This topic is under construction for the 17.3 release of LabKey Server. For current documentation of this feature, click here.

Create a Scatter Plot

  • Navigate to the data grid you want to visualize.
  • Select (Charts) > Create Chart. Click Scatter.
  • The columns eligible for charting from your current grid view are listed.
  • Select the X Axis column by drag and drop.
  • Select the Y Axis column by drag and drop.
  • Only the X and Y Axes are required to create a basic scatter plot. Other options will be explored below.
  • Click Apply to see the basic plot.
  • Click View Data to see, filter, or export the underlying data.
  • Click View Chart to return. If you applied any filters, you would see them immediately reflected in the plot.
  • Customize your visualization using the Chart Type and Chart Layout links in the upper right.
  • Chart Type reopens the creation dialog allowing you to:
    • Change the X or Y Axis column (hover and click the X to delete the current selection).
    • Optionally select columns for grouping of points by color or shape.
    • Note that you can also click another chart type on the left to switch how you visualize the data with the same axes and color/shape groupings when practical.
    • Click Apply to update the chart with the selected changes.
  • Here we see the same scatter plot data, with colors varying by cohort and points shaped based on gender. Notice the key in the upper right.

Change Chart Layout

The Chart Layout button offers the ability to change the look and feel of your chart.

There are four tabs:

  • General:
    • Provide a title to display on the plot. The default is the name of the source data grid.
    • Provide a subtitle to display under the title.
    • Specify a width and height.
    • Choose whether to jitter points.
    • Control the point size and opacity, as well as choose the default color palette. Options: Light (default), Dark, and Alternate. The array of colors is shown under the selection.
    • Group By Density: Select either "Always" or "When number of data points exceeds 10,000."
    • Grouped Data Shape: Choose either hexagons or squares.
    • Density Color Palette: Options are blue & white, heat (yellow/orange/red), or select a single color from the dropdown to show in graded levels. These palettes override the default color palette and other point options in the left column.
  • X-Axis/Y-Axis:
    • Change the display labels for the axis (notice this does not change which column provides the data).
    • Choose log or linear scale for the Y-axis, and specify a range if desired.
  • Developer: Only available to users that are members of the "Site Developers" permission group.
    • Provide a JavaScript function that will be called when a data point in the chart is clicked.

Example: Heat Map

Displaying a scatter plot as a heatmap is done by changing the layout of a chart. Very large datasets are easier to interpret as heatmaps, grouped by density (also known as point binning).

  • Click Chart Layout and change Group By Density to "Always".
  • Select Heat as the Density Color Palette and leave the default Hexagon shape selected
  • Click Apply to update the chart with the selected changes.
  • Notice that when binning is active, a warning message will appear reading: "The number of individual points exceeds XX. The data is now grouped by density which overrides some layout options." XX will be either 10,000 or 1, if you selected "Always" as we did. Click Dismiss to remove that message from the plot display.

Save and Export Plots

  • When your plot is finished, click Save.
  • Name the plot, enter a description (optional), and choose whether to make it viewable by others. You will also see the default thumbnail which has been auto-generated, and can choose whether to use it. As with other charts, you can later attach a custom thumbnail if desired.

Once you have saved a scatter plot, it will appear in the Data Browser and on the (charts) menu for the source dataset. You can manage metadata about it as described in Manage Data Views.

Export Chart

Hover over the chart to reveal export option buttons in the upper right corner:

Export your completed chart by clicking an option:

  • Script: pop up a window displaying the JavaScript for the chart which you can then copy and paste into a wiki. See Export Chart as JavaScript for a tutorial on this feature.
  • PNG: create a PNG image.
  • PDF: generate a PDF file.


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