Update pandas version (#21)

Update pandas version

ioos_tools/ioos.py

@@ -535,11 +535,11 @@ def _sanitize(name):
     """
     Examples
     --------
-    >>> _sanitize('ROMS/TOMS')
+    >>> _sanitize("ROMS/TOMS")
     'ROMS_TOMS'
-    >>> _sanitize('USEAST model')
+    >>> _sanitize("USEAST model")
     'USEAST_model'
-    >>> _sanitize('GG1SST, SST')
+    >>> _sanitize("GG1SST, SST")
     'GG1SST_SST'
 
     """
@@ -576,7 +576,7 @@ def get_model_name(url):
     return mod_name
 
 
-@timeout_decorator.timeout(20, use_signals=False)
+@timeout_decorator.timeout(40, use_signals=False)
 def is_station(url):
     from netCDF4 import Dataset
 
@@ -651,17 +651,15 @@ def load_ncs(config):
         else:
             model = os.path.splitext(os.path.split(fname)[-1])[0].split("-")[
                 -1
-            ]  # noqa
+            ]
             df = nc2df(fname, columns_name="station_code")
             # FIXME: Horrible work around duplicate times.
             if len(df.index.values) != len(np.unique(df.index.values)):
                 kw = {"subset": "index", "take_last": True}
                 df = df.reset_index().drop_duplicates(**kw).set_index("index")
             kw = {"method": "time", "limit": 2}
-            df = df.reindex(index).interpolate(**kw).ix[index]
+            df = df.reindex(index).interpolate(**kw).loc[index]
             dfs.update({model: df})
-    kw = {"orient": "items", "intersect": False}
-    dfs = pd.Panel.from_dict(dfs, **kw).swapaxes(0, 2)
     return dfs
 
 

ioos_tools/skill_score.py

@@ -79,9 +79,17 @@ def r2(x, y):
     return r2_score(x, y)
 
 
+def _get_df(dfs, station):
+    ret = {}
+    for k, v in dfs.items():
+        ret.update({k: v[station]})
+    return DataFrame.from_dict(ret)
+
+
 def apply_skill(dfs, function, remove_mean=True, filter_tides=False):
     skills = {}
-    for station, df in dfs.iteritems():
+    for station in dfs["OBS_DATA"].columns:
+        df = _get_df(dfs, station)
         if filter_tides:
             df = df.apply(low_pass)
         skill = {}
@@ -90,7 +98,8 @@ def apply_skill(dfs, function, remove_mean=True, filter_tides=False):
             # No observations.
             skills.update({station: np.NaN})
             continue
-        for model, y in df.iteritems():
+        for model in df.columns:
+            y = df[model]
             # No models.
             if y.isnull().all():
                 skills.update({station: np.NaN})

ioos_tools/tardis.py

@@ -28,7 +28,6 @@ def is_model(cube):
     Examples
     --------
     >>> import iris
-    >>> iris.FUTURE.netcdf_promote = True
     >>> url = "http://thredds.cencoos.org/thredds/dodsC/CENCOOS_CA_ROMS_FCST.nc"
     >>> cubes = iris.load_raw(url, 'sea_water_potential_temperature')
     >>> [is_model(cube) for cube in cubes]

requirements.txt

@@ -2,16 +2,17 @@ beautifulsoup4
 cftime
 folium
 iris
+jupyter
 matplotlib
 netcdf4
 numpy
 oceans
 owslib
-pandas>=0.20
+pandas>=0.25.1
 pytz
 requests
 retrying
 scikit-learn
 scipy
 timeout-decorator
-jupyter
+lxml