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matplotlib

Matplotlib is a powerful Python 2D plotting library that generates publication-quality figures in various formats. This guide covers the basics of creating simple plots, customizing plots with colors and markers, and managing multiple figures and subplots. Learn how to use Matplotlib to visualize data effectively, including working with histograms and customizing labels. Whether you're plotting lines, scatter plots, or histograms, Matplotlib provides the tools necessary for high-quality visualizations in your data analysis projects.

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matplotlib

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  1. matplotlib

  2. matplotlib

  3. matplotlib matplotlib is a python 2D plotting library which produces publicatio quality figures in a variety of hardcopy http://matplotlib.sourceforge.net/

  4. matplotlib Simple Plot. The most basic plot(), with text labels import matplotlib.pyplot as plt plt.plot([1,2,3,4])‏ plt.ylabel('some numbers')‏ plt.show()‏

  5. matplotlib plot() is a versatile command, and will take an arbitrary number of arguments. For example, to plot x versus y, you can issue the command: plt.plot([1,2,3,4], [1,4,9,16])‏ there is an optional third argument which is the format string that indicates the color and line type of the plot.

  6. matplotlib import matplotlib.pyplot as plt plt.plot([1,2,3,4], [1,4,9,16], 'ro')‏ plt.axis([0, 6, 0, 20])‏ plt.show()‏

  7. matplotlib import matplotlib.pyplot as plt t= [float(x)/10.0 for x in range(0,50,2)] t2=[x**2 for x in t] t3=[x**3 for x in t] plt.plot(t,t,'r--', t,t2,'bs', t,t3,'g^')‏ plt.show()‏

  8. Matplotlib: Working with multiple figures and axes import matplotlib.pyplot as plt plt.figure(1) # the first figure plt.subplot(211) # the first subplot in the first figure plt.plot([1,2,3])‏ plt.subplot(212) # the second subplot in the first figure plt.plot([4,5,6])‏ plt.figure(2) # a second figure plt.plot([4,5,6]) # creates a subplot(111) by default plt.figure(1) # figure 1 current; subplot(212) still current plt.subplot(211) # make subplot(211) in figure1 current plt.title('Easy as 1,2,3') # subplot 211 title plt.show()‏

  9. Matplotlib: working with text import numpy as np import matplotlib.pyplot as plt mu, sigma = 100, 15 x = mu + sigma * np.random.randn(10000)‏ # the histogram of the data n, bins, patches = plt.hist(x, 50, normed=1, facecolor='g', alpha=0.75)‏ plt.xlabel('Smarts')‏ plt.ylabel('Probability')‏ plt.title('Histogram of IQ')‏ plt.text(60,.025, r'$\mu=100,\ \sigma=15$')‏ plt.axis([40, 160, 0, 0.03])‏ plt.grid(True)‏ plt.show()‏

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