Index: wflow-py/Scripts/e2o-getfromwci.py
===================================================================
diff -u -r12ea40dc08628f654753679e0972e87b7bb12f7a -ra86cb51cd1731ce83f57e4b0b932a2a115b39712
--- wflow-py/Scripts/e2o-getfromwci.py	(.../e2o-getfromwci.py)	(revision 12ea40dc08628f654753679e0972e87b7bb12f7a)
+++ wflow-py/Scripts/e2o-getfromwci.py	(.../e2o-getfromwci.py)	(revision a86cb51cd1731ce83f57e4b0b932a2a115b39712)
@@ -1,6 +1,7 @@
 #!/usr/bin/env python
 # we need the netcdf4 library. This allows us to read netcdf from OpeNDAP or files
 import netCDF4
+import cftime
 import osgeo.gdal as gdal
 from osgeo.gdalconst import *
 
@@ -103,7 +104,7 @@
         lon = lon[lonidx]
         # Now get the time for the x-axis
         time = ncdataset.variables["time"]
-        timeObj = netCDF4.num2date(time[:], units=time.units, calendar=time.calendar)
+        timeObj = cftime.num2date(time[:], units=time.units, calendar=time.calendar)
 
         # Now determine area P for each timestep and display in a graph
         # first  the mean per area lat, next average those also