Update app.py

app.py

@@ -26,17 +26,21 @@ def read(file,dep,ord):
     for col in df.columns.values:
         if str(df.dtypes[col]) == 'bool' or str(df.dtypes[col]) == 'object':
             cat.append(col)
+    if ord == "":
+        ord = list()
+    else:
+        ord = ord.split(',')
+    ord.append(dep)
     nom = list(set(cat).difference(set(ord)))
+    le = LabelEncoder()
     new_df = df.dropna(axis=0)
-    if str(ord) != "":
-        ord = ord.split(',')
-        le = LabelEncoder()
-        new_df[ord] = new_df[ord].apply(lambda col: le.fit_transform(col))
-    else:
+    new_df[ord] = new_df[ord].apply(lambda col: le.fit_transform(col))
+    if len(nom) == 0:
         pass
-    ohe_df = pd.get_dummies(new_df[nom], drop_first=True)
-    new_df.drop(columns=nom, axis=1,inplace=True)
-    new_df = pd.concat([new_df,ohe_df],axis=1)
+    else:
+        ohe_df = pd.get_dummies(new_df[nom], drop_first=True)
+        new_df.drop(columns=nom, axis=1,inplace=True)
+        new_df = pd.concat([new_df,ohe_df],axis=1)
     if dep_type == 'bool' or dep_type == 'object':
         text = "classification"
         result = classification(new_df,dep)