Section 9.3. Practical Charting

9.3. Practical Charting

Figure 9-1 shows you how to chart a list that contains two columns you want to graphone with text labels, and one with the numeric data. But in real life, you probably need to deal with many different types of data that occupy many different configurations on your worksheet.

Think for a minute about all the possible variations on the simple sales chart shown in Figure 9-1. For example, you may need to compare the sales figures but, rather than showing region-to-region comparisons, you want to show how well (or poorly) each of your firm's products sold. Or perhaps you want to chart the quarterly performance of different stores over a five-year period, or determine the relationship between sales and profitability. All these charts require a slightly different arrangement of data. In the next section, you'll get a quick introduction to all these possibilities, using just the simple column chart and line chart.

9.3.1. Charts with Multiple Series of Numbers

A series is the sequence of numbers that you plot on a graph. In the simple chart example (Figure 9-1), there's just one series of numbers, which represents the sales figures for a company's different regions. Of course, a real chart usually adds extra layers of detail. For example, you may want to compare the sales figures from several different years. In this case, you'd add a separate column to your worksheet data for each year. Then you'd add each column to your chart as a separate series.

You don't need any special expertise to create a chart that uses multiple seriesjust select your table of data, fire up the Chart Wizard, and follow the same steps as you would for a chart that has a single series. Different types of charts automatically handle multiple series in different ways. For example, the clustered column chart creates a separate bar for each value in a row, as shown in Figure 9-6. A line chart, on the other hand, shows a separate line for each series (as demonstrated in the next section). For more possibilities, take a look at the "Chart Types" section on Section 9.4.

Figure 9-6. This clustered column chart shows five sets of columns, one set for each location (Central, Eastern, Western, and so on). In each set, there are three bars, one for each data series. (In the worksheet, you see that each data series represents a sales year.) Excel labeled the regions on the category axis, but you need to consult the legend to determine which year each column represents.

Tip: You can add multiple series to an existing chart without starting over from scratch. First, select the chart so that the linked data becomes highlighted. Then, click the rightmost edge, and drag it to the right to expand the range so that it includes the new columns (which, of course, you've already added to your worksheet).

9.3.2. Controlling the Data Excel Plots on the X-Axis

Excel's charting tool has a dirty little secret. You may not realize it right away, but sooner or later, whether it's your first chart or your fortieth, you'll stumble onto the fact that Excel makes a fairly important decision for you about what data shows up in your chart's x-axis. This decision may not be what you wantbut you can change it.

The issue stems from the fact that Excel creates your charts according to how you organized the data in your worksheet. The best way to understand what kind of difference this scheme can lead to is to look at a simple example.

UP TO SPEED
Data in Different Scales

When you add multiple series, you run the risk of one potential problem. Each series must use the same scale. For example, the worksheet in Figure 9-6 works perfectly well because the different series of sales figures all use the same unitdollars. But if one series records sales totals in dollars and another records them in Euros (or even worse, records totally different data like the number of units sold), the chart would be uselessthe equivalent of comparing apples to horses.

Excel doesn't complain if your series use different scales; in fact, it has no way to notice that anything is amiss. The problem is that the chart you end up creating is misleading. For example, the chart may imply a comparison that isn't accurate or, if the scale is radically different, Excel stretches the chart so much that it starts to lose detail. For example, if you have sales figures from $50,000 to $100,000 in one series, and units sold from 1 to 100 in another, the scale stretches from 1 to 100,000, and the differences in sales totals or units sold are too small to show up at all.

What's the solution? Don't mix different scales. Ideally, convert values to the same scale (for example, use the currency exchange rate to turn Euros into U.S. dollars before you create the chart). Or just create two charts, one for each data series.

The worksheet in Figure 9-6 looks at sales based on two factors: the year when the sales were recorded and the region where the sales were made. In technical charting terms, the regions form the across-the-bottom category axis, while the sales figures form the up-and-down value axis. In other words, Excel creates a separate series for each year. But you could just as well organize the table in a different way, by making the year the category axis and creating a separate series for each region. Figure 9-7 contrasts these two different ways of looking at the same data and shows how they affect the way Excel groups your data in a column chart.

