bg fix : approximation

pipeline.py

@@ -307,8 +307,8 @@ class Components :
 
 							_df[_col] = self.approximate(real_df[_col])
 							_approx[_col] = {
-								"io":{"min":_df[_col].min(),"max":_df[_col].max(),"mean":_df[_col].mean(),"sd":_df[_col].values.std(),"missing": _df[_col].where(_df[_col] == -1).dropna().count(),"zeros":_df[_col].where(_df[_col] == 0).dropna().count()},
+								"io":{"min":_df[_col].min().astype(float),"max":_df[_col].max().astype(float),"mean":_df[_col].mean().astype(float),"sd":_df[_col].values.std().astype(float),"missing": _df[_col].where(_df[_col] == -1).dropna().count().astype(float),"zeros":_df[_col].where(_df[_col] == 0).dropna().count().astype(float)},
-								"real":{"min":real_df[_col].min(),"max":real_df[_col].max(),"mean":real_df[_col].mean(),"sd":real_df[_col].values.std(),"missing": real_df[_col].where(_df[_col] == -1).dropna().count(),"zeros":real_df[_col].where(_df[_col] == 0).dropna().count()}
+								"real":{"min":real_df[_col].min().astype(float),"max":real_df[_col].max().astype(float),"mean":real_df[_col].mean().astype(float),"sd":real_df[_col].values.std().astype(float),"missing": real_df[_col].where(_df[_col] == -1).dropna().count().astype(float),"zeros":real_df[_col].where(_df[_col] == 0).dropna().count().astype(float)}
 							}
 						else:
 							_df[_col] = -1