-	    spmc=np.rint(10*spm)/10.,
-	    cumdist=cumdist,
-	    )
+	datadf
 	)
 
  
@@ -605,7 +512,7 @@ def interactive_chart(id=0,promember=0):
 		  toolbar_sticky=False,
 		  tools=TOOLS)
 
-    plot.line('x','y2',source=source,legend="Pace")
+    plot.line('time','pace',source=source,legend="Pace")
     plot.title.text = row.name
     plot.title.text_font_size=value("1.0em")
     plot.xaxis.axis_label = "Time"
@@ -636,17 +543,17 @@ def interactive_chart(id=0,promember=0):
 
 
     hover.tooltips = OrderedDict([
-	('Time','@tf'),
-	('Pace','@pace'),
-	('HR','@heartrate'),
-	('SPM','@spmc{1.1}'),
+	('Time','@ftime'),
+	('Pace','@fpace'),
+	('HR','@hr'),
+	('SPM','@spm{1.1}'),
 	('Distance','@cumdist{1.1}'),
 	])
  
     hover.mode = 'mouse'
 
     plot.extra_y_ranges = {"hr": Range1d(start=100,end=200)}
-    plot.line('x','y',source=source,color="red",
+    plot.line('time','hr',source=source,color="red",
 	      y_range_name="hr", legend="Heart Rate")
     plot.add_layout(LinearAxis(y_range_name="hr",axis_label="HR"),'right')
 
@@ -672,19 +579,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 
     thedata = pd.concat(therows)
 
-    csvcolumns = {
-	'time': 'TimeStamp (sec)',
-	'distance': 'cum_dist',
-	'hr': ' HRCur (bpm)',
-	'spm': ' Cadence (stokes/min)',
-	'pace': ' Stroke500mPace (sec/500m)',
-	'power': ' Power (watts)',
-	'averageforce': ' AverageDriveForce (lbs)',
-	'drivelength': ' DriveLength (meters)',
-	'peakforce': ' PeakDriveForce (lbs)',
-	'driveenergy': 'driveenergy',
-	'drivespeed': 'drivespeed',
-	}
 
     axlabels = {
 	'time': 'Time',
@@ -729,47 +623,29 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 	}
     
 
-    thedata['driveenergy'] = thedata[' DriveLength (meters)']*thedata[' AverageDriveForce (lbs)']*4.44822
+    datadf = dataprep.dataprep(thedata)
+    #    thedata['driveenergy'] = thedata[' DriveLength (meters)']*thedata[' AverageDriveForce (lbs)']*4.44822
+    
 
     # throw out zeros from dataframe
-    thedata = thedata[thedata[csvcolumns[yparam1]] > 0] 
-    thedata = thedata[thedata[csvcolumns[xparam]] > 0] 
+    #thedata = thedata[thedata[csvcolumns[yparam1]] > 0] 
+    #thedata = thedata[thedata[csvcolumns[xparam]] > 0] 
+    datadf = datadf[datadf[yparam1] > 0] 
+    datadf = datadf[datadf[xparam] > 0] 
     if yparam2 != 'None':
-	thedata = thedata[thedata[csvcolumns[yparam2]] > 0]
-
+	#thedata = thedata[thedata[csvcolumns[yparam2]] > 0]
+	datadf = datadf[thedata[yparam2] > 0]
+	
     # check if dataframe not empty
-    if thedata.empty:
+    if datadf.empty:
 	return ['','<p>No non-zero data in selection</p>','','']
 
-    spm = thedata.ix[:,csvcolumns['spm']]
+ 
+    x1 = datadf.ix[:,xparam]
 
-    f = thedata['TimeStamp (sec)'].diff().mean()
-    if not np.isnan(f):
-	windowsize = 2*(int(10./(f)))+1
-    else:
-	windowsize = 5
-	
-    if windowsize <= 3:
-	windowsize = 5
-
-    if windowsize > 3:
-	spm = savgol_filter(spm,windowsize,3)
-
-    thedata[' Cadence (stokes/min)'] = spm
-
-    drivelength = thedata[' DriveLength (meters)']
-    if windowsize > 3:
-	drivelength = savgol_filter(drivelength,windowsize,3)
-    thedata[' DriveLength (meters)'] = drivelength
-    
-    thedata['drivespeed'] = drivelength/thedata[' DriveTime (ms)']*1.0e3
-
-
-    x1 = thedata.ix[:,csvcolumns[xparam]]
-
-    y1 = thedata.ix[:,csvcolumns[yparam1]]
+    y1 = datadf.ix[:,yparam1]
     if yparam2 != 'None':
-	y2 = thedata.ix[:,csvcolumns[yparam2]]
+	y2 = datadf.ix[:,yparam2]
     else:
 	y2 = y1
 
@@ -811,18 +687,14 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 	y1 = y1.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
 
 
-    time = thedata.ix[:,csvcolumns['time']]
-
-    hr = thedata.ix[:,csvcolumns['hr']]
-    if windowsize > 3:
-	hr = savgol_filter(hr,windowsize,3)
-
-
-    pace = thedata.ix[:,csvcolumns['pace']]
-
-    distance = thedata.ix[:,csvcolumns['distance']]
-
-    power = thedata.ix[:,csvcolumns['power']]
+    time = datadf.ix[:,'time']
+    hr = datadf.ix[:,'hr']
+    pace = datadf.ix[:,'pace']
+    distance = datadf.ix[:,'distance']
+    power = datadf.ix[:,'power']
+    ftime = datadf.ix[:,'ftime']
+    fpace = datadf.ix[:,'fpace']
+    spm = datadf.ix[:,'spm']
 
