diff --git a/python/examples/multichannel.py b/python/examples/multichannel.py
index 8d0d7d2..2a39de1 100644
--- a/python/examples/multichannel.py
+++ b/python/examples/multichannel.py
@@ -1,24 +1,43 @@
 
 import IMCtermite
 import pandas
+import datetime
+
+def add_trigger_time(trigger_time, add_time) :
+    trgts = datetime.datetime.strptime(trigger_time,'%Y-%m-%dT%H:%M:%S')
+    dt = datetime.timedelta(seconds=add_time)
+    return (trgts + dt).strftime('%Y-%m-%dT%H:%M:%S:%f')
 
 if __name__ == "__main__" :
 
+    # read file and extract data
     imctm = IMCtermite.imctermite(b"Measurement.raw")
-
     chns = imctm.get_channels(True)
-
-    df = pandas.DataFrame()
     
-    xcol = "time ["+chns[0]['xunit']+"]"    
-    df[xcol] = pandas.Series(chns[0]['xdata'])
+    # prepare abscissa
+    xcol = "time ["+chns[0]['xunit']+"]"
+    #xcol = "timestamp"
+    xsts = [add_trigger_time(chns[0]['trigger-time'],tm) for tm in chns[0]['xdata']]
 
-    for idx,chn in enumerate(chns) :
+    # sort channels
+    chnnms = sorted([chn['name'] for chn in chns], reverse=False)
+    chnsdict = {}
+    for chn in chns :
+        chnsdict[chn['name']] = chn
+
+    # construct dataframe
+    df = pandas.DataFrame()
+    df[xcol] = pandas.Series(chns[0]['xdata'])
+    #df[xcol] = pandas.Series(xsts)
+    #for idx,chn in enumerate(chns) :
+    for chnnm in chnnms :
+        chn = chnsdict[chnnm]
         #xcol = (chn['xname'] if chn['xname'] != '' else "x_"+str(idx))+" ["+chn['xunit']+"]"
         #df[xcol] = pandas.Series(chn['xdata'])
         ycol = chn['yname']+" ["+chn['yunit']+"]"
         df[ycol] = pandas.Series(chn['ydata'])
 
+    # show entire dataframe and write file
     print(df)
     df.to_csv("Measurement.csv",header=True,sep='\t',index=False)