DATA VISUALIZATION

By

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S.V.V.D.Jagadeesh

Sr. Assistant Professor

Dept of Artificial Intelligence & Data Science

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LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING

At the end of this unit, Student will be able to:

• CO4 Understand different structural data visualization techniques. (Unerstand-L2)

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Unit-IV Outcomes

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Relationship of Information

• While most of the visualization techniques focus on the display of data values and their attributes, another important application of visualization is the conveying of relational information, e.g., how data items or records are related to each other.
• These interrelationships can take many forms:

• part/subpart, parent/child, or other hierarchical relation

• connectedness, such as cities connected by roads or computers connected by networks

• derived from, as in a sequence of steps or stages

• shared classification

• similarities in values

• similarities in attributes (e.g., spatial, temporal)

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Relationship of Information

• Relationships can be simple or complex: unidirectional or bi-directional, nonweighted or weighted, certain or uncertain.
• Indeed, the relationships may provide more and richer information than that contained in the data records.

LBRCE

DATA VISUALIZATION

Groups

1. Venn Diagram:
1. Description: Overlapping circles represent relationships between groups, with each circle representing a distinct category.
2. Application: Used to show the overlap or commonalities between different sets of entities.
2. Clustered Bar Chart:
• Description: Bars are grouped together based on categories, and each bar within a group represents a subcategory.
• Application: Effective for comparing values within different categories and subcategories.
3. Pie Chart:
• Description: A circular chart divided into slices, each representing a proportion of the whole.
• Application: Useful for displaying the distribution of a whole into different categories or groups.
4. Heatmap:
• Description: A matrix where colors represent values, and rows or columns are grouped based on categories.
• Application: Commonly used to visualize the intensity of relationships or values within a matrix.
5. Dendrogram:
• Description: A tree diagram that represents hierarchical relationships, with entities grouped based on similarity.
• Application: Commonly used in clustering analysis to show relationships within hierarchical structures.

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Groups

1. Bubble Chart:
1. Description: Circles represent groups, and the size of each circle indicates a certain value or dimension.
2. Application: Useful for comparing multiple dimensions within different groups.
2. Tree Map:
• Description: Rectangles represent groups, with each rectangle divided into sub-rectangles based on a specific dimension.
• Application: Efficient for visualizing hierarchical data and the distribution of values within groups.
3. Chord Diagram:
• Description: Circles represent groups, and chords connect related groups, showing relationships between them.
• Application: Suitable for visualizing connections or interactions between multiple groups.
4. Radar Chart:
• Description: A chart with spokes radiating from the center, each representing a different category or group.
• Application: Useful for comparing values across multiple dimensions for different groups.

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GROUPS

• A Venn diagram is a type of chart used to visualize the overlap between two or more datasets. It typically uses circles or ellipsis to illustrate relationships between segments, graphically highlighting how they are similar to or different from each other.
• Venn diagrams are widely used in many disciplines, most notably in mathematics, statistics, logic, teaching, linguistics, computer science and business.
• They are particularly effective at organizing and visualizing datasets, making the relationship easier to understand. Because of its powerful visual effect, the Venn diagram is a popular choice for business reports and presentations�

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S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Displaying Hierarchial Structures

• Trees or hierarchies (we’ll use the terms interchangeably) are one of the most common structures to hold relational information.
• For this reason, many visualization techniques have been developed for display of such information.
• We can divide these techniques into two classes of algorithms:
• space-filling.
• non–space-filling.

LBRCE

DATA VISUALIZATION

• As the name implies, space-filling techniques make maximal use of the display space.
• This is accomplished by using justatpositioning to imply relations, as opposed to, for example, conveying relations with edges joining data objects.
• The two most common approaches to generating space-filling hierarchies are rectangular and radial layouts.

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Space Filling Methods

LBRCE

DATA VISUALIZATION

• Treemaps and their many variants are the most popular form of rectangular space-filling layout.
• In the basic treemap, a rectangle is recursively divided into slices, alternating horizontal and vertical slicing, based on the populations of the subtrees at a given level.
• As mentioned, many variants on treemaps have been proposed and de veloped since they were introduced, including squarified treemaps (to reduce the occurrence of long, thin rectangles) and nested treemaps (to emphasize the hierarchical structure).

