Following are descriptions of the types of graphs you can create:

• Line graphs. Line graphs are useful for emphasizing the movement or trend of numerical data over time, since they allow a viewer to trace the evolution of a particular point by working backwards or interpolating. Highs and lows, rapid or slow movement, or a tendency towards stability are all types of trends that are well suited to a line graph.

  Line graphs can also be plotted with two or more scales to suggest a comparison of the same value, or set of values, in different time periods. The number of scales your graph has depends on the type of graph you select. There is a description of each available graph type on the Graph types tab of the Graph Assistant.

• Bar graphs. Bar graphs plot numerical data by displaying rectangular blocks against a scale. The length of a bar corresponds to a value or amount. Viewers can develop a clear mental image of comparisons among data series by distinguishing the relative heights of the bars. Use a bar graph to display numerical data when you want to present distributions of data. You can create horizontal as well as vertical bar graphs.
• Pie graphs. Pie graphs emphasize where your data fits in relation to a larger whole. Keep in mind that pie graphs work best when your data consists of several large sets. Too many variables divide the pie into small segments that are difficult to see. Use color or texture on individual segments to create visual contrast.
• Scatter graphs. Scatter graphs share many of the characteristics of basic line graphs. Data can be plotted using variable scales on both axes. When you use a scatter graph, your data is plotted using a basic line pattern. Use a scatter graph to visualize the density of individual data values around particular points or to demonstrate patterns in your data. A numeric X-axis, or sort field, will always yield a scatter graph by default.

  It is important to note that scatter graphs and line graphs are distinguishable from one another only by virtue of their X-axis format. Line graphs can appear without connecting lines (making them look like scatter graphs) and scatter graphs can appear with connecting lines (making them look like line graphs).

• Area graphs. Area graphs are similar to line graphs except that the area between the data line and the zero line (or axis) is usually colored or textured. Area graphs allow you to stack data on top of each other. Stacking enables you to highlight the relationship between data series, showing how some data series approach or shadow a second series.
• 3D graphs. 3D graphs add dimension to your graphing presentation. Dimensionality enables your viewers to recognize trends based on two or more data sets easily. 3D graphs also add impact to your presentation.
• Bubble charts. Bubble charts are used to display three dimensions, requiring only three COLUMN fields representing X, Y, and Z data values in that order. The data points can be either opaque or transparent bubbles. If you want to visualize the precise data point, you can add a dot in the center of the bubble. The size of the bubbles are proportional to the values they represent.
• Polar graphs. The Graph Assistant supports two styles of Polar graphs: an XY Polar Chart or a polar coordinate scatter chart and an XY Polar Dual-Axis Chart or a Dual-Y polar coordinate chart. In both styles, only one Column field is allowed in the following order: X (degree) for the Column field and Y (distance from the center) for the Across/By field.
• Radar graphs. Radar graphs are used to compare two or more data sets. You can use axes or polygons to represent values in a star or spider configuration. They are essentially analogous to a line chart, except that the scale wraps around. Radar graphs work well with any data that are cyclical, such as the months of a year.
• Stock Chart. Stock charts are used to track the trend of a particular stock. Stock charts show the stock's volume, opening and closing values as well as the stock's high and low values over a specific time period. The data is represented by sets of bars and/or lines.
• Histogram. Histograms depict the distribution of a data set by grouping all of the data together and assigning it to buckets based on their value. You only measure one variable in histograms. After the data is sorted by this variable, you count the number of instances of this data. This determines the height of each bar. For example, if a company wanted to measure how many franchises there are in each class of annual revenue, a histogram would show the number of franchises that have 1,000,000 to 2,000,000; 2,000,000 to 5,000,000; 5,000,000 to 10,000,000; and 10,000,000 to 15,000,000.
• Multi-y. A Multi-y is a vertical, triple/quadruple/quintuple-Y-axis clustered bar chart. Any series can be assigned to any of the triple/quadruple/quintuple axes.
• Waterfall. A Waterfall chart is a cumulative stacked chart. The waterfall chart will automatically perform the cumulative sum when using Subtotal or Total. Waterfall charts essentially require one data value for each series or group marker to be drawn in a chart.
• Miscellaneous. The Miscellaneous Graph Type includes a variety of Graph Styles:
  • Default (Circular Gauge). A Gauge Chart usually indicates the current position of a value within a given spectrum.
  • Funnel. A Funnel Chart is basically a pie chart displaying only one group of data at a time from the first series to the last series at the bottom of the funnel.
  • Pareto. The X-axis scale is for the group members. The Y-axis scale is the percent of the total accumulation for each selected series.
  • Product Position. A Product Position chart provides a visual representation of market share and growth versus revenue and measurement (past, present, and future). Product Position charts require a set of three display fields.
  • Resource Return. Resource charts plot X- and Y-axis data cumulatively. They are useful for plotting two independent variables against each other, particularly in cases where one or both of the axes specify percentages and the user wants to examine issues such as capacity utilization.
  • Spectral Map. This is a Spectral Map Chart. This is a chart with row or column matrix of markers that are colored according to data values.

You can choose among several graph styles for each graph type. First you select the graph type with which you want to work in the Graph Type drop-down list box, and then you select the graph style from the Graph Styles drop-down list box. A thumbnail graph with a graph type and style definition appears to the right on the Graph types tab.

The graph in the Graph Preview window displays the graph type and style you chose as well as any styling information you specified from the template drop-down list or in the Properties tab. The Preview does not open by default for other resolutions. In this case, you have to click the Show Preview button.

The following image is of a bar graph that uses the 3DBAR graph style. This generic chart is a two-dimensional chart with three-dimensional type bars.

The data used for this Graph Preview is built with the selected data sources' field format types and lengths of the data. In this case, the X-axis field (car) is alphanumeric (A16) and will be displayed as Axxxxxxxxxxxxxxx as the series label

where:

A

Represents the data type alphanumeric.

xxxxxxxxxxxxxxx

Indicates the number of characters or digits allowed.

The Y-axis (dealer cost and retail cost) scale is based on a data range of selected Y-axis fields.

You can manually update the Graph Preview by clicking the Update button to see how your changes will look in a graph. You can choose to have the Graph Preview updated automatically any time you make changes by selecting the Automatic update check box.

Important:

• The graphical representation in the Graph Preview is based on an internal algorithm to help show the type and style of the graph. It is not a true representation of your particular data. However, legends and axis labels will reflect selected fields, formats and positioning.
• An X11 Server is necessary when using Graph Preview on Unix installations.
• Merged graphs are not supported in the Preview panel.

The auto arrange feature enables the Graph Preview to arrange all the elements in a graph report efficiently. The auto arrange feature is checked by default.

After you have chosen a graph type, you should select an appropriate scale. A scale is a classification scheme or series of measures that you select for application to the axes of your graph. The scale provides the framework against which your data are plotted. When you choose an appropriate scale for your data, meaningful patterns can emerge, and when you modify a scale, the overall shape of your graph changes.

Steps or measures in the scale are represented along the axes of your graph by marks. The type of scale you choose determines the number of divisions along the scale. There are two general types of scales you can apply to the y-axis of your graph:

• Linear scales
• Logarithmic scales

A linear scale is a scale in which the values increase arithmetically. Each measure along the scale is one unit higher than the one that precedes it. Linear scales are useful when the data you are plotting are relatively small in range.

A logarithmic scale is a scale in which the values increase logarithmically. Each measure along the scale represents an exponential increase in the data value. Logarithmic scales are useful when you need to accommodate a large range of numbers.