Visualization 1: Matplotlib Basics Exercises



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%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

Scatter plots

Learn how to use Matplotlib's plt.scatter function to make a 2d scatter plot.

Generate random data using np.random.randn.
Style the markers (color, size, shape, alpha) appropriately.
Include an x and y label and title.



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plt.scatter(np.random.randn(100), np.random.randn(100), marker="x", color="m", linestyle="-", alpha=0.6)
plt.xlabel("x label")
plt.ylabel("y label")









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<matplotlib.text.Text at 0x7f71da4f23d0>

Histogram

Learn how to use Matplotlib's plt.hist function to make a 1d histogram.

Generate randpom data using np.random.randn.
Figure out how to set the number of histogram bins and other style options.
Include an x and y label and title.



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plt.hist(np.random.randn(100), bins=20, cumulative=True, histtype="step", log=True, color='r')
plt.xlabel = ("Widgets")
plt.ylabel = ("Gadgets")



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