SPC Histogram 1.4.2 - What's New

Tomasz Czerkas -

Version 1.4.2 of the SPC Histogram panel for Grafana is out. This release adds a handful of features that have been requested for a while, along with the usual round of bug fixes. Here's a rundown of what changed.
Statistics Table

The biggest addition in this release is the statistics table — a summary panel that appears below the histogram and shows the key numbers for each data series in one place.

The table includes:

  • Descriptive statistics: n, Mean, Std Dev, Min, and Max
  • Control limits: LCL and UCL (when a chart type is selected)
  • Process capability indices: Cp, Cpk, Pp, and Ppk (when LSL and USL are defined)

You don't have to show every column. The panel editor lets you pick exactly which ones you want to display, so you can keep it focused on what matters for your use case.

Export to CSV

You can now export your SPC data to a CSV file directly from the panel. There are two ways to do it: click the download icon in the statistics table header, or right-click anywhere on the panel and choose "Download CSV".

The exported file has three sections: statistics (the same numbers shown in the table), control lines (name, type, and position for each configured line), and histogram data (bucket boundaries and counts per series).

One thing worth noting: this exports the calculated SPC values, not the raw data from your data source. If you need the raw values, Grafana's built-in Inspect panel export still works the same way.

Histogram Tooltip

Hovering over histogram bins now shows a tooltip with the bucket range and the count for each series — similar to how Grafana's built-in histogram panel behaves. If you have a Gaussian curve configured, the tooltip also shows the fitted curve's value at that bin, which makes it easy to compare your actual data against the expected normal distribution.

Gaussian Peak (µ) Control Line

There's a new control line type called Gaussian Peak (µ). It marks the peak of the fitted Gaussian curve, using the mean calculated by the Levenberg-Marquardt algorithm.

This is different from the arithmetic Mean control line. For data that follows a normal distribution closely, the two will land in nearly the same spot. For skewed or non-normal data, they can diverge — and seeing both on the same chart can tell you something useful about your process.

This control line requires a Gaussian curve to be configured on the same series.

Bug Fixes

A number of smaller bugs were fixed in this release. Nothing dramatic, but things should generally feel more stable and reliable.

Getting Started

SPC Histogram is available in the Grafana Plugin Catalog. If you're already using it, the update should be available from your Grafana plugin management page.

The full documentation is at docs.kensobi.com/panels/spc-histogram. If you run into issues or have questions, you can open a ticket on GitHub or join the conversation on Discord.