![]() Specifically, "jqplotDataHighlight", "jqplotDataUnhighlight", "jqplotDataClick" and "jqplotDataRightClick" events are triggered. This automatically sets the "highlightMouseOver" option to false.Įvents are also trigger with plot interaction. Here the "highlightMouseDown: true" option is set which causes the plot to highlight on mousedown (click). Bubble highlighting is controlled with the "highlightMouseOver" and "highlightMouseDown" boolean options. This chart also demonstrates some of the highlighting options. The "autoscaleMultiplier" will makes all bubbles larger or smaller for values greater or less than 1.0. A negative value will decrease bubble size and number of bubbles increases. The "autoscalePointsFactor" options controls bubble scaling with the number of points on the plot. The following bubble chart shows the "autoscalePointsFactor" and "autoscaleMultiplier" options which can be used to control bubble scaling. ![]() Excanvas translates the canvas rendering to VML rendering for IE 7 and 8, but unfortunately does not properly handle radial gradients. jqPlot renders charts using the HTML canvas element which is supported by nearly every browser including IE 9. Under the “ Fill Group”, set the “ Transparency” to between 50% and 70%.*Radial gradients are not supported in IE 7 and IE 8 because they are not supported in the excanvas emulation layer used by jqPlot to render charts in IE 7 and IE 8. Right-click on the bubble you want to change and choose “ Format Data point”. To modify the default color and transparency, select the bubble series. If you want to highlight one or more data points, you can do that easily by using different colors and transparency. In addition, we recommend you delete the following parts: vertical axis, gridlines, and borders. #5: Clean and customize the Bubble ChartĪpply some minor improvements to remove the unnecessary chart elements. Select the “ Labels” group and adjust the label position to “ Low” using the drop-down list. ![]() To make the chart easy to read, change the X-axis labels! Select the labels, then look at the Format Axis tab. Click on “ Select Data” and click “ Add” to add a new series. Select the chart area and right-click on it. #3: Create data points for the Bubble Chart commentsĪs we stated, you need to create connectors above the data points. Finally, under the “ Series Bubble size” section, select the C3:C25 range and click OK to close the dialog box. Next, repeat this step for Series Y values: use the E3:E25 range. After that, select values for Series X: click on the arrow icon and select the B3:B25 range. First, add a name for the series, for example, “ Sales” column values determine the bubble sizes. In this section, you can customize the selected series. Then, under the “ Legend Entries” group, click “ Edit”. To modify the chart, right-click on the chart and choose the “ Select Data Source” option. Then, under the Charts Group, click on the Bubble chart icon to insert the chart. Once your data is ready, select the B3:B25 range, and choose the Insert Tab. Finally, in the Flag column, use a simple logical expression to check whether the Comments filed are empty. The Y1 and Y2 points help you to align the connection lines between the bubble chart and the comments. In column D, you can enter the comment you want to show above the given data point. Create six columns using the following headers: “ Year”, “ Sales”, “ Comments”, “ Y1”, “ Y2”, and “ Flag”. In the example, we will track and display the sales over 20 years. How to create a Bubble chart in Excel #1: Prepare and Organize your data Today’s tutorial is a step-by-step guide we will show you all the necessary steps in detail. This property helps you to track sales, revenues, or costs over time. For example, look at the picture above the values are proportional to the displayed bubble sizes. The difference is between the standard scatter plot and bubble chart that we use various size bubbles for the different data points. ![]() Learn how to create a custom bubble chart based on a scatter plot in Excel to visualize your data over time. ![]()
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