diff --git a/pipeline.py b/pipeline.py
index 8d35cd8..00bb80c 100644
--- a/pipeline.py
+++ b/pipeline.py
@@ -166,7 +166,9 @@ class Components :
 		:param values	array of values to be approximated
 		"""
 		if values.dtype in [int,float] :
-			r = np.random.dirichlet(values)
+			#
+			# @TODO: create bins?
+			r = np.random.dirichlet(values+.001) #-- dirichlet doesn't work on values with zeros
 			x = []
 			_type = values.dtype
 			for index in np.arange(values.size) :
@@ -222,7 +224,7 @@ class Components :
 				dtype = str
 				name = _item['name']
 				novalue = -1
-				if _item['type'] == 'INTEGER' :
+				if _item['type'] in ['INTEGER','NUMERIC']:
 					dtype = np.int64
 					
 				elif _item['type'] == 'FLOAT' :
@@ -296,11 +298,11 @@ class Components :
 				#	- The original dataset has all the fields except those that need to be synthesized
 				#
 				
-				_df = _df[list(set(_df.columns)  - set(skip_columns))]
+				_df = _df[list(set(_df.columns)  - set(skip_columns))].copy()
 				if x_cols :
 					for _col in x_cols :
 						if real_df[_col].unique().size > 0 :
-							_df[_col] = self.approximate(real_df[_col].fillna(-1))
+							_df[_col] = self.approximate(real_df[_col])
 						else:
 							_df[_col] = -1