..

pipeline.py

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