Figure 9-7. This worksheet shows the same data charted in two different ways. In the table on the left, the category axis lists the sales years and the value axis (the up-and-down data bars) lists the regions. In the table on the right, the order is switched: the category axis lists the regions, and the value axis lists the sales years. Notice the difference in bar heights between the two charts.

The column chart example shown in Figure 9-7 is fairly innocent. Although you may prefer one way of looking at the data over the other, they're relatively similar. But most Excel charts aren't as forgiving. A classic example is the line chart.

In a line chart, each line represents a different series. If you list the sales years on the category axis (as shown on the left side of Figure 9-8), you end up with a separate line for each region that shows how the region has performed over time. But if you invert the table (shown on the right side), you end up with a chart that doesn't make much sense at all: a series of lines that connect different regions in each year. Figure 9-8 illustrates the problem.

Figure 9-8. The chart on the left is pretty straightforward. The chart on the right shows a line for each year, which makes sense if you concentrate on what's being depicted but mainly illustrates the way people can use computers to complicate things.

UP TO SPEED
The Category Axis vs. the Value Axis

With simple column charts, life is easy. It doesn't matter too much what data you choose to use for your category axis because your choice simply changes the way data is grouped. Other chart types that follow the same principle include pie charts (which allow only one series), bar charts (like column charts, but oriented horizontally instead of vertically), and donut charts (where each series is a separate ring).

The same isn't true for line charts and most other types of Excel charts. The category axis you use for a line chart is important because the values in each series are connected (in this case, with a line). This line suggests some sort of "movement" or transition as values move from one category to another. That means it makes sense to use a line to connect different dates in a region (showing how sales have changed over time), but it probably doesn't make sense to use a line to connect different regions for each date. Technically, this latter scenario (shown on the right side of Figure 9-8) should show how yearly sales vary as you move from region to region, but it's just too counterintuitive for anyone to interpret properly.

As a general rule, use time or date values for the category axis. You should do this especially for chart types like line and area, which usually show how things change over time.

Clearly, when you create a line chart, you need to make sure the chart ends up displaying the data in a way you and other folks can understand. So how does Excel decide how to plot the data? Essentially, Excel makes its best guess about your data. If you have more rows than columns, Excel assumes that the first column represents the category axis. If you have more columns than rows (or if you have the same number of rows and columns), Excel assumes that the first row represents the category axis.

Fortunately, you have the power to override Excel's choice if you need to. Just follow these steps:

Right-click your chart and choose Source Data.
The Source Data dialog box appears, which has the same information as step 2 of the Chart Wizard.
In the Data Range tab, change the setting in the "Series in" section. For example, if you're currently using Rows, change the setting to Columns, or vice versa.
If you choose Rows, Excel assumes each row is a separate series, and the top row (with the column headings) is the category axis. To see an example, check out the charts in Figure 9-8. In both cases, Excel assumes that each row is a separate series. In the chart on the left, each region is a separate series. In the chart on the right, each year period is a separate series.
If you choose Columns, Excel assumes each column is a separate series, and the leftmost column (with the row headings) is the category axis. For example, if you were to use this approach with both tables in Figure 9-8, you'd reverse the results. In other words, the chart on the left would group the data into yearly series, and the chart on the right would group the data into regional series.

Tip: You don't have to change the orientation of a chart after you've created it. If you're sharp enough to anticipate the problem before it occurs, you can make the adjustment in step 2 of the Chart Wizard. Excel shows a preview of the chart to help you assess whether you have the data oriented the right way.

9.3.3. Data that Uses a Date or Time Scale

As the previous example demonstrates, using time or date values for the category axis makes a lot of sense for charting progress or spotting long-term trends. But the example does cheat a little. Even though any sentient human knows that the labels Sales-03, Sales-04, and Sales-05 represent consecutive years, Excel is oblivious to what these labels actually mean. You could, for example, chart a bunch of years that were far from sequential (Sales-92, Sales99, and Sales02, for example) and Excel would obediently (and misleadingly) place each value on the category axis, spaced out evenly.

This snafu doesn't present a problem in the previous example, but it's an issue if you need to chart years that aren't spread out evenly. Fortunately, Excel offers an easy solution. Instead of entering text labels, you can enter actual dates or times. Because Excel stores dates and times as numbers, it can scale the chart accordingly (this process is sometimes called category-axis scaling). Best of all, Excel automatically notices when you're using real dates, and kicks into action, making the appropriate adjustments, as shown in Figure 9-9.

