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Core Visuals, SVG & HTML

This is a collection of Power BI Core Visuals, SVGs and HTML for use in Power BI. All the work is original and where this has been inspired by the work of others, I have pointed this out.

Chips & Donuts

A simple table that uses an SVG to show a donut as well as demonstrating the use of SVGs nested within HTML nested within SVGs for the display of the chips.

Chips (DAX UDF)

A UDF to easily create SVG Chips. Syntax is as simple as Bacci.SVG.Chip("Text","Blue")

Duration (DAX UDF)

A user-defined function that calculates the duration between two dates in the format n years n months n days.

Most existing algorithms I found rely on a simplified calendar (assuming 30 days per month and 365 days per year) and use basic MOD() and QUOTIENT() operations to determine the duration. This often produces inaccurate or unintuitive results. In contrast, this UDF calculates durations using actual month and year boundaries, resulting in a more natural, human-readable output. The results are displayed side by side for easy comparison with the conventional method.

Info Icon

A HTML info icon which when hovered over, displays all the key details and context that readers need to understand the numbers they’re seeing.

Matrix Gradient

Power BI conditional formatting for gradients is quite restrictive and limited to 3 colours. Using some simple DAX, we can easily interpolate between as many colours as required and have much more control over gradient boundaries.

Report Hub

HTML Content (Lite) visual used to create a report hub. Use Direct Query to query the last refresh times from each semantic model.

Slicers

Elevate the slicer user experience by showing how many records will be affected with each selection. Useful when using Sync Slicers functionality.

Tornado Chart

SVG bars created using a User Defined Function. The bars can be left or right aligned and are used here to create a 2025 World Population Pyramid. Regular Power BI data bars cannot be used in this scenario as bar lengths cannot be uniformly scaled across multiple columns and would result in a misleading visualisation.

Source data: https://www.census.gov/

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