Overview

A Scatter Plot is a visualization technique that represents relationships between two numerical variables. Each point on the chart corresponds to an observation, helping to identify patterns, trends, and correlations between the variables.

When to Use

• To analyze relationships between two numerical variables.
• To detect clusters, trends, and outliers in data.
• To visualize correlations between different measures (e.g., unit sales vs. store sales).
• To represent multiple categories with colors and different marker sizes.

Data Structure

A Scatter Plot requires:

• X-Axis: A numerical field (e.g., unit_sales).
• Y-Axis: A numerical field (e.g., store_sales).
• Marker: A categorical field representing distinct groups (e.g., product_subcategory).
• Legend: A categorical field to differentiate data points by color (e.g., product_family).
• Size (Optional): A numerical field to adjust the marker size based on values (e.g., Margin).
• Color(Optional):Customize colors to represent different groups.
• Filters (Optional): Used to refine the displayed data (e.g., by date, product type, or region).

Example Data Structure

product_subcategory	product_family	unit_sales	store_sales	Margin
Fresh Vegetables	Food	3.05	12000	200
Frozen Chicken	Food	3.12	35000	500
Chocolate Candy	Non-Consumable	3.08	15000	300
Soft Drinks	Drink	3.10	18000	250
Potato Chips	Non-Consumable	3.06	9000	150

Example

The following example visualizes the relationship between unit sales and store sales across different product subcategories, with marker size representing the Margin.