Update pages/1_Data_Card_and_Data_collection.py

pages/1_Data_Card_and_Data_collection.py

@@ -4,10 +4,10 @@ import streamlit as st
 from io import StringIO
 
 # Persistent file path for the dataset
-DATA_FILE_PATH = "consumer_electronics_sales_data.csv"
+DATA_FILE_PATH = "customer-churn-prediction.csv"
 
 # Page Title
-st.markdown("<h1 style='text-align:center; color:white;'>Electronics Sales Data Set</h1>", unsafe_allow_html=True)
+st.markdown("<h1 style='text-align:center; color:white;'>customer-churn-prediction Data Set</h1>", unsafe_allow_html=True)
 
 # Function to load the dataset from the disk
 def load_dataset():
@@ -55,15 +55,17 @@ if df is not None:
 
 | **Feature**              | **Description**                                                    | **Example**                  |
 |-------------------------|--------------------------------------------------------------------|------------------------------|
-| **ProductID**            | Unique identifier for each product.                                | 12345                        |
-| **ProductCategory**      | Category of the consumer electronics product.                      | Smartphones, Laptops         |
-| **ProductBrand**         | Brand of the product.                                              | Apple, Samsung               |
-| **ProductPrice**         | Price of the product (in dollars).                                 | 999.99                       |
-| **CustomerAge**          | Age of the customer.                                               | 35                           |
-| **CustomerGender**       | Gender of the customer (0 - Male, 1 - Female).                     | 1                            |
-| **PurchaseFrequency**    | Average number of purchases per year.                              | 3                            |
-| **CustomerSatisfaction** | Customer satisfaction rating (1 - 5).                              | 4                            |
-| **PurchaseIntent**       | Target variable: Intent to purchase (classification target).       | 0 (No), 1 (Yes)              |
+| **creditscore** 	      | Credit score of the customer, typically ranging from 300 to 850.   | 750
+| **geography**           | Country or region of the customer.	                               | France, Germany, Spain
+| **gender**	          | Gender of the customer.	                                           | Male, Female
+|**age**	              | Age of the customer.	                                           | 45 
+|**tenure**	              | Number of years the customer has been with the organization.	   | 5
+|**balance**	          | Account balance of the customer.                                   |125000.50
+|**numofproducts**	      | Number of products the customer is using with the company.	       | 2
+|**hascrcard**	          | Indicates whether the customer has a credit card                   |(1 - Yes, 0 - No).	1
+|**isactivemember**	      | Indicates whether the customer is an active member                 |(1 - Yes, 0 - No).	0
+|**estimatedsalary**	  |Annual estimated salary of the customer.	                           |70000.00
+|**exited Target variable**| Indicates if the customer has exited                              |(1 - Yes, 0 - No).	1
 ''')
 
     
@@ -72,7 +74,7 @@ else:
     st.info("No dataset found. Please upload a CSV file.")
 
 # Define the URL of the background image (use your own image URL)
-background_image_url = "https://cdn-uploads.huggingface.co/production/uploads/67445925102349e867c92342/ssf43ThS1EbxpS-5uxhcF.jpeg"
+background_image_url = "https://cdn-uploads.huggingface.co/production/uploads/67441c51a784a9d15cb12871/xpoN_mbctlrQAgRU06EPt.jpeg"
 
 # Apply custom CSS for the background image and overlay
 st.markdown(
@@ -111,5 +113,4 @@ st.markdown(
 if st.button("Previous ⏮️"):
     st.switch_page("pages/0_Problem-Statement_and_Aim.py")
 if st.button("Next ⏭️"):
-    st.switch_page("pages/2_Data_CLeaning_and_Preprocessing.py")
-    
+    st.switch_page("pages/2_Data_CLeaning_and_Preprocessing.py")