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Spotfire Error Bars

charts and line charts can display vertical errors. Scatter plots can display both vertical and horizontal errors. The image below shows all four possible error bars on a scatter plot marker. However, upper spotfire curve from data table and lower errors refer to the underlying data. This means that if you use

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reversed scales in a visualization, or change orientation of the bars in a bar chart, the error bars will also be reversed spotfire trend line or change orientation respectively. For example, for a scatter plot with a reversed Y-axis, an upper vertical error will be displayed below the marker instead of above the marker. For a bar chart with horizontal bars and

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non-reversed scale, an upper horizontal error will be displayed to the right of the bar. You can choose to show only one of the error bars, or any combination of them. The length of an error bar indicates the uncertainty of the value. For example, for an average value, a long error bar means that the concentration of the values the average was calculated on is low, and thus that the average value is regression modeling spotfire uncertain. Conversely, a short error bar means that the concentration of values is high, and thus, that the average value is more certain. There are two different ways to set up error bars in Spotfire. For aggregated values, you can use one of the existing measures, such as standard error or standard deviation. The length of the error bars will then be calculated in Spotfire. In the example below, a bar chart shows the average sales for each month during one year. The statistical measure standard error was used to calculate the length of the upper error bars. No lower error bars were defined in this graph. The other way to define error bars is to use the values in existing data table columns. You may, for example, have a data table where average values and error values have already been calculated, as in the table below. You can then use these columns to set up the error bars. In the scatter plot below, the Y-axis represents the column Average, and the upper and lower errors represent the two columns Upper Error and Lower Error respectively. By default, error bars are drawn relative to the marker position in the visualization, but for some measures this may not be what you want to display. Custom expressions could be he

that column or measure are visible in the visualization. Clear the check box to hide the error bars for a column or measure.

Trendline Spotfire

No error bars will be visible in the visualization until an upper or

Spotfire Combination Chart

lower error has been defined. Settings Shows the settings for the selected column or measure. Upper error Specifies the how to interpret error bars column and aggregation method, or custom expression to use for the upper error bars. Note: The chosen column or measure must have numerical values. Lower error Specifies the column and aggregation method, https://docs.tibco.com/pub/spotfire/6.5.0/doc/html/vis/vis_error_bars.htm or custom expression to use for the lower error bars. Note: The chosen column or measure must have numerical values. Color Same as bar Choose this option if you want an error bar to have the same color as the bar. For positive bars, the lower error bar will be invisible if this option is selected, and for negative bars, the upper https://docs.tibco.com/pub/spotfire/7.0.1/doc/html/bar/bar_properties_error_bars.htm error bar will be invisible. Custom Choose this option if you want to use a custom color for the error bars. Click on the drop-down list to show the palette and select a different color. Show end caps Specifies whether or not orthogonal lines should be displayed at the end of the error bars. Include error bars in axis range Sets the automatic zooming so that the error bars are always visible. Note: The upper and lower errors refer to the underlying data. This means that if you use reversed scales in a visualization, the error bars will also be reversed. For example, for a vertical bar chart with reversed value axis, the upper error bar will be displayed below the bar. It also means that when the bars are displayed horizontally, an upper error will be displayed to the left of the bar. Note: Make sure the layout of the bar chart is set to Side-by-side bars. Open the Appearance page if you need to change the bar chart layout. See also: Bar Chart Properties How to Use the Bar Chart What is a Bar Chart? Error Bars

for in the visualization. If a check mark is shown in the check box, then error bars for that column or measure are visible in the visualization. Clear the check box to hide the error bars for a column or measure. Note that no error bars http://informatics.sepa.org.uk/SpotfireWeb/Help/GUID-ACCEF964-8760-4399-83BC-E66BACD9AD38.html will be visible in the visualization until an upper or lower error has been defined. Settings for selected error bar Shows the settings for the selected column or measure. If you use multiple Y-axes in the visualization you can define different error bars http://votolab.blogspot.com/2016/09/error-bars-are-not-just-for-use-in.html for the axes. However, all the defined vertical error bars will share the same settings for Color, Show end caps, and Include error bars in axis range. For example, you cannot set one vertical error bar to be blue, and another vertical error bars error bar to be yellow in the same scatter plot. This also applies to using multiple measures on a Y-axis with a single scale. Upper error Specifies the column and aggregation method, or custom expression to use for the upper error bars. Note that the chosen column or measure must have numerical values. For horizontal error bars in a scatter plot with non-reversed scales, the upper error refers to the error bar on the right hand side of the marker. Lower error Specifies the column and spotfire error bars aggregation method, or custom expression to use for the lower error bars. Note that the chosen column or measure must have numerical values. For horizontal error bars in a scatter plot with non-reversed scales, the lower error refers to the error bar on the left-hand side of the marker. Color Use marker color Choose this option if you want an error bar to have the same color as the line/bar/marker. In a bar chart with positive bars, the lower error bar will be invisible if this option is selected, and for negative bars, the upper error bar will be invisible. Custom color Choose this option if you want to use a custom color for the error bars. Click on the color selector to show the palette and select a different color. Show end caps Specifies whether or not orthogonal lines should be displayed at the end of the error bars. Include error bars in axis range Sets the automatic zooming so that the error bars are always visible. Note: The upper and lower errors refer to the underlying data. This means that if you use reversed scales in a visualization, the error bars will also be reversed. For example, for a vertical bar chart with reversed value axis, the upper error bar will be displayed below the bar. It also means that when the bars are displayed horizontally, an upper error will be displayed to the left of the bar. In a bar chart, make sure the layout is set to Side-by-side bars i

any data table to show approved ranges of values compared to actual values.For example, assume a sales manager in a company wants to compare the previous quarter's forecast to actual revenue for his staff. He wants to investigate any situation where the actual revenue was more than 20% above or below the forecast. If the forecast was within the acceptable range of tolerance, no further investigation was needed. If the revenue was more than 20% above or below, he needed to investigate why the forecast was off so much.So, the sales manager uses Spotfire to plot his data using a Line Chart. There are two lines displayed, one for the forecast and one for the actual of all the salespeople. Error Bars where then added to the Forecast line, with the upper value set to 20% and the lower value set to 20%.We can now see clearly which salespeople fell outside the acceptable range. If the line representing the actual sales numbers is not within the error bars, then we need to investigate further.This is automatically setup as a template, meaning, the sales manager can easily load in new data at the end of the quarter and the plot will automatically be configured with the correct error bars. If you plan on using the 20 % in other plots in the analysis, it would make more sense to store this 20% inside a Document Property (see our tip on Global Variables). Labels: Spotfire Tips & Tricks Newer Post Older Post Home Resources Spotfire IronPython Examples Spotfire Tips & Tricks Archive Spotfire Videos Powered by Blogger.

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