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Figure 10-19 Here you can define as many languages as you want .
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It is quite easy to set up such a model:
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The Parameters 1 worksheet, which is fully used here again, contains all of the label elements to be used in the relevant language versions (see Figure 10-19) . Depending on the current control setting, they are transferred to the Data 1 and Basis sheet (see Figure 10-20) and shown in the chart .
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Figure 10-20 Something a little different: a two-row axis label from one text list .
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Profile Comparisons on the Radar Chart
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The data source for the chart is the range K11:Q23 in the Data 1 and Basis sheet . The unusual category axis label for the chart can be interpreted from Figure 10-20 . It is easy to create this type of offset two-row structure, which is always an option if the text is longer than the width of the chart column, if it cannot or must not be wrapped, and if it should remain horizontal for the sake of legibility . The result is a little different thus it is effective . Note The cells that appear to be empty in the range K12:L23 must contain blank characters . Otherwise, the entries in the second row will shift in the chart s axis label .
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The chart heading is a text field linked with the cell rD1.Heading . This map of Europe, in which the nations represented within the company have been highlighted, is available on the CD-ROM as the file \Materials\Pictures\Europe03.tif .
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Profile Comparisons on the radar Chart
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The first time anyone sees a radar chart without its data series, they immediately think of a spider s web . So do these charts show what was the prey Or do they plot the results of a managerial radar surveillance Of course, they don t . The data series for this extremely helpful chart type appear as lines that have been closed to form shapes and/or molded areas . The term profile chart would be more appropriate because this is exactly what this chart produces best: easy-to-understand profiles and specific shapes that form a whole . The chart clearly comprises comparatively similar shapes that differ in some regard, is an accurate description . You will immediately see why the radar chart is particularly good at any form of comparison and why it is my unrivaled favorite when it comes to comparative analyses for survey or measurement results . On the Companion CD Open the file \Samples\1006_RadarComparison.xlsx on the CD-ROM . The Focus 1 worksheet in the file 1006_RadarComparison is designed for the Full screen presentation view and is protected without a password . Allow me to set the scene: a beverages manufacturer has conducted sensory product testing several times and presented the results in a dynamic radar chart . This is part of a market analysis whose results will influence the company s new product range .
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Figure 10-21 Whatever anyone tastes can be measured and compared using this chart .
First, you need to know how this model works . Note the following points with reference to Figure 10-21:
You can use four OptionButtons to determine which test results you want to display: Tap Water, Mineral Water, Soda Pops, or Juices (the sensory rating of tap water is a benchmark for standardizing the testing modes) . When you click an OptionButton, the selection lists for both underlying ComboBoxes are updated accordingly; in other words, their content changes . These lists, which are managed in parallel, enable you to make selections according to specific product groups and then compare, at product level, the data for each list entry against the data for another list entry . You can also remove either data series to display individual profiles . The double selection made in the ComboBoxes is combined to form comparison profiles within the chart . An area that belongs to the left ComboBox is compared against a shape with a blue outline . Each category in the radar chart has its own value axis . However, its scaling is shown only once and fixed in this example (0, 100, 20, which means that the testing subjects could award each drink a maximum of 100 points) . The data series connect the six value axes . The closer a data series on a value axis approaches the outer edge of the radar chart, the better the product rating . The category abbreviations shown as data labels are age groups . For example, TS_C 23-32 stands for Testing Subjects, group C, aged between 23 and 32 . In short, the profiles show the popularity of each drink in each age group .
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