Update app_utils.py

app_utils.py

@@ -40,7 +40,28 @@ def init_model():
         st.error(f"Error occurred during model initialization: {e}")
 
 
-# Function to store the user data to a CSV file
+# # Function to store the user data to a CSV file
+# def save_user_data(first_name, last_name, email, phone):
+#     """
+#     Function to store the user data to a CSV file
+
+#     :param first_name: str - First name of the user
+#     :param last_name: str - Last name of the user
+#     :param email: str - Email of the user
+#     :param phone: str - Phone number of the user
+#     :return: None
+#     """
+#     csv_file = Path("./user_data/user_data.csv")
+#     # Check if the file exists and create a DataFrame accordingly
+#     if csv_file.exists():
+#         df = pd.read_csv(csv_file)
+#     else:
+#         df = pd.DataFrame(columns=["First Name", "Last Name", "Email", "Phone Number"])
+#     new_data = {"First Name": first_name, "Last Name": last_name, "Email": email, "Phone Number": phone}
+#     df = df.append(new_data, ignore_index=True)
+#     df.to_csv(csv_file, index=False)
+#     return None
+
 def save_user_data(first_name, last_name, email, phone):
     """
     Function to store the user data to a CSV file
@@ -56,9 +77,15 @@ def save_user_data(first_name, last_name, email, phone):
     if csv_file.exists():
         df = pd.read_csv(csv_file)
     else:
-        df = pd.DataFrame(columns=["First Name", "Last Name", "Email", "Phone Number"])
-    new_data = {"First Name": first_name, "Last Name": last_name, "Email": email, "Phone Number": phone}
-    df = df.append(new_data, ignore_index=True)
+        df = pd.DataFrame(columns=["First Name", "Last Name",
+                                   "Email", "Phone Number"])
+
+    # Add and save new user data.
+    new_data = pd.DataFrame({"First Name": [first_name],
+                             "Last Name": [last_name],
+                             "Email": [email],
+                             "Phone Number": [phone]})
+    df = pd.concat([df, new_data], ignore_index=True)
     df.to_csv(csv_file, index=False)
     return None