Being able to visualize data can have a tremendous impact on the reader. Compared to just printing raw numerical data, adding a chart to a report makes it possible for readers to quickly grasp the important relationships between data. Many times reports are used with proposals to sell a reader on an idea or plan. Adding a colorful chart can sell your idea more effectively than a dry report filled with endless numbers. This chapter shows you what types of charts are available as well as how to modify their appearance so that they can make your report more appealing and quickly get your message across.
Choosing the Proper Chart
Charts are used to make it easy to compare sets of data. The visual aspect of a chart lets the reader immediately recognize things such as the differences in quantity, percentage of the whole or numerical trending. Crystal Reports gives you 16 different types of charts to choose from. Table 12-1 lists the types and shows a sample picture of each.
Table 12-1. Example chart types.
Chart Type | Sample | Chart Type | Sample |
---|---|---|---|
Bar |
|
Radar |
|
Line |
|
Bubble |
|
Area |
|
Stock |
|
Pie |
|
Numeric Axis |
|
Doughnut |
|
Gauge |
|
3D Riser |
|
Gantt |
|
3DSurface |
|
Funnel |
|
XY Scatter |
|
Histogram |
|
With the wide variety of charts available, it can be hard to decide which one to use. Of course, you want one that looks good, but more importantly is that it is appropriate for the data you are displaying. Certain chart styles are more effective at presenting certain types of data than others. Making this decision can be a bit tough at first. Table 12-2 lists each chart type and shows where it is effective. This table gets you started in the right direction for choosing the proper chart.
Table 12-2. Effectiveness of different chart styles.
Chart Style | Effective at … |
---|---|
Bar Chart | Comparing the differences between items and events. |
Comparing items and events against the same scale without relation to time. | Showing relationships between sets of data using grouping. |
Note: The X-axis is generally non-numeric. When it is numeric, the interval isn’t relevant. | Line Chart/Area Chart |
Comparing continuous data over a period of time against a common scale. | Tracking movement over time. |
Examining trends between two or more sets of data. | Note: The X-axis represents a unit of time. |
Pie/Doughnut Chart | Visualizing the percent of the whole. |
Examining relationships as part-to-whole. | Note: There is only a single axis being represented. Thus, only one value is being charted. |
3D Riser/Surface Chart | Showing trends with relationship to time. |
Note: It uses a three dimensional surface to make it easy to analyze a large quantity of data. | X-Y Scatter Chart |
Charting a large quantity of values without relation to time. | Finding groups of data where there is a large percentage of similar data points. |
Radar Chart | Comparing data sets in a star pattern. The importance/relationship of each data set is determined by having the target value start at either the center of the axis or the outside. |
Bubble Chart | Comparing the significance of data points by looking at the size of each bubble compared to the other bubbles. Similar to the X-Y chart, but with a third data point. The third data point determines the bubble’s diameter. Each bubble is proportional to the value compared to the other data points. |
Stock Chart | Analyzing stock values. Shows the trading range for the day as well as first trade and last trade amounts. |
Gauge | Plotting one or more data points using a dial format. |
Represents a number by its position on the dial. | Gantt |
Plots activities in a business plan. Shows how long an activity took to complete as well as its relationship to the other activities. | Each activity must have a start date and stop date associated with it. |
Funnel | Shows stages in a sales process. |
Histogram | Shows how data is distributed with relationship to the mean value. |
Makes it easy to visualize the pattern within a large number of data points. |
Table 12-2 has a lot of information in it, so let’s try to make it easier to digest by looking at a table that highlights the important aspect of each chart. Table 12-3 lists different aspects you have to consider when using a chart and lists which one applies to which chart. The first columns, Time, tells you whether the chart plots data over a period of time (i.e. it plots dates). The second column, Show %, tells whether the chart visualizes what percent each data point has compared to the total chart. Bigger areas mean a larger percent. The third column, # of Data, tells you how many data points a chart is best used with. Some charts are best at showing a small number of data points and other charts are designed to plot many data points.
Table 12-3. Common chart characteristics.
Chart | Time | Show % | # of Data |
---|---|---|---|
Bar | N | N | Small/Med |
Line | Y | N | Small/Med |
Area | Y | Y | Small/Med |
Pie/Doughnut | N | Y | Small/Med |
3D Surface | Y | N | Small/Large |
X-Y Scatter | N | N | Large |
Radar | N | N | Small/Large |
Bubble | N | N | Small/Large |
Stock | Y | N | Small/Large |
Gauge | N | N | Small |
Gantt | Y | N | Small/Large |
Funnel | Y | Y | Small/Med |
Histogram | N | N | Large |
To use Table 12-2 and 12-3, think about why you are using a chart to present your data. Ask yourself what is the message you are trying to convey to the reader. Scan the list of reasons why one chart is more effective than the other charts. Once you see a description that best matches your purpose, select that type of chart.
For example, assume you have a report that prints the annual sales for each division in a corporation. The message you are conveying is which division had the largest sales volume as well as which division had the lowest sales. The charts that are good at comparing different data sets are the bar chart, the line chart and the X-Y chart. The bar chart immediately looks good because it is effective at comparing differences between items. The line chart also compares data, but it does so over a period of time. This doesn’t apply here because the data is within the same time period (i.e. the same year). So the line chart is not a good choice. The X-Y chart compares data, but it is done with respect to two data points. In other words, both the X and Y axis must represent numerical data. The sales report is charted with the sales volume and the division name. Since the division name isn’t numerical data, it can’t be used with the X-Y chart. The best choice for the division annual sales report is the bar chart.
Let’s build on this example by saying that you are given a new requirement where the report has to be modified so that it is now a drill-down report. It currently shows the annual sales per division and it needs to be modified so that you can drill-down on a division and see its monthly sales. This helps the reader determine if the division had a particular month that was exceptionally better than the other months or if the division was consistently improving. The purpose of this chart is very similar to the first chart. You want to tell the reader how the total sales compare to each other. But this example has a slight variation: you are now charting for a single division and the individual months are being compared to each other. You are working with data that changes over a period of time and looking for the trend. The only reason we didn’t use a line chart in the first example was because the data didn’t relate to time. This example does relate to time and it is also looking at the sales trend. So the line chart is an excellent choice for presenting the monthly sales figures.