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Descriptions of Graph Views
Bar
Line
Area
Pie
Time Series Line
Line-Bar
Pareto
Scatter
Bubble
Radar
Microchart
Waterfall
Many of the available views that you can add to an analysis and its Compound Layouts are graphs. There
are a variety of different available graphs, each of which is edited using the Graph editor, whose tools
and layout vary slightly depending on the requirements of the graph being designed or edited.
Bar: Shows quantities associated with categories. Bar graphs show quantities as bar lengths and
categories as bars or groups of bars. Bar graphs are useful for comparing differences among like
items; for example, competing product sales, same product sales over different time periods, or
same product sales over different markets. You can use bar graphs to compare measure
columns by showing bars in a horizontal or vertical direction.
Line: Shows quantities over time or by category. Line graphs are useful for showing trends over
time and you can use them to plot multiple measure columns.
Area: Shows the trend of the contribution of each value over time or by category. An area graph
is a line graph for which the regions between lines are filled in. Regions are stacked up, adding
up to the total value for each time period or category. In 100% stacked graphs, each category is
displayed as a percentage contribution to the total value.
Pie: Shows data sets as percentages of a whole.
Time Series Line: Plots time series data, scaling the X-axis based on the time that has elapsed
between data points.
Line-Bar: Plots two sets of data with different ranges, one set as bars, and one set as lines
overlaid on the bars. Line-bar graphs are useful for showing trend relationships between data
sets.
Pareto: Displays criteria in descending order in a form of bar graph and line graph, with the line
showing a cumulative total of the percentages. Pareto graphs are useful for identifying
significant elements, such as best and worst or most and least.
Scatter: Displays x-y axis values as discrete points, scattered within an x-y grid. Scatter graphs
plot data points based on two independent variables. This enables you to plot large numbers of
data points and observe the clustering of data points. Scatter graphs are useful for observing
relationships and trends in large data sets.