Daily DAX : Day 261 SAMPLECARTESIANPOINTSBYCOVER

 The DAX function SAMPLECARTESIANPOINTSBYCOVER is a specialized function in Power BI that allows you to generate a sample subset of data by treating rows as points in a 2D Cartesian space. It then aims to remove overlapping points based on a defined radius.

Here's a breakdown of its purpose, syntax, and use cases:

Purpose:

The primary purpose of SAMPLECARTESIANPOINTSBYCOVER is to:

    • Sample data points: It lets you extract a specified number of rows from a table.

    • Visualize spatial distribution: By treating rows as X and Y coordinates, it helps in understanding the spatial distribution of your data.

    • Remove overlapping points: It's designed to ensure that the sampled points are not too close to each other, which can be useful for visualizations where overcrowding of points is an issue.

Syntax:

The general syntax of SAMPLECARTESIANPOINTSBYCOVER is:

Code snippet

SAMPLECARTESIANPOINTSBYCOVER(

    <Size>,

    <Table>,

    <XAxis>,

    <YAxis>,

    [<Radius>],

    [<MaxMinRatio>],

    [<MaxBlankRatio>]

)

Where:

    • <Size>: The number of rows (points) you want in your sample.

    • <Table>: The table expression from which you want to sample data.

    • <XAxis>: The numerical column from your table that will represent the X-coordinate.

    • <YAxis>: The numerical column from your table that will represent the Y-coordinate.

    • [<Radius>] (Optional): A numerical column that defines a radius for each point. This is crucial for the function's ability to remove overlapping points.

    • [<MaxMinRatio>] (Optional): When Radius is specified, this defines the ratio between the maximum and minimum drawn points' radii.

    • [<MaxBlankRatio>] (Optional): When Radius is specified, this defines the ratio between the maximum drawn point's radius and points with a blank radius value.

How it works (conceptual):

    1. Plotting points: The function takes your specified XAxis and YAxis columns and imagines each row as a point in a 2D Cartesian plane.

    2. Radius and coverage: If you provide a Radius column, it associates a "coverage" area around each point.

    3. Sampling and overlap removal: It then attempts to select a subset of Size points, prioritizing those that are distinct and do not significantly overlap based on their radii. The MaxMinRatio and MaxBlankRatio parameters allow for fine-tuning this overlap removal.

Use Cases:

While SAMPLECARTESIANPOINTSBYCOVER might not be as commonly used as some other DAX functions, it can be valuable in specific scenarios, particularly in geospatial analysis, data visualization, and simulations:

    • Geospatial plotting:

        ◦ Creating representative map visualizations: If you have a dense dataset of geographical coordinates (e.g., customer locations, sensor readings), you can use this function to sample a manageable number of points that still represent the overall distribution without cluttering the map.

        ◦ Analyzing coverage areas: For instance, if you're planning cell tower placements or Wi-Fi hotspots, you could use this to simulate coverage and identify optimal locations by sampling points within desired coverage zones.

    • Simulation models: Generating input data for 2D simulations where you need a controlled distribution of points.

    • Optimization problems: Identifying candidate locations for facilities or resources where you need to consider spatial distribution and avoid too much clustering.

    • Advanced data visualization: When creating custom visuals where you need to plot data points in a 2D space and manage density for better readability.

Important Considerations and Caveats:

    • Undocumented/Unsupported: It's important to note that SAMPLECARTESIANPOINTSBYCOVER is not officially documented by Microsoft in the same way as many other DAX functions. This means its behavior might change without prior notice, and it might not be fully supported in all Power BI environments or future versions. Some sources even suggest it might be deprecated.

    • Performance: For very large datasets or a high number of points, the performance can be an issue. Careful consideration of the Size and the complexity of your Coverage definition is necessary.

    • Alternatives: For simpler random sampling, the SAMPLE DAX function is a more general and widely supported alternative. If you're primarily interested in top N results, TOPN is also a good choice.

In summary, SAMPLECARTESIANPOINTSBYCOVER is a niche DAX function that offers advanced capabilities for spatial sampling and de-duplication of points in a 2D plane. While its undocumented nature warrants caution, it can be a powerful tool for specific geospatial and visualization challenges.