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This template also takes a variety of other parameters: |color-#= The template can take a color input for each do that is color-dot number (The default color is red) (overrides color-even and color-odd) |legend-color= This template can take a legend input to add to the legend.
A dot plot of 50 random values from 0 to 9. The dot plot as a representation of a distribution consists of group of data points plotted on a simple scale. Dot plots are used for continuous, quantitative, univariate data. Data points may be labelled if there are few of them. Dot plots are one of the simplest statistical plots, and are suitable ...
This template's initial visibility currently defaults to expanded, meaning that it is fully visible. To change this template's initial visibility, the |state= parameter may be used: {{Graph, chart and plot templates | state = collapsed}} will show the template collapsed, i.e. hidden apart from its title bar.
Dot plot (bioinformatics), for comparing two sequences Dot plot (statistics) , data points on a simple scale Dot plot graphic for Federal Reserve Open Market Committee polling result
The Fed’s dot plot is a chart updated quarterly that records each Fed official’s projection for the central bank’s key short-term interest rate, the federal funds rate. The dots reflect what ...
Dot plot showing the death rates per 1000 in Virginia in 1940. The graphic was created by User:Schutz for Wikipedia on 28 December 2006, using the R statistical project . The program that generated the graphic is given below; it is based on the example provided with the help page of the R dataset dotchart (accessible using the command help ...
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):
The presence of one of these features, or the presence of multiple features, will cause for multiple lines to be plotted in a various possibility of configurations, depending on the features present in the sequences. A feature that will cause a very different result on the dot plot is the presence of low-complexity region/regions.