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Tree Maps-Rectangular Space Filling

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Tree Maps-Rectangular Space Filling

LBRCE

DATA VISUALIZATION

• Radial space-filling hierarchy visualizations, sometimes referred to as sunburst displays, have the root of the hierarchy in the center of the display and use nested rings to convey the layers of the hierarchy.
• Each ring is divided based on the number of nodes at that level.
• These techniques follow a similar strategy to treemaps, in that the number of terminal nodes in a subtree determines the amount of screen space that will be allocated for it.
• However, unlike treemaps, which assign most screen space to conveying the terminal nodes, radial techniques also show the intermediate nodes.

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Radial Space Filling

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Radial Space Filling

LBRCE

DATA VISUALIZATION

• The most common representation used to visualize tree or hierarchical re lationships is a node-link diagram.
• Organizational charts, family trees, and tournament pairings are just some of the common applications for such diagrams.
• The drawing of such trees is influenced the most by two factors: the fan-out degree (e.g., the number of siblings a parent node can have) and the depth (e.g., the furthest node from the root).
• Trees that are significantly constrained in one or both of these aspects, such as a binary tree or a tree with only three or four levels, tend to be much easier to draw than those with fewer constraints.

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• When designing an algorithm for drawing any node-link diagram(not just trees), one must consider three categories of often-contradictory guidelines: drawing conventions, constraints, and aesthetics.
• Conventions may include restricting edges to be either a single straight line, a series of rectilinear lines, polygonal lines, or curves.
• Other conventions might be to place nodes on a fixed grid, or to have all sibling nodes share the same vertical position.
• Constraints may include requiring a particular node to be at the center of the display, or that a group of nodes be located close to each other, or that certain links must either go from top to bottom or left to right.
• Each of the above guidelines can be used to drive the algorithm design.

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• Aesthetics, however, often have significant impact on the interpretability of a tree or graph drawing, yet often result in conflicting guidelines.
• Some typical aesthetic rules include:

• minimize line crossings

• maintain a pleasing aspect ratio

• minimize the total area of the drawing

• minimize the total length of the edges

• minimize the number of bends in the edges

• minimize the number of distinct angles or curvatures used

• strive for a symmetric structure

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• For trees, especially balanced ones, it is relatively easy to design algorithms that adhere to many, if not most, of these guidelines.
• For example, a simple tree drawing procedure is given below
• Slice the drawing area into equal-height slabs, based on the depth of the tree.
• For each level of the tree, determine how many nodes need to be drawn.
• Divide each slice into equal-sized rectangles based on the number of nodes at that level.
• Draw each node in the center of its corresponding rectangle.
• Draw a link between the center-bottom of each node to the center-top of its child node(s).

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• Many enhancements can be made to this rather basic algorithm in order to improve space utilization and move child nodes closer to their parents
• Some of these include:

• Rather than using even spacing and centering, divide each level based on the number of terminal nodes belonging to each subtree.

• Spread terminal nodes evenly across the drawing area and center parent nodes above them.

• Add some buffer space between adjacent non sibling nodes to emphasize relationships.

• If possible, reorder the subtrees of a node to achieve more symmetry and balance.

• Position the root node in the center of the display and lay out child nodes radially, rather than vertically.

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• For large trees, a popular approach is to use the third dimension, supplemented with tools for rotation, translation, and zooming.
• Perhaps the most well-known of such techniques is called a cone tree.
• In this layout, the children of a node are arranged radially at evenly spaced angles and then offset perpendicular to the plane.
• The two parameters critical to this process are the radius and offset distance; varying these influences the density of the display and the level of occlusion.
• Minimally they should be set so that separate branches of the tree do not fall into the same section of 3D space.
• One method to ensure this is to have the radius inversely proportional to the depth of a node in the tree.

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S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Non Space Filling Methods

LBRCE

DATA VISUALIZATION

• Unit-IV Outcomes
• Relationship of Information
• Groups
• Displaying Hierarchial Structures
• Space Filling Methods
• Non Space Filling Methods

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S.V.V.D.Jagadeesh

Tuesday, October 21, 2025

Summary

LBRCE

DATA VISUALIZATION