Databomb Dashboard

Static Loader

This example demonstrates a static dashboard of US state error data, presenting a choropleth map, pie chart, and three data tables that update based on user selections. The visualization is built using the HPCC Systems visualization framework, loaded via a persist string that specifies version 1.10.6. The code constructs multiple interactive views—a map using the CHORO type, a pie chart, and tables—all driven by databomb data sources. It employs the `hpcc-viz.js` library from the specified URL to render the dashboard components.

79% match

Dashboard I

This interactive dashboard explores healthcare data breach submissions, showing how incident counts vary by state, breach type, and submission quarter, with a time-series of affected individuals. The interface uses a choropleth map, bar chart, pie chart, and tabbed line/table views. Selections in any chart filter the others, updating the visualizations via the `d3.nest()` API. The dashboard is built with the HPCC Systems visualization library, including `ChoroplethStates`, `Bar`, `Pie`, `Line`, `Table`, and `Grid` components.

74% match

Dashy Generated Dashboard 1

This dashboard presents a multi-panel view of people and account data, combining a US state choropleth, a gender bubble chart, a customer table, and an account summary line chart. It uses the HPCC-js composite, marshaller, and map libraries, with a RoxieRequest and WUResult fetching data from a remote ECL server. Linked selections filter results across panels, while a resizable layout arranges the widgets.

73% match

Static Loader II

This example demonstrates a dashboard visualization framework’s ability to load an older version (1.12.4) of the HPCC Systems visualization library while still running a dashboard definition built with version 1.14.0-rc7. It shows a choropleth map, pie chart, and multiple detail tables that update based on selections. The visualization uses the `hpcc-viz.js` library, with data embedded as a databomb containing aggregated error counts by state and error code.

70% match

DashBoard

This dashboard links a histogram, pie chart, and legend to enable interactive exploration of frequency data across states. Hovering over a histogram bar filters the pie chart and legend to show that state’s breakdown by age group, while hovering over a pie slice updates the histogram to display the distribution of that age group across all states. Built with D3 v3, it uses SVG for rendering and transitions for smooth updates, with mouseover and mouseout events driving the synchronized changes between the three visual components.

MMatteoTomassetti

DashBoard

This dashboard example shows how linked views can be used for interactive data exploration. A bar chart of state frequencies and a pie chart with a legend are initially displayed together, and hovering over a bar in the histogram updates the pie chart and legend to show that state's breakdown by low, mid, and high segments. Conversely, hovering over a pie slice triggers a transition that updates the histogram to reflect the frequencies of that segment across the states. The code uses D3 v3 with an SVG rendering approach, relying on d3.scale.ordinal, d3.scale.linear, and transition methods to animate the changes.

KKirun1

DashBoard

The dashboard displays the distribution of frequencies across three categories—low, mid, and high—for each state, using a histogram and an interactive pie chart linked to it. Hovering over a histogram bar filters the pie chart and legend to show that state’s category breakdown, while hovering over a pie slice updates the histogram to reflect the selected category’s totals. Built with D3 v3, the visualization uses SVG for rendering and transitions for smooth updates, driven by the `histoGram` and `pieChart` functions. The data comes from a Gist, with the code styled via custom CSS for hover effects and axis formatting.

AAlainRo

Dashboard_TEST_ok

This dashboard presents four synchronized views of sales data: a bar chart, a U.S. choropleth map, a scatter plot, and a pie chart. It uses several D3.js v6 APIs, including `scaleBand`, `scaleLinear`, `geoAlbersUsa`, `geoPath`, `pie`, and `arc`. The map colors states based on total sales from the provided dataset, while the pie chart breaks down sales by sub-category. All visualizations support interactive tooltips and updates with animation.

BBomkerss