new

resultview.py

@@ -39,7 +39,7 @@ def tenant_inference(similarity_matrix, requested_tenants,dataframe):
         similarity_tenant = similarity_matrix[requested_tenants].head(4).sort_values(ascending = False)
         
         final_tenants = similarity_tenant.index
-        tenant_features = dataframe.loc[final_tenants, ["Names", "Age", "Smoking", "Email"]]
+        tenant_features = dataframe.loc[final_tenants, ["names", "age", "smoking", "email"]]
         tenants_dict = {
             key : list(tenant_features[key]) for key in tenant_features.columns
         }

similarity.py

@@ -14,7 +14,7 @@ def data_preparing():
     )
     engine = create_engine(connection_string)
     original_dataframe = pd.read_sql("SELECT * FROM tenants", con=engine)
-    columns = ['Age', 'Worktimes', 'Schedules', 'Studies level', 'Pets', 'Cooking', 'Sport', 'Smoking', 'Organized']
+    columns = ['age', 'worktimes', 'schedules', 'studieslevel', 'pets', 'cooking', 'sport', 'smoking', 'organized']
     dataframe = original_dataframe[columns]
     return dataframe, original_dataframe
 

try.py

@@ -9,7 +9,7 @@ print(file.loc(0))
 
     
 from sqlalchemy import URL, create_engine
-
+import resultview as rv
 connection_string = URL.create(
     'postgresql',
     username='koyeb-adm',
@@ -17,9 +17,9 @@ connection_string = URL.create(
     host='ep-rough-fire-a27dp2i1.eu-central-1.pg.koyeb.app',
     database='koyebdb',
 )
-engine = create_engine(connection_string)
-df = pd.read_sql("SELECT * FROM tenants", con=engine)
-print(df)
-print(type(df))
+
+tenant_list = rv.algo_start(5)
+print(tenant_list)
+