Tree Map Example

Tree Map Example

Problem Statement

Create a Tree Map for the Cars data using the variables disp, wt, and gear.

How to perform analysis

Step 1: Open Sigma Magic
  1. Click on the Sigma Magic button on the Excel toolbar.
  2. Click on the New button to create a new project.
Step 2: Add the analysis template
  1. Click on the Tool Wizard to add the analysis template.
  2. Click on Analytics and then Tree Map.


Step 3: Specify analysis options
A new worksheet will be added to your workbook. Analysis Setup will be automatically opened, in the setup tab specify the survey results.



Click on Data to specify the data required for this analysis.



If you need to make changes to the charts, specify the optional settings in the Charts tab.

 Labels:

  • Add a title for the chart.
  • Label the X-axis and Y-axis appropriately.

Appearance:

  • Adjust colors, font sizes, or other visual elements as needed.
  • Enable/disable gridlines or background shading.


Click the Verify tab to ensure all the inputs are okay and shown in a green checkmark.



Step 4: Generate analysis result
Click OK and then click Compute Outputs to get the final results.



Interpretation of Results

    • The tree map visualizes data with grouping by "disp" and values based on "wt" (as per the Input Summary).
    • Each rectangle represents a unique category within "disp" with the weight ("wt") as its size.
    • The size of each rectangle is proportional to the "wt" values.
    • Larger rectangles indicate higher "wt" values, while smaller ones signify lower values.
    • Each category is color-coded, making it easier to distinguish different groups within "disp".
    • The colors provide a quick visual reference for comparison.
    • The largest rectangle (472) suggests that one category contributes significantly more than others.
    • The smallest rectangle (108) represents the category with the lowest "wt" value.
    • The tree map is not evenly distributed, indicating that certain categories dominate the dataset.
    • Some categories have significantly larger areas, suggesting an imbalance in values.
    • Each rectangle contains numerical values representing "wt", making it easier to compare different categories.
    • The labels provide exact numbers, avoiding the need for estimations.
    • The Input Summary confirms a continuous data type, ensuring that the values can be analyzed on a scale.
    • This justifies the tree map’s approach of using area sizes for representation.
    • The nested layout shows that the dataset contains different subcategories grouped under a broader classification.
    • This can help in analyzing dependencies or hierarchical trends.
    • This visualization could be useful for weight analysis in manufacturing, performance distribution in business, or market segmentation.
    • It allows decision-makers to quickly identify dominant categories and underperforming segments.
    • The tree map is successfully created as per the "Analysis Results" and "Conclusion" sections.
    • It provides an effective and visually appealing way to interpret weighted hierarchical data.

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