gistfile1.txt

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/preprocessing/label.py:111: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
  y = column_or_1d(y, warn=True)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-12-1c13669bcaa5> in <module>()
      5 
      6 pipeline = (trans(LabelEncoder(), in_cols=['class']) + trans(None, ['source', 'x','y','z'])) | (trans(StandardScaler(), in_cols=['x','y','z']) + trans(None, ['source', 'class']))
----> 7 df_scaled = pipeline.fit_transform(df)

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/pipeline.py in fit_transform(self, X, y, **fit_params)
    281         Xt, fit_params = self._fit(X, y, **fit_params)
    282         if hasattr(last_step, 'fit_transform'):
--> 283             return last_step.fit_transform(Xt, y, **fit_params)
    284         elif last_step is None:
    285             return Xt

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/ibex/_base.py in fit_transform(self, X, y, **fit_params)
    445 
    446         Xts = joblib.Parallel(n_jobs=self.n_jobs)(
--> 447             joblib.delayed(_fit_transform)(trans, weight, X, y, **fit_params) for _, trans, weight in self._iter())
    448         return self.__concat(Xts)
    449 

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/parallel.py in __call__(self, iterable)
    777             # was dispatched. In particular this covers the edge
    778             # case of Parallel used with an exhausted iterator.
--> 779             while self.dispatch_one_batch(iterator):
    780                 self._iterating = True
    781             else:

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/parallel.py in dispatch_one_batch(self, iterator)
    623                 return False
    624             else:
--> 625                 self._dispatch(tasks)
    626                 return True
    627 

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/parallel.py in _dispatch(self, batch)
    586         dispatch_timestamp = time.time()
    587         cb = BatchCompletionCallBack(dispatch_timestamp, len(batch), self)
--> 588         job = self._backend.apply_async(batch, callback=cb)
    589         self._jobs.append(job)
    590 

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/_parallel_backends.py in apply_async(self, func, callback)
    109     def apply_async(self, func, callback=None):
    110         """Schedule a func to be run"""
--> 111         result = ImmediateResult(func)
    112         if callback:
    113             callback(result)

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/_parallel_backends.py in __init__(self, batch)
    330         # Don't delay the application, to avoid keeping the input
    331         # arguments in memory
--> 332         self.results = batch()
    333 
    334     def get(self):

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/parallel.py in __call__(self)
    129 
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
    132 
    133     def __len__(self):

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/sklearn/externals/joblib/parallel.py in <listcomp>(.0)
    129 
    130     def __call__(self):
--> 131         return [func(*args, **kwargs) for func, args, kwargs in self.items]
    132 
    133     def __len__(self):

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/ibex/_base.py in _fit_transform(transformer, weight, X, y, *args, **kwargs)
    355 def _fit_transform(transformer, weight, X, y, *args, **kwargs):
    356     if hasattr(transformer, 'fit_transform'):
--> 357         res = transformer.fit_transform(X, y, *args, **kwargs)
    358     else:
    359         res = transformer.fit(X, y, *args, **kwargs).transform(X)

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/ibex/_function_transformer.py in fit_transform(self, X, y)
    114 
    115         if in_cols is not None:
--> 116             Xt = Xt[in_cols]
    117 
    118         if self.func is None:

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/pandas/core/frame.py in __getitem__(self, key)
   2131         if isinstance(key, (Series, np.ndarray, Index, list)):
   2132             # either boolean or fancy integer index
-> 2133             return self._getitem_array(key)
   2134         elif isinstance(key, DataFrame):
   2135             return self._getitem_frame(key)

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/pandas/core/frame.py in _getitem_array(self, key)
   2175             return self._take(indexer, axis=0, convert=False)
   2176         else:
-> 2177             indexer = self.loc._convert_to_indexer(key, axis=1)
   2178             return self._take(indexer, axis=1, convert=True)
   2179 

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/pandas/core/indexing.py in _convert_to_indexer(self, obj, axis, is_setter)
   1248                 # if it cannot handle
   1249                 indexer, objarr = labels._convert_listlike_indexer(
-> 1250                     obj, kind=self.name)
   1251                 if indexer is not None:
   1252                     return indexer

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/pandas/core/indexes/multi.py in _convert_listlike_indexer(self, keyarr, kind)
   1804             mask = check == -1
   1805             if mask.any():
-> 1806                 raise KeyError('%s not in index' % keyarr[mask])
   1807 
   1808         return indexer, keyarr

KeyError: "['x' 'y' 'z'] not in index"