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pipeline.py
14
pipeline.py
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@ -231,7 +231,7 @@ class Components :
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if 'ignore' in args and 'columns' in args['ignore'] :
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_cols = self.get_ignore(data=df,columns=args['ignore']['columns'])
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args['data'] = df[ list(set(df.columns)- set(_cols))]
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args['data'] = args['data'][ list(set(df.columns)- set(_cols))]
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#
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# We need to remove the continuous columns from the data-frame
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# @TODO: Abstract this !!
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@ -267,12 +267,6 @@ class Components :
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# for _name in _df.columns:
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# if _name in name:
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# skip_columns.append(_name)
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if x_cols :
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for _col in x_cols :
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if df[_col].unique().size > 0 :
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_df[_col] = self.approximate(df[_col].fillna(-1))
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else:
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_df[_col] = -1
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#
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# We perform a series of set operations to insure that the following conditions are met:
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# - the synthetic dataset only has fields that need to be synthesized
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@ -284,6 +278,12 @@ class Components :
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if set(df.columns) & set(_df.columns) :
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_columns = set(df.columns) - set(_df.columns)
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df = df[_columns]
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if x_cols :
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for _col in x_cols :
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if df[_col].unique().size > 0 :
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_df[_col] = self.approximate(df[_col].fillna(-1))
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else:
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_df[_col] = -1
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#
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# Let us merge the dataset here and and have a comprehensive dataset
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