Mastering Radar Charts: Best Practices and Usage Examples
Radar charts, alternatively called spider or polar charts, are a visualization crafted for plotting multivariate data on a two-dimensional graph. In this representation, each variable is expressed on axes originating from a common point. Each axis corresponds to a distinct dimension, enabling a quick and simultaneous comparison of multiple variables. It is particularly useful for displaying performance metrics, as it highlights strengths and weaknesses by showing each variable’s value in an easily comprehensible and comparable form. With Bold BI by Syncfusion, users can seamlessly integrate and visualize complex data using radar charts for intuitive and dynamic data presentations. This blog explains the application of these charts in detail.
When to use a radar chart
- For performance analysis.
- When visualizing multivariate data with a moderate number of variables (around five to ten).
- When identifying the relationship between each variable is crucial.
- When displaying cyclical or periodic data, where the circular layout accentuates patterns over a range of variables.
- When you want to compare two or more products over a range of features.
When not to use a radar chart
- When dealing with many variables, the clarity of the visualization diminishes with overcrowded charts.
- If the variables being compared have significantly different scales.
The elements of a radar chart
A radar chart excels at concisely displaying multiple data points to highlight patterns, outliers, and relationships that may be less obvious in other chart types.
Let’s dive into the elements of radar charts in detail:
Data points
Data points are plotted on each axis according to the value of the corresponding variable from a particular data set.
Legend
A legend explains the colors, symbols, or line styles used when multiple data sets are plotted on the same chart. It helps distinguish the various data sets for comparative analysis.
Axes
Each axis in a radar chart represents a different variable, with points along the axis indicating the magnitude of the variable. The axes radiate from a central point and are evenly spaced around the chart.
Axis labels
In a radar chart, labels are placed at the end of each axis to identify the variable it represents. This helps viewers quickly understand what each axis stands for, making data interpretation straightforward.
Gridlines
Lines may be drawn in the chart at regular intervals from the center to aid viewers in judging the magnitude of the variables. Though not in the usual grid shape, these gridlines serve as a reference to help estimate the value of each variable, improving the accuracy of visual comparisons. Depending on the charting software, radar chart gridlines can be concentric circles or line segments between each axis.
Best practices for a radar chart
Designing radar charts for analytical purposes involves thoughtful consideration of various elements. Here are best practices and tips, with particular focus on dimensions and audience:
Identify key dimensions:
- Define the essential dimensions that align with your analytical goals. Select variables that provide meaningful insights and contribute to the data narrative.
- Prioritize simplicity by limiting the number of dimensions to maintain clarity and avoid overwhelming your audience with excessive information.
Normalize data: If your selected dimensions have different scales or units, consider normalizing the data. This ensures that each dimension contributes proportionally to the overall analysis, preventing bias toward variables with larger magnitudes.
Tailor to audience understanding: Understand your audience’s background, expertise, and preferences, and tailor the chart’s complexity to match the audience’s analytical proficiency.
Use consistent scaling: Maintain consistent scaling across all axes to facilitate accurate comparisons. Inconsistent scaling can distort the representation of data and lead to misinterpretations.
How to configure a radar chart in Bold BI
To configure data for a radar chart in Bold BI, follow these steps:
- Prepare your data by selecting the tables and columns you want to plot in the chart on the Data Sources page.
- In the Widget panel, select the Radar Polar chart under the Comparison category, drag and drop it into the dashboard designer page, and then resize it to the desired dimensions.
- Click the Properties panel of the chart and navigate to the Assign Data tab.
- Drag and drop a Dimension to the Columns field and drag two or more Measures to the Values field.
- Customize the chart by setting properties according to your preferences.
- Add labels and legends for a clear presentation of the data.
- Click the Preview button to see how the chart looks with your data, and then save your dashboard.
Refer to our documentation for more details.
Use cases of radar charts in various industries
This visual representation of data is widely utilized in business management for benchmarking, strategic planning, and performance analysis, and in various other areas for direct, interactive multivariate data comparison. Such domains include:
Information technology
a. Monthly investment and revenue
A radar chart comparing monthly investment and revenue in IT departments provides a clear picture of the department’s finances. The Investment category shows spending on research, physical and digital infrastructure, and operations, while the Revenue category shows monthly earnings. This chart helps stakeholders assess the relationship between expenses and income, aiding in financial planning. It highlights profitable periods and opportunities for cost-cutting or increased investment.
Healthcare industry
a. Implant failure rate vs. pain management score by complication type
This radar chart shows the relationship between implant failure rates and pain management effectiveness, sorted by complication type, in healthcare. The Pain Management Score series measures pain control quality, and the Implant Failure Rate series shows how many implants fail. This chart helps healthcare professionals identify patterns between pain management and implant success, improving patient care and guiding surgical and aftercare practices.
b. Admissions by gender and urgency type
This radar chart provides key insights into patient demographics and resources in healthcare. The Male and Female series show gender-based admissions, and the urgency levels-emergency, inpatient, outpatient, and booked appointment-indicate case frequency. This visual aid helps healthcare managers and providers recognize admission trends, plan for gender-based resources, and prepare for varying care urgencies.
Customer support department
a. Resolved vs. unresolved tickets by priority
For a customer support team, monitoring resolved versus unresolved tickets by their urgency is key to gauging team performance and customer happiness. A radar chart can helpfully visualize this information by representing a different ticket urgency level on each spoke and then plotting the number of resolved and unresolved tickets in each level. This helps identifies weak spots in support and guides efforts to cut down on wait times. Improved resolution efforts enhance overall service for users.
How challenges in radar charts can be solved using Bold BI features
Complex data interpretation: Radar charts with multiple variables can be hard to read. Bold BI simplifies this with interactive filters and highlights, making data stand out for easier analysis.
Flexible customization: Standard radar charts might be difficult to comprehend. Bold BI provides easy customization options for scale, color, and data points to meet user needs.
Entity comparison: Comparing several entities on radar charts can be confusing. Bold BI allows for clearer comparisons with side-by-side charts or multiple small charts in the same space.
Data scaling: Disparate scales can skew radar chart data. Bold BI offers data normalization to equalize variable scales for accurate comparisons.
In summary, the radar chart is a potent tool for visualizing and comparing multidimensional data, highlighting patterns and relationships with its radial layout. It provides decision-makers with clear insights, proving useful in any industry or domain.
Originally published at https://www.boldbi.com on March 6, 2024.
