def to_frame(self, name=None):
# ported from pandas 0.16
from pandas_ml.core.frame import ModelFrame
if name is None:
df = ModelFrame(self)
else:
df = ModelFrame({name: self})
return df
def _wrap_transform(self, transformed, columns=None):
"""
Wrapper for transform methods
"""
if len(transformed.shape) == 2:
if util._is_1d_harray(transformed):
transformed = transformed.flatten()
else:
from pandas_ml.core.frame import ModelFrame
return ModelFrame(transformed, index=self.index)
return self._constructor(transformed, index=self.index, name=self.name)
def _wrap_results(self, results):
keys = []
values = []
for key, value in compat.iteritems(results):
keys.extend([key] * len(value))
values.append(value)
results = pd.concat(values, axis=0, ignore_index=False)
if isinstance(results, pd.Series):
results = ModelSeries(results)
# keys must be list
results = results.groupby(by=keys)
elif isinstance(results, pd.DataFrame):
results = ModelFrame(results)
# keys must be Series
results = results.groupby(by=pd.Series(keys))
else:
raise ValueError('Unknown type: {0}'.format(results.__class__.__name__))
return results
