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Visual Components
GoodData.UI comes with ready-made visual components. You can use these visual components as-is or customize them. You can also use the unique InsightView component that simply renders any chart that you create in GoodData.
This article provides components examples and basic instructions on component usage.
All examples in this section showcase the use of the code generated by catalog-export and assume that the application is set up with BackendProvider and WorkspaceProvider as described in Integrate into and Existing Application.
Currently available out-of-the-box visualizations:
| Name | Visual | Description |
|---|---|---|
| Area Chart |
| Shows data as an area under a line intersecting dots. Can display multiple measures or a single measure split by one attribute. |
| Bar Chart |
| Horizontal visual commonly used to illustrate trends, comparisons, and distributions. |
| Bubble Chart |
| Shows data as bubbles using Cartesian coordinates. Typically shows three measures for X-axis, Y-axis, and one for the size. |
| Column Chart |
| Shows data in vertical columns. Can display one or multiple measures. |
| Combo Chart |
| Combines two types of visualizations, usually, a column chart and a line chart. |
| Donut Chart |
| Shows data as proportional segments of a disc with hollowed out center. Can be segmented by either multiple measures or an attribute. |
| Geo Pushpin Chart |
| Visualizes data broken down by geographic region across an actual map and points the latitude and longitude of locations. |
| Headline |
| Shows a single number or compares two numbers. |
| Heatmap |
| Represents data as a matrix where individual values are represented as colors. Helps discover trends and understand complex datasets. |
| Line Chart |
| Shows data as line-connected dots. Can display either multiple measures as individual lines or a single measure split by one attribute into multiple lines with points intersecting attribute values. |
| Pie Chart |
| Shows data as proportional segments of a disc. Can be segmented by either multiple measures or an attribute. |
| Pivot Table |
| Expands capabilities of a regular (flat) table by allowing to reorganize and summarize selected data beyond the typical row-column relationship. |
| Scatter Plot |
| Shows data as points using Cartesian coordinates. Typically have a minimum of two measures, one for the X-axis and the other for the Y-axis, and one attribute, which determines the meaning of each data point. |