 
     # Add hover to this comma-separated string and see what changes
@@ -853,34 +725,25 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 	    x1=x1,
 	    y1=y1,
 	    y2=y2,
-	    time=niceformat(
-		time.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
-		),
-	    pace=nicepaceformat(
-		pace.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
-		),
+	    time=ftime,
+	    pace=fpace,
 	    hr = hr,
 	    spm = spm,
-	    spmc=np.rint(10*spm)/10.,
 	    distance=distance,
 	    power=power,
 	    )
 	)
 
+
     source2 = ColumnDataSource(
 	data = dict(
 	    x1=x1,
 	    y1=y1,
 	    y2=y2,
-	    time=niceformat(
-		time.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
-		),
-	    pace=nicepaceformat(
-		pace.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
-		),
+	    time=ftime,
+	    pace=fpace,
 	    hr = hr,
 	    spm = spm,
-	    spmc=np.rint(10*spm)/10.,
 	    distance=distance,
 	    power=power,
 	    )
@@ -947,7 +810,7 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 	('Time','@time'),
 	('Pace','@pace'),
 	('HR','@hr'),
-	('SPM','@spmc{1.1}'),
+	('SPM','@spm{1.1}'),
 	('Power','@power{int}'),
 	])
  
@@ -966,7 +829,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
        var time1 = data['time']
        var pace1 = data['pace']
        var hr1 = data['hr']
-       var spmc1 = data['spmc']
        var distance1 = data['distance']
        var power1 = data['power']
        
@@ -985,7 +847,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
        data2['time'] = []
        data2['pace'] = []
        data2['hr'] = []
-       data2['spmc'] = []
        data2['distance'] = []
        data2['power'] = []
        data2['x1mean'] = []
@@ -1005,7 +866,6 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
 		data2['time'].push(time1[i])
 		data2['pace'].push(pace1[i])
 		data2['hr'].push(hr1[i])
-		data2['spmc'].push(spmc1[i])
 		data2['distance'].push(distance1[i])
 		data2['power'].push(power1[i])
 
@@ -1129,20 +989,7 @@ def interactive_flex_chart2(id=0,promember=0,
 	'drivespeed':4,
 	}
     
-    # check if valid ID exists (workout exists)
-    row = Workout.objects.get(id=id)
-    # g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime")
-
-    f1 = row.csvfilename
-	
-    r = row.user
-    u = r.user
-
-    rr = rrower(hrmax=r.max,hrut2=r.ut2,
-		hrut1=r.ut1,hrat=r.at,
-		hrtr=r.tr,hran=r.an)
-
-    rowdata = rdata(f1,rower=rr)
+    rowdata,row = dataprep.getrowdata(id=id)
     if rowdata == 0:
 	return "","CSV Data File Not Found"
 
@@ -1521,22 +1368,7 @@ def interactive_flex_chart2(id=0,promember=0,
 
 def interactive_bar_chart(id=0,promember=0):
     # check if valid ID exists (workout exists)
-    row = Workout.objects.get(id=id)
-
-    f1 = row.csvfilename
-	
-    # create interactive plot
-    plot = Figure(plot_width=400,plot_height=300)
-    # get user
-    # u = User.objects.get(id=row.user.id)
-    r = row.user
-    u = r.user
-
-    rr = rrower(hrmax=r.max,hrut2=r.ut2,
-		hrut1=r.ut1,hrat=r.at,
-		hrtr=r.tr,hran=r.an)
-
-    rowdata = rdata(f1,rower=rr)
+    rowdata,row = dataprep.getrowdata(id=id)
     if rowdata == 0:
 	return "","CSV Data File Not Found"
     
@@ -1716,18 +1548,11 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
 
     
     # check if valid ID exists (workout exists)
-    row1 = Workout.objects.get(id=id1)
-    row2 = Workout.objects.get(id=id2)
-
-    f1 = row1.csvfilename
-    f2 = row2.csvfilename
-	
-
-    rowdata1 = rdata(f1)
+    rowdata1,row1 = dataprep.getrowdata(id=id1)
+    rowdata2,row2 = dataprep.getrowdata(id=id1)
     if rowdata1 == 0:
 	return "","CSV Data File Not Found"
     
-    rowdata2 = rdata(f2)
     if rowdata2 == 0:
 	return "","CSV Data File Not Found"
 
@@ -1924,17 +1749,7 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
 
 def interactive_otw_advanced_pace_chart(id=0,promember=0):
     # check if valid ID exists (workout exists)
-    row = Workout.objects.get(id=id)
-
-    f1 = row.csvfilename
-	
-
-    # get user
-    # u = User.objects.get(id=row.user.id)
-    r = row.user
-    u = r.user
-
-    rowdata = rdata(f1)
+    rowdata,row = dataprep.getrowdata(id=id)
     if rowdata == 0:
 	return "","CSV Data File Not Found"