def __init__(self, data, target=None,
*args, **kwargs):
if data is None and target is None:
msg = '{0} must have either data or target'
raise ValueError(msg.format(self.__class__.__name__))
elif data is None and not is_list_like(target):
msg = 'target must be list-like when data is None'
raise ValueError(msg)
data, target = skaccessors._maybe_sklearn_data(data, target)
data, target = smaccessors._maybe_statsmodels_data(data, target)
# retrieve target_name
if isinstance(data, ModelFrame):
target_name = data.target_name
data, target = self._maybe_convert_data(data, target, *args, **kwargs)
if target is not None and not is_list_like(target):
if target in data.columns:
target_name = target
df = data
else:
msg = "Specified target '{0}' is not included in data"
raise ValueError(msg.format(target))
self._target_name = target_name
else:
df, target = self._concat_target(data, target)
if isinstance(target, pd.Series):
self._target_name = target.name
elif isinstance(target, pd.DataFrame):
if len(target.columns) > 1:
self._target_name = target.columns
else:
self._target_name = target.columns[0]
else:
# target may be None
self._target_name = self._TARGET_NAME
pd.DataFrame.__init__(self, df)
def __init__(self, data, target=None,
*args, **kwargs):
if data is None and target is None:
msg = '{0} must have either data or target'
raise ValueError(msg.format(self.__class__.__name__))
elif data is None and not is_list_like(target):
msg = 'target must be list-like when data is None'
raise ValueError(msg)
data, target = skaccessors._maybe_sklearn_data(data, target)
data, target = smaccessors._maybe_statsmodels_data(data, target)
# retrieve target_name
if isinstance(data, ModelFrame):
target_name = data.target_name
data, target = self._maybe_convert_data(data, target, *args, **kwargs)
if target is not None and not is_list_like(target):
if target in data.columns:
target_name = target
df = data
else:
msg = "Specified target '{0}' is not included in data"
raise ValueError(msg.format(target))
self._target_name = target_name
else:
df, target = self._concat_target(data, target)
if isinstance(target, pd.Series):
self._target_name = target.name
elif isinstance(target, pd.DataFrame):
if len(target.columns) > 1:
self._target_name = target.columns
else:
self._target_name = target.columns[0]
else:
# target may be None
self._target_name = self._TARGET_NAME
pd.DataFrame.__init__(self, df)