Visualization 1: Matplotlib Basics Exercises



In [1]:

    
%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 [2]:

    
plt.scatter(np.random.randn(100), np.random.randn(100), c='g', s=50, marker='+', alpha=0.7)
plt.xlabel('Random x values')
plt.ylabel('Random y values')
plt.title('Randomness Fun!')









    Out[2]:





<matplotlib.text.Text at 0x7f3ea4f27610>

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 [3]:

    
plt.hist(np.random.randn(100), bins=5, log=True, orientation='horizontal')
plt.xlabel('Logarithmic Probability')
plt.ylabel('Random Number')
plt.title('Probability of Random Numbers')









    Out[3]:





<matplotlib.text.Text at 0x7f3ea4e1a750>