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@ -306,7 +306,7 @@ class Shuffle(Generator):
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This is a method that will yield data with low utility
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"""
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def __init__(self,**_args):
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super().__init__(self)
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super().__init__(**_args)
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def run(self):
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@ -315,7 +315,8 @@ class Shuffle(Generator):
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np.random.shuffle(_index)
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_iocolumns = self.info['columns']
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_ocolumns = list(set(self._df.columns) - set(_iocolumns) )
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_iodf = pd.DataFrame(self._df[_ocolumns],self._df.loc[_index][_iocolumns],index=np.arange(self._df.shape[0]))
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# _iodf = pd.DataFrame(self._df[_ocolumns],self._df.loc[_index][_iocolumns],index=np.arange(_index.size))
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_iodf = pd.DataFrame(self._df[_iocolumns],index = np.arange(_index.size))
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self._df = self._df[_ocolumns].join(_iodf)
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@ -336,8 +337,8 @@ class factory :
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:param autopilot will generate output automatically
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:param batch (default 2k) size of the batch
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"""
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if _args['apply'] == 'shuffe' :
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if _args['apply'] == 'shuffle' :
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return Shuffle(**_args)
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elif _args['apply'] == 'generate' :
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return Generator(**_args)
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