OpenOffice.org OpenOffice - 3.0 User's Guide Page 166

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data points. (For large time series, a line chart would be better.) It is
the default chart type.
Bar charts
Bar charts
are excellent for giving an immediate visual impact for
data comparison where time is not important, for example to
compare the popularity of a few products in a marketplace.
Pie charts
Pie charts
are excellent when you need to compare proportions, for
example, comparisons of departmental spending: what the
department spent on different items or what different departments
spent. They work best with smaller numbers of values, about half a
dozen; more than this and the visual impact begins to fade.
This is one of the charts that can profitably be made into a 3D chart.
It can then be tilted, given shadows, and generally turned into a
work of art. You can choose to explode the pie chart, but this is an
all or nothing option.
Donut charts
If you want to show the proportional nature of your data but want to
include more than one data series, a
donut chart
is your best option.
The extra layer attempts to give pies another dimension of time.
However, two or three data series are all you can include before it
becomes meaningless. As with pie charts, you can explode the
pieces of a donut chart.
Area charts
An
area chart
is a version of a line or column graph. It may be useful
where you wish to emphasize volume of change. Area charts have a
greater visual impact than a line chart, but the data you use will
make a difference. You may need to use transparency values in an
area chart.
Line charts
A
line chart
is a time series with a progression. It is ideal for raw
data, and useful for charts with plentiful data that shows trends or
changes over time where you want to emphasize continuity. On line
charts, the x-axis is ideal to represent time series data. 3D lines
confuse the viewer, so just using a thicker line often works better.
Scatter or XY charts
Scatter charts
are great for visualizing data that you have not had
time to analyze, and they may be the best for data when you have a
constant value with which to compare the data; for example weather
data, reactions under different acidity levels, conditions at altitude,
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