Update data.py

data.py

@@ -1,39 +1,46 @@
-import json
-import pandas as pd
-
-#for adding bank name to the cards in the graph
-eligibility_df = pd.read_csv("cards_eligibility_updated.csv")
-card_to_bank = dict(zip(eligibility_df['Name'], eligibility_df['Bank']))
-
-# Loading credit card data
-df = pd.read_csv("credit_card_data_updated.csv")
-card_descriptions = dict(zip(df["name"], df["description"]))
-
-# Loading all 55 cards for comparison feature
-df_all_cards = pd.read_csv("credit_card_data_updated.csv") 
-all_card_names = df_all_cards["name"].tolist()
-all_card_lookup = dict(zip(df_all_cards["name"], df_all_cards["description"]))
-    
-with open('for_graph_construction_(expanded labels).json') as f:
-    card_feature_data = json.load(f)
-
-card_features_lookup = {
-    card['card_name']: set(card['features'])
-    for card in card_feature_data
-}
-
-
-#function for the chatbot functionality
-eligibility_lookup = {}
-for _, row in eligibility_df.iterrows():
-    card_name = row["Name"].strip()
-    eligibility_info = f"""
-        - Bank: {row['Bank']}
-        - Age: {row['Minimum Age']} to {row['Maximum Age']}
-        - Minimum Income: {row['Minimum Income (LPA)']} LPA
-        - Minimum Credit Score: {row['Minimum Credit Score']}
-        - Joining Fee: ₹{row['Joining fee']}
-        - Annual Fee: ₹{row['Annual fee']}
-    """
-    eligibility_lookup[card_name] = eligibility_info.strip()
-    
+import json
+import pandas as pd
+
+#for adding bank name to the cards in the graph
+eligibility_df = pd.read_csv("cards_eligibility_updated.csv")
+card_to_bank = dict(zip(eligibility_df['Name'], eligibility_df['Bank']))
+
+# Loading credit card data
+df = pd.read_csv("credit_card_data_updated.csv")
+card_descriptions = dict(zip(df["name"], df["description"]))
+
+# Loading all 55 cards for comparison feature
+df_all_cards = pd.read_csv("credit_card_data_updated.csv") 
+all_card_names = df_all_cards["name"].tolist()
+all_card_lookup = dict(zip(df_all_cards["name"], df_all_cards["description"]))
+    
+with open('for_graph_construction_(expanded labels).json') as f:
+    card_feature_data = json.load(f)
+
+card_features_lookup = {
+    card['card_name']: set(card['features'])
+    for card in card_feature_data
+}
+
+
+#function for the chatbot functionality
+eligibility_lookup = {}
+for _, row in eligibility_df.iterrows():
+    card_name = row["Name"].strip()
+    eligibility_info = f"""
+        - Bank: {row['Bank']}
+        - Age: {row['Minimum Age']} to {row['Maximum Age']}
+        - Minimum Income: {row['Minimum Income (LPA)']} LPA
+        - Minimum Credit Score: {row['Minimum Credit Score']}
+        - Joining Fee: ₹{row['Joining fee']}
+        - Annual Fee: ₹{row['Annual fee']}
+    """
+    eligibility_lookup[card_name] = eligibility_info.strip()
+
+def get_all_features():
+    with driver.session() as session:
+        result = session.run("MATCH (f:Feature) RETURN f.name AS feature")
+        return [record["feature"] for record in result]
+
+features = get_all_features()
+