The goal of this tutorial is to provide an overview of the use of Matplotlib. Matplotlib has a vast array of functionality, so this is by no means complete. For more information, try looking at the:
Matplotlib is a library that started as a way to get MATLAB-like plotting capabilities in Python. It has since evolved on its own, with a focus on publication-quality graphics. Some features
Matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
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# Set-up to have matplotlib use its inline backend
%matplotlib inline
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# Convention for import of the pyplot interface
import matplotlib.pyplot as plt
import numpy as np
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# Create some example data
x = np.linspace(0, 2, 100)
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# Go ahead and explicitly create a figure and an axes
fig, ax = plt.subplots(1, 1)
# Plot our x variable on the x-axis and x^2 on the y-axis
ax.plot(x, x**2)
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# Add some labels to the plot
ax.set_xlabel('x')
ax.set_ylabel('f(x)')
# Needed to reuse and see the updated plot while using inline
fig
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# Let's add a title with a bit of latex syntax
ax.set_title('$y = x^2$', fontdict={'size':22})
fig
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fig, ax = plt.subplots(figsize=(6, 4), dpi=100)
# Plot a set of different polynomials.
# The label argument is used when generating a legend.
ax.plot(x, x, label='$x$')
ax.plot(x, x * x, label='$x^2$')
ax.plot(x, x**3, label='$x^3$')
# Add labels and title
ax.set_xlabel('x')
ax.set_ylabel('f(x)')
ax.set_title('Polynomials')
# Add gridlines
ax.grid(True)
# Add a legend to the upper left corner of the plot
ax.legend(loc='upper left')
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Make a plot containing: