Modern analytics is not just about querying data, it’s about communicating insights clearly and effectively. Apache Superset provides a rich set of visualization options that help transform raw data into meaningful stories.
However, with so many chart types available, choosing the right visualization can be overwhelming. This guide helps you understand Superset’s chart categories, explains their purpose, and helps you decide when to use each one.
Choosing the Right Chart in Superset
When you create a chart in Superset, you are presented with a chart selector. This is where you decide how your data will be visualized.
These chart types are grouped into categories to help you navigate easily and choose based on analytical intent rather than guesswork.
Let’s walk through the key categories.
1. Correlation Charts
Correlation charts help you understand relationships between variables.
· Scatter Plot: Shows relationships between two numeric variables. Ideal for identifying correlations or clusters.
· Heatmap: Useful for showing intensity or concentration of values.
· Bubble Chart: Extends scatter plots by adding a third dimension using size.
Use case: Understanding how variables like revenue, cost, or engagement relate to each other.
2. Evolution (Trends Over Time or Categories)
These charts help you track changes and trends.
· Line Chart: Best for showing trends over time or ordered categories.
· Bar Chart: Great for comparing values across categories.
· Area Chart: Highlights magnitude over time.
· Waterfall Chart: Shows cumulative effect of sequential values.
Use case: Sales trends, user growth, or performance tracking.
3. Maps (Geospatial Analysis)
Geographical charts help visualize location-based data.
· World Map / Country Map: Compare metrics across regions.
· Deck.gl Scatterplot: Plot points on a map with size/color encoding.
Use case: Regional sales, delivery tracking, user distribution.
4. Tables (Structured Data View)
Sometimes raw precision matters more than visuals.
· Table View: Simple rows and columns with sorting and filtering.
· Pivot Table: Aggregates data like Excel for multidimensional analysis.
· Time-Series Table: Combines tabular view with temporal data.
Use case: Financial reports, audits, and detailed drilldowns.
5. Part-to-Whole Analysis
Understand composition and contribution.
· Pie Chart: Simple proportion breakdown.
· Treemap: Hierarchical distribution of data.
· Sunburst Chart: Multi-level part-to-whole visualization.
Use case: Revenue contribution by product or region.
6. Ranking Charts
Used for comparative performance analysis.
· Word Cloud: Frequency-based textual visualization.
· Radar Chart: Multi-metric comparison.
· Parallel Coordinates: Compare multiple dimensions across entities.
Use case: Performance benchmarking, feature comparison.
7. KPI & Metrics
Focused on single or summary metrics.
· Big Number: Highlights key metric.
· Gauge Chart: Shows progress toward a goal.
· Bullet Chart: Compares actual vs target.
Use case: Dashboards for executives and real-time monitoring.
8. Other Advanced Charts
· Sankey Diagram: Flow of data or users.
· Chord Diagram: Relationships between entities.
· Gantt Chart: Project timelines.
Apache Superset is more than just a BI tool—it’s a powerful visualization engine. The real value comes from selecting the right chart for the right question. A good dashboard is not the one with the most charts, but the one that delivers clarity at a glance.
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