Once you connect to the data that you want to analyze, you can
build simple or complex charts. These chart types including the
following:
- Bar chart. Plots numeric 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 chart to display numeric data when you want to present
distributions of data. You can create horizontal, as well as vertical
bar charts.
- Line chart. Emphasizes the movement or trend of numeric
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 toward stability
are all types of trends that are well suited to a line chart.
- Area chart. Similar to a line chart, except that the
area between the data line and the zero line (or axis) is usually
colored or textured. An area chart allows you to stack data on top
of each other. Stacking allows you to highlight the relationship between
data series, showing how some data series approach or shadow a second series.
- Pie chart. Emphasizes where your data fits in relation
to a larger whole. Keep in mind that a pie chart works 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 chart. Shows the relationship between two different
numeric measures. A scatter chart gives you a sense of trends, concentrations,
and outliers that pinpoint where to focus further investigation
efforts.
- Bubble chart. Plots data similar to a scatter chart,
where the size of each marker is proportional to the value of a
third measure.
- Treemap chart. Displays large amounts of hierarchically
structured data. Using a set of nested rectangles to illustrate
data relationships, sections of a treemap represent branches of
a tree.
- Gauge chart. Indicates the current position of a single
data value within a given spectrum. This chart has a circular shape.
A gauge thermometer chart indicates the current position of a single
data value within a given scale. This chart has the shape of a thermometer.
- Pareto chart. Uses the X axis to show group members,
and the Y axis to show the percent of the total of all groups that
each group represents. This chart highlights the differences between
groups of data.
- Box Plot chart. Shows the distribution of data, vertically
or horizontally, through five-number summaries: Upper limit, Upper
Quartile, Median, Lower Quartile, and Lower Limit. This chart can
be represented with or without outliers, also known as whiskers.
- Funnel chart. Displays only one group of data at a time,
from the first series to the last series at the bottom of the funnel.
Funnel charts are similar to pie charts.
- Pyramid chart. Displays only one group of data at a time,
from the first series to the last series at the top of the pyramid.
A pyramid chart is similar to a pie chart.
- Heatmap chart. Displays data in a table where the color
of each cell is dependent on the value in the cell. A heatmap chart
is similar to a spectral map.
- Tagcloud chart. Displays text data, typically used to
depict keywords on websites or to visualize free form text. This
format is useful for quickly perceiving the most prominent terms.
In addition to the charts that you can create, you can also create
interactive, informative maps. Using the lightweight mapping feature,
you can view important information for a region and drill down to
view and analyze trends, population changes, or sales data. These
chart types include the following:
- Choropleth map. Uses color to differentiate between
value groups on a map. It is useful for visualizing location-based
data, trends, and distributions across a geographic area.
- Proportional Symbol map. Uses marker size and color to
differentiate between the data on a map.