The HydroShare Jupyterhub Notebook Server is an environment designed provide added value to existing HydroShare resources via interactive computational notebooks.
I'm trying to run a JupyterNotebook on the CUAHSI JupyterHub the resource is here . The version of Pandas and Ulmo do not work together I get a warning:
/opt/conda/envs/python2/lib/python2.7/site-packages/ulmo/twc/kbdi/core.py:20: FutureWarning: pandas.tslib is deprecated and will be removed in a future version. You can access Timestamp as pandas.Timestamp CSV_SWITCHOVER = pandas.tslib.Timestamp('2016-10-01')
and an error:
`AttributeErrorTraceback (most recent call last)
<ipython-input-4-b758f7901a7d> in <module>()
3 # read daily mean discharge data from cache (statistics code 00003)
4 #Rio Sabana
----> 5 data = nwis.get_site_data('50067000',start='2017-09-01', end='2017-09-30') #, parameter_code='00060:00003')['00060:00003']
6
7 # print(data['value'])
/opt/conda/envs/python2/lib/python2.7/site-packages/ulmo/usgs/nwis/core.pyc in get_site_data(site_code, service, parameter_code, statistic_code, start, end, period, modified_since, input_file, methods, **kwargs)
250 datetime_formatter = isodate.datetime_isoformat
251 if start is not None:
--> 252 start_datetime = util.convert_datetime(start)
253 url_params['startDT'] = datetime_formatter(start_datetime)
254 if end is not None:
/opt/conda/envs/python2/lib/python2.7/site-packages/ulmo/util/misc.pyc in convert_datetime(datetime)
50 datetime-like object (datetime.date, datetime.datetime, or pandas.Timestamp)
51 """
---> 52 return pandas.Timestamp(datetime).to_datetime()
53
54
AttributeError: 'Timestamp' object has no attribute 'to_datetime'`
From: https://github.com/hydroshare/hydroshare/issues/2877
@miguelcleon writes:
I'm trying to run a JupyterNotebook on the CUAHSI JupyterHub the resource is here . The version of Pandas and Ulmo do not work together I get a warning:
/opt/conda/envs/python2/lib/python2.7/site-packages/ulmo/twc/kbdi/core.py:20: FutureWarning: pandas.tslib is deprecated and will be removed in a future version. You can access Timestamp as pandas.Timestamp CSV_SWITCHOVER = pandas.tslib.Timestamp('2016-10-01')
and an error: