Ridgeline Plot by Powerviz


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Visualize the trends and distribution across multiple categories as density plots

An advanced visual that shows the distribution of numeric values for several groups.

Create an in-depth visualization with ridge styling, line curves, scaling, vibrant colors, conditional formatting, and more. Allow quick comparisons by effectively utilizing space in your Power BI report.

A ridgeline plot, also known as a joy plot, is a data visualization used to display the distribution of numeric variables for multiple categories along a common continuous axis. It displays the distribution by stacking them vertically in such a manner that the overlapping lines create the impression of a mountain range. Ridgeline plots are particularly useful for showcasing how the patterns of distributions change across different categories, time periods, or scenarios, providing insights into the variability and trends within the data.

Check out the live demo here.

To access all the advanced settings features, click the gear "⚙️" icon in the top-right corner.

Key Feature Highlights:
  • Multiple Distribution: Plot distribution across several groups. It also allows more than one value comparison.
  • Ridge Style: For visually appealing display, smooth line styling and stroke and marker options are available.
  • Scaling: Spot patterns easily by controlling the Y-axis scaling and density/area overlaps.
  • Colors: Apply color by axis, category. There is 30+ palettes, 7 color scheme and FX rules available.
  • Legend: Legend is available in case of multiple values to plot data accurately.
  • Ranking: Filter out Top/Bottom N by value or peaks within data. Show remaining values as "Others".
  • Reference Line: Add line on the Y and X-axis to highlight a range or important data points.
  • Mode Line: Highlight peak points and display labels on them.
  • Custom Tooltip: Add highest, lowest, mean & median point in tooltip without any additional DAX/measure.
  • Themes: Easily save your designs using the JSON export/import feature, enabling seamless sharing and use across multiple Power BI reports.
  • Annotation: Add additional information and interpretations on specific data points.
  • Grid View: Transforms the visual into an interactive table. Use pivot mode, filter, search, and sort capabilities for quick data scanning.
  • Show condition: Show/hide the visual based on a condition.
  • Native Features: Supports native features including cross-filtering, interaction, selection, tooltip, bookmark, and context menu.
Business Use Cases:
  1. Time Series Data: When you have data that changes over time, like stock prices, weather patterns, or sales figures, you can use ridgeline plots to see how the distributions of these values evolve over different time periods.
  2. Statistical Analysis: To understand frequency datasets like population study, country comparison, or time points, you can use ridgeline plots to visualize how these values are distributed across those groups.
  3. Distribution Data: Use ridgeline plot to visualize numeric variables in form of bins or range as x-axis against multiple categories. This can reveal the frequency and patterns for the category.

Powerviz library is a set of feature-rich custom visuals that bring the “wow” factor to your reports. Create modern-looking Power BI reports with Powerviz visuals that enhance intuitive storytelling, boost the user experience and drive more user adoption.


To know more about Powerviz visuals, visit the website.

Check out the feature video and other tutorials. Learn about the Ridgeline Plot with detailed documentation.

You can also purchase Ridgeline Plot along with many other advanced visuals from Powerviz library at a discounted bundle price in ours website.

If you have any questions or need a personalized quote, you can email us at or schedule a meeting with us.

Visual capabilities

When this visual is used, it
  • Can access external services or resources

At a glance