Visualization 1: Matplotlib Basics Exercises



In [2]:

    
%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 [4]:

    
x = np.random.randn(100)
y = 2.4 * x + 1.3 + np.random.randn(100)
plt.scatter(x, y)
plt.xlabel("x")
plt.ylabel("y")
plt.title("y vs. x")









    Out[4]:





<matplotlib.text.Text at 0x7f150ef1e6d0>

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 [5]:

    
z = np.random.randn(10000)
plt.hist(z)
plt.xlabel("z")
plt.ylabel("Frequency")
plt.title("Histogram of z")









    Out[5]:





<matplotlib.text.Text at 0x7f150ee56690>