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Each bar can also have a comment, such as "comment7=xx" to show "(xx)" after the number in bar 7. For a 2-column bar chart, the 2nd column items have prefix "col2_" such as scale maximum, col2_data_max=110, and col2_data3=67 with col2_comment3=zz. See below: "Example with two data columns". Each bar chart can be formatted typically within 1/5 ...
The {{Graphical timeline}} template allows representations of extensive timelines. The template offers complex formatting and labeling options to control the output. Typically, each use is made into its own template, and the template is then transcluded into the article. See an example here, and an example of it being used in an article here.
Matplotlib can create plots in a variety of output formats, such as PNG and SVG. Matplotlib mainly does 2-D plots (such as line, contour, bar, scatter, etc.), but 3-D functionality is also available. A simple SVG line plot with Matplotlib. Here is a minimal line plot (output image is shown on the right):
A pie chart showing the composition of the 38th Parliament of Canada. A chart (sometimes known as a graph) is a graphical representation for data visualization, in which "the data is represented by symbols, such as bars in a bar chart, lines in a line chart, or slices in a pie chart". [1]
A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a column chart and has been identified as the prototype of charts. [1]
If you do not specify when a bar should start or end, it will continue to the edge of the plot Text should not be too long for the bar The way that overflowing text wraps is also handled differently in different browsers – it pokes out of the right of the bar on Firefox, but is wrapped within it by IE.
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Statistical graphics have been central to the development of science and date to the earliest attempts to analyse data. Many familiar forms, including bivariate plots, statistical maps, bar charts, and coordinate paper were used in the 18th century.