LIMITACIONES DEL ESTUDIO

Figure 5.6 shows how a combination chart can be used to present two data series: The verti- cal bars represent visitor count, and the line graph represents page views. Because visitor count and page views are not exactly the same kind of quantity, you need to make use of a dual-axis facility.

Figure 5.6 A combination chart is well suited for simultaneously dis- playing different kinds of information along a common axis.

The following are important design features of this combination chart:

■ You can make the chart title and/or subtitle dependent on the underlying spreadsheet content. In this example, the subtitle is pegged to cell C5, which changes every time the day number in the Spinner control is changed.

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■ The Spinner control title and rectangular background are purposely similar in appear- ance to the Combination Chart legend. This allows the dashboard user to perceive the Spinner control as an actual part of the combination chart.

■ The plot area of the chart is a distinctly different color or shading than the area imme- diately behind the chart. This helps the visual data to stand out. The horizontal grid- lines are visible, but they don’t compete for attention with the chart data. In particular, only the major gridlines are enabled. If minor gridlines were enabled, the chart might be a little too busy.

■ The labels along the axes and in the legend appear in boldface, making the chart easier to read. Using contrasting colors or shades between the chart labels and their back- ground also helps the readability.

There are some hidden wrinkles that you need to be aware of related to combination charts. Figure 5.6 shows one of them. The primary axis ranges from a value of 1000(a nonzero

number) to 6000. The secondary axis ranges from a value of 0to 120K. As you cycle through

the days, as shown in Figure 5.7, notice that the scaling is not exactly proportional.

Figure 5.7 The scaling in this chart is not always proportional.

On day 147, the maximum value of both axes jumps up 50% (from 6000_to 9000_{and from} 120Kto 180K), but the minimum values do not change uniformly. The primary axis originally

starts at 1000, and on day 147, it grows to 3000. The secondary axis originally starts at 0, and

it remains unchanged when the timeline advances to day 147. Clearly, the scales do not remain proportional as you advance the timeline.

You can force these scales to be proportional, but to do so, you must have complete control over the scaling, and you may not always be happy with the chart appearance. You can experiment with the file ch05_DataViewer.xlf, which provides a solution.

You may need to be aware of a couple other things. Dual-axis charts are generally supported in Xcelsius 2008. If you plan on displaying three or more data series in a chart, at least two of the series will have to share either the primary axis or the secondary axis. If your data series contains similarly valued items (such as percentage of efficiency or market penetra- tion), this would not be a problem. If the values between data series vary significantly, this

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could be problematic. Consider the example of unique visitor counts and total page views. If you want to plot the ratio of page views per visitor, you might find numbers typically varying between 10 and 25. When you try including these as an additional data series in the combi- nation chart, the data becomes flatlined, as the numbers are too small for either of the pri- mary or secondary scales. To cope with this issue, you have several strategies available.

■ You could put the page views on the same axis as the visitors and place the page views per visitor on the other axis. Unless the data series sharing a common axis have similar values, this is not going to be a very effective solution. In this particular case, the page views dominate. The visitor count is visible but too small, resulting in loss of meaning- ful information.

A common technique for dealing with quantities that are vastly different in order of magnitude is to apply logarithmic scaling instead of linear scaling.

■ You could apply context switching so that only one data series is displayed at any time, but the user would have complete freedom to choose which two data series you want to view.

■ You could overlay a line chart on top of the combination chart. The line chart would need to be precisely positioned. Its background would have to be disabled so it is fully transparent. You would not display the line chart axis labels. The line chart axes could be hidden as well.

■ Instead of overlaying a chart, you could make a separate chart that is pegged to the same timeline as the main chart. If you are going to follow this strategy, and the time- line shifts the displayed data to the left or right, you should place the separate chart directly below or above the main chart, not to its left or right (see Figure 5.8).

Figure 5.8 A possible layout for two charts on the same timeline.

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Viewing Grouped Data with Stacked Charts

Stacked charts—whether column, bar, or area charts—have features similar to their

unstacked counterparts. An obvious difference is that the data displayed in a stacked chart is shown cumulatively.

With stacked charts, you can set the transparency of the data series. The transparency slider shown in Figure 5.9 applies to all the data series. The series cannot be individually set.

T I P

In order to create a unified appearance when displaying more than one chart in a dash- board, you can enclose the charts in a single rectangular shaded region, as is done in Figure 5.8.

Figure 5.9 Adjusting the trans- parency for your data series.

Transparency plays a more important role with a regular area chart than it does with a stacked chart because valuable data can be easily obscured with a regular area chart (see the lower-left corner of Figure 5.10).

Xcelsius 2008 has the Stacked Area Chart component, but there is no option to automati- cally represent data based on its relative contribution, as shown in the top-right corner of Figure 5.10. To do this, you need to prepare your spreadsheet data so that the data is repre- sented in terms of its relative contribution. Mathematically, this is straightforward. In the current example, you simply divide each of the values for the department by the total quan- tity for the quarter. Because the quantities for the quarters add up to 100%, the maximum limit for all the quarters is the fixed value 1. This is what gives this kind of stacked area

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You still need to make a further adjustment to the scaling for your Y-axis. Use of auto- scaling will push the maximum value on the Y-axis to a number greater than 1, to something

like 1.2. To regain control, you need to set your scale to manual and peg the minimum and

maximum values to 0_and 1_{, respectively (see Figure 5.11). In addition, you have the choice}

of setting the number of divisions along the Y-axis or the size of the division. Both of these approaches are equally suited because your scale is fixed.

Figure 5.10 Various ways to rep- resent data by using the Area Chart and Stacked Area Chart components.

Figure 5.11 Setting the chart scaling for displaying relative contribution.

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