![]() ![]() When you create graphs based on Excel tables, the program automatically calculates values and builds a graph based on these calculations, but there is a possibility that the automatically created graph will be uncomfortable or unattractive. Excel, in particular, is not even remotely easy to use, especially if you are not tech-savvy. Although most people claim to be proficient in Office, this is far from the case. When using the IsStartedFromZero = False option, we recommend either emphasizing the values on the axis itself, or adding an annotation notifying the user that this axis has a different starting point.These days, almost everyone uses Microsoft Office on a daily basis. While you could use this property in conjunction with the scale break, it would be poor practice in most cases as the properties serve different purposes. It is possible to set your own starting value on the axis directly, but this property automatically identifies the best starting value. Now you have a chart where the variations in the values are easier to identify. Instead of adding a scale break to the Y axis, find the property called IsStartedFromZero and set the value to False. If you have a set of data in a bar or column chart where all the values are very high with subtle, but important variations you can start the axis at a value that is not zero. ![]() Scale breaks are great for emphasizing differences for similar values within a mixed set. Remember to click Save and the update the chart. Not all the settings are required, but make sure Enabled is always set to “True”. In theScaleBreakStyle node options make a selection in the following settings. Right click on the axis where you want to apply the scale break. ![]() ![]() Make sure you are only using this feature when relevant.Īs usual, we will bypass the export, manual editing, and the import of the chart XML and just open the chart in the Advanced Chart Editor for the XrmToolBox. For these situations, you can add a scale break to the chart.Īdding a scale break gives you a better view of how the comparative segment are doing against each other, but you will lose some detail on how those segments are positioned in context of each other. Whenever you have a chart that combine very high and very low values, it can be difficult to assess individual columns. ![]()
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