Python for Data Science For Dummies, 2nd Edition
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Whenever you create a plot, you need to identify the sources of information using more than just the lines. Creating a plot that uses differing line types and data point symbols makes the plot much easier for other people to use. The following table lists the line plot styles.
Color Marker Style
Code Line Color Code Marker Style Code Line Style
b blue . point - Solid
g green o circle : Dotted
r red x x-mark -. dash dot
c cyan + plus -- Dashed
m magenta * star (none) no line
y yellow s square
k black d diamond
w white v down triangle
^ up triangle
< left triangle
> right triangle
p 5-point star
h 6-point star

Remember that you can also use these styles with other kinds of plots. For example, a scatter plot can use these styles to define each of the data points. When in doubt, try the styles to see whether they’ll work with your particular plot.

About This Article

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About the book authors:

John Paul Mueller is a tech editor and the author of over 100 books on topics from networking and home security to database management and heads-down programming. Follow John's blog at http://blog.johnmuellerbooks.com/. Luca Massaron is a data scientist who specializes in organizing and interpreting big data and transforming it into smart data. He is a Google Developer Expert (GDE) in machine learning.

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