Figure 9-9. Category-axis scaling in action.

What's happening in Figure 9-9 is worth examining in a bit of detail. The worksheet pictured shows two charts that illustrate the same data: a series of monthly sales figures from three regions (covering the time period between January 2004 and December 2005). The squares and triangles on the line charts indicate the data points for which sales data is available. The twist is that a big chunk of data (the months between August 2004 and June 2005) is missing. To make sure this omission is handled correctly, you need to enter real date values (rather than text labels) for the category axis. If you take that step, the chart Excel creates automatically uses a continuous timescale, as shown in the top chart. (As you can see by looking at the data points in the top chart, there are no data points in the middle of the series, which is as it should be.)

On the other hand, if you enter the labels as text (as was done when creating the bottom chart), you see an incorrect and misleading result: the data from August 2004 and June 2005 are placed close togethereven though they record months that are almost a year apart. A quick glance at this bottom chart, and you may not even notice that there's missing data (which could potentially lead to some pretty bad business decisions).

Note: Category-axis scaling works with more than just dates. You can scale any category-axis values, as long as they're numeric.

9.3.4. Non-Contiguous Chart Ranges

So far, all the chart examples have assumed the data you want to chart is placed in a single, tightly packed table. But what if your information is actually scattered across your worksheet? This scenario may seem uncommon, but it actually occurs quite often when you need to chart only part of the data in a table. For example, you may want to create a chart using two or three columns, and these columns may not necessarily be next to each other. If they aren't, you need to take a few extra steps when you create your chart.

For example, imagine you have a table that records the monthly sales of 10 different regional offices. However, you want to create a chart that compares only two of these offices. Your chart will use the category information in column A (which contains the month in which the sales were recorded), along with the values in column C and column D (which contain the total amount of sales for the two regions in which you're interested).

The easiest way to create this chart is to start by selecting the non-contiguous range that contains your data. This technique is described in detail in Chapter 3 (Section 3.1.2). Here's what you need to do:

First, select the data in column A with the mouse.
Excel surrounds the data with a marching-ant marquee. Don't click anywhere else yet.
Then, hold down the Ctrl key while you move over and select the data in columns C and D.
Because you're holding down the Ctrl key, column A remains selected (see Figure 9-10).
Now choose Insert Chart and follow the steps in the Chart Wizard.
This approach works most of the time. However, if you have trouble, or if the columns you want to select are spaced really far apart, you can explicitly configure the range while you're creating the chart. To try this out, just follow these steps:
1. Select the entire chart, and choose Insert Chart.
  Figure 9-10. This worksheet shows a non-contiguous selection (columns A, C, and D) that ignores the numbers from region 1. When you choose Insert Chart, the Chart Wizard charts only the selected columnsin this case, two series: one for region 2, and one for region 3.
2. In step 2 of the wizard, make sure that the "Data range" includes all the data you want, and verify that the "Series in" option is set correctly (to either Rows or Columns) so Excel knows which axis is the category axis.
  For more information on setting the "Series in" option correctly, see the section "Controlling the Data Excel Plots on the X-Axis" on Section 9.3.2.
3. Now click the Series tab, which lists all the separate series that you're adding to your chart (Figure 9-11).
  The Series tab demonstrates a little-known secret of Excel charting. Excel not only records the whole range that contains the chart data, it also lets you see how it breaks that data up into a category axis and one or more series. You can use this tab to remove a series you don't want to plot (click its name in the Series list and click Remove) or add a new series (click Add and specify the appropriate cell references for the Name and Values).
  
  Figure 9-11. You can add and remove series in the Series tab.
  
  You can click each series in the list to see the corresponding name (the label of the value from the category axis) and the values (the rest of the column or row data). More important, you can select a range and click Remove so that Excel doesn't include it in the chart.
4. Once you've removed the ranges that you don't want, click Next to go on to the next Chart Wizard step, or click Finish to insert the chart immediately.
Tip: You can also use this technique to add or remove a series from an existing chart. Just right-click the existing chart, select Source Data, and continue with step 2.