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.



In [31]:

    
x = np.random.rand(100)
y = np.random.rand(100)
plt.scatter(x, y, color='orange', s=70, alpha=0.8)
plt.xlabel('X')
plt.ylabel('Y')
plt.title('X v. Y Scatter')









    Out[31]:





<matplotlib.text.Text at 0x7f5f4b77c850>

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.



In [19]:

    
x = np.random.rand(100)
plt.hist(x, bins=25, color='green')
plt.xlabel('X')
plt.ylabel('Y(X)')
plt.title('Random Histogram')









    Out[19]:





<matplotlib.text.Text at 0x7f5f4bff8a10>



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