g

app.py

@@ -18,13 +18,13 @@ from sklearn.preprocessing import OneHotEncoder
 def greet_o(name, str2):
     return "Hello " + name + "!!" + " str2=" + str2
 
-def greet(name, str2):
+def greet(name, sex_num):
     user_df = {}
 
     # Get user input for numerical columns
     user_df['age'] = 22.0
     user_df['status'] = 1.0
-    user_df['sex'] = 0.0
+    user_df['sex'] = 0.0 + sex_num
     user_df['height'] = 60.0
     user_df['smokes'] = 1.0
     user_df['new_languages'] = 2.0
@@ -58,7 +58,7 @@ def greet(name, str2):
     suggested_name = recommendOne(user_df)
 
     #return "Hello " + name + "!!" + " str2=" + str2
-    return "Hello " + suggested_name + "!!" + " str2=" + str2
+    return suggested_name
 
 # reading dataset using panda
 tinder_df = pd.read_csv("tinder_data.csv")