Plotting with matplotlib in Python

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Generate a BYU Football field with Python.

June 21, 2020, at 04:16 AM by 136.36.211.159 -
Deleted lines 56-73:

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May 03, 2019, at 08:55 PM by 10.37.45.29 -
Changed lines 13-29 from:
 import numpy as np
 x = np.linspace(0,6,100)
 y = np.sin(x)
 z = np.cos(x)

 import matplotlib.pyplot as plt
 plt.plot(x,y,'r--',linewidth=3)
 plt.plot(x,z,'k:',linewidth=2)
 plt.legend(['y','z'])
 plt.xlabel('x')
 plt.ylabel('values')
 plt.xlim([0, 3])
 plt.ylim([-1.5, 1.5])
 plt.savefig('myFigure.png')
 plt.savefig('myFigure.eps')
 plt.show()
to:

(:source lang=python:) import numpy as np x = np.linspace(0,6,100) y = np.sin(x) z = np.cos(x)

import matplotlib.pyplot as plt plt.plot(x,y,'r--',linewidth=3) plt.plot(x,z,'k:',linewidth=2) plt.legend(['y','z']) plt.xlabel('x') plt.ylabel('values') plt.xlim([0, 3]) plt.ylim([-1.5, 1.5]) plt.savefig('myFigure.png') plt.savefig('myFigure.eps') plt.show() (:sourceend:)

Changed lines 34-49 from:
 import numpy as np
 x = np.linspace(0,6,100)
 y = np.sin(x)
 z = np.cos(x)

 %matplotlib inline
 import matplotlib.pyplot as plt
 plt.plot(x,y,'r--',linewidth=3)
 plt.plot(x,z,'k:',linewidth=2)
 plt.legend(['y','z'])
 plt.xlabel('x')
 plt.ylabel('values')
 plt.xlim([0, 3])
 plt.ylim([-1.5, 1.5])
 plt.savefig('myFigure.png')
 plt.savefig('myFigure.eps')
to:

(:source lang=python:) import numpy as np x = np.linspace(0,6,100) y = np.sin(x) z = np.cos(x)

%matplotlib inline import matplotlib.pyplot as plt plt.plot(x,y,'r--',linewidth=3) plt.plot(x,z,'k:',linewidth=2) plt.legend(['y','z']) plt.xlabel('x') plt.ylabel('values') plt.xlim([0, 3]) plt.ylim([-1.5, 1.5]) plt.savefig('myFigure.png') plt.savefig('myFigure.eps') (:sourceend:)

Changed line 11 from:

Source Code

to:

Tutorial Source Code

Added lines 10-49:

Source Code

 import numpy as np
 x = np.linspace(0,6,100)
 y = np.sin(x)
 z = np.cos(x)

 import matplotlib.pyplot as plt
 plt.plot(x,y,'r--',linewidth=3)
 plt.plot(x,z,'k:',linewidth=2)
 plt.legend(['y','z'])
 plt.xlabel('x')
 plt.ylabel('values')
 plt.xlim([0, 3])
 plt.ylim([-1.5, 1.5])
 plt.savefig('myFigure.png')
 plt.savefig('myFigure.eps')
 plt.show()

If using the iPython notebook, exclude the command plt.show() and include %matplotlib inline before loading matplotlib.pyplot as shown below.

 import numpy as np
 x = np.linspace(0,6,100)
 y = np.sin(x)
 z = np.cos(x)

 %matplotlib inline
 import matplotlib.pyplot as plt
 plt.plot(x,y,'r--',linewidth=3)
 plt.plot(x,z,'k:',linewidth=2)
 plt.legend(['y','z'])
 plt.xlabel('x')
 plt.ylabel('values')
 plt.xlim([0, 3])
 plt.ylim([-1.5, 1.5])
 plt.savefig('myFigure.png')
 plt.savefig('myFigure.eps')

Additional Tutorials

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<iframe width="560" height="315" src="https://www.youtube.com/embed/abL-fDq4p_o" frameborder="0" allowfullscreen></iframe>

to:

<iframe width="560" height="315" src="https://www.youtube.com/embed/xRzuzT2Kmsw" frameborder="0" allowfullscreen></iframe>

Added lines 1-30:

(:title Plotting with matplotlib in Python:) (:keywords big data, data analysis, Python programming, matplotlib, scatter plot, graph, university course:) (:description Plot data with Python and export for a presentation or report:)

Effective plots are important to synthesize the information into relevant and persuasive information. The following tutorial details some of the common data plotting functions within Python.

(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/abL-fDq4p_o" frameborder="0" allowfullscreen></iframe> (:htmlend:)

This tutorial can also be completed with scripting programming languages like Excel and MATLAB. Click on the appropriate link for additional information and source code.


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