Update app.py

app.py

@@ -8,30 +8,20 @@ st.title('Sales Data Visualization App')
 # Display Sample Data Format
 st.subheader('Sample Data Format:')
 st.write("""
-The data should be in the following format with the listed columns:
-
-| Customer Name | Date       | City         | Country     | State       | Product Name   | Product Attribute 1 | Product Attribute 2 | Product Attribute 3 | Product Attribute 4 | Net Sales Value | Margin Amount | Cost  |
-|----------------|------------|--------------|-------------|-------------|-----------------|---------------------|---------------------|---------------------|---------------------|------------------|---------------|-------|
-| John Doe       | 2024-01-01 | New York     | USA         | NY          | Product A       | Attribute 1A         | Attribute 2A         | Attribute 3A         | Attribute 4A         | 1000             | 300           | 700   |
-| Jane Smith     | 2024-01-02 | Los Angeles  | USA         | CA          | Product B       | Attribute 1B         | Attribute 2B         | Attribute 3B         | Attribute 4B         | 1500             | 400           | 1100  |
-| Bob Johnson    | 2024-02-15 | Chicago      | USA         | IL          | Product A       | Attribute 1A         | Attribute 2A         | Attribute 3A         | Attribute 4A         | 1200             | 350           | 850   |
-| Alice Williams | 2024-03-10 | Miami        | USA         | FL          | Product C       | Attribute 1C         | Attribute 2C         | Attribute 3C         | Attribute 4C         | 2000             | 500           | 1500  |
-| Charlie Brown  | 2024-04-05 | Houston      | USA         | TX          | Product B       | Attribute 1B         | Attribute 2B         | Attribute 3B         | Attribute 4B         | 1800             | 450           | 1350  |
-
-### Description of Columns:
-- **Customer Name**: The name of the customer (e.g., John Doe).
-- **Date**: The date of the sale, formatted as `YYYY-MM-DD` (e.g., `2024-01-01`).
-- **City**: The city where the sale took place (e.g., New York).
-- **Country**: The country where the sale took place (e.g., USA).
-- **State**: The state where the sale took place (e.g., NY).
-- **Product Name**: The name of the product (e.g., Product A).
-- **Product Attribute 1**: Additional product attribute (e.g., Attribute 1A).
-- **Product Attribute 2**: Additional product attribute (e.g., Attribute 2A).
-- **Product Attribute 3**: Additional product attribute (e.g., Attribute 3A).
-- **Product Attribute 4**: Additional product attribute (e.g., Attribute 4A).
-- **Net Sales Value**: The net sales value for the transaction (e.g., `1000`).
-- **Margin Amount**: The margin for the transaction (e.g., `300`).
-- **Cost**: The cost of the product sold (e.g., `700`).
+The data should contain the following columns:
+
+| Customer Name | Date       | Product Name | Net Sales Value | Margin Amount | Cost  |
+|----------------|------------|--------------|------------------|---------------|-------|
+| John Doe       | 2024-01-01 | Product A    | 1000             | 300           | 700   |
+| Jane Smith     | 2024-01-02 | Product B    | 1500             | 400           | 1100  |
+
+### Key Columns:
+- **Customer Name**: Name of the customer
+- **Date**: Sale date (YYYY-MM-DD)
+- **Product Name**: Product sold
+- **Net Sales Value**: Sales value of the product
+- **Margin Amount**: Profit margin on the sale
+- **Cost**: Cost of the product sold
 """)
 
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