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 [28]:

    
z=np.random.randn(2,10)
x=z[0,:]
x
y=z[1.:]
y

plt.scatter(x, y, s=60)
plt.xlabel('x')
plt.ylabel('y')
plt.title('y vs x')
plt.tight_layout()
plt.grid(True)
plt.yticks([-4,-2,0,2,4], [-4,-2,0,2,4])
plt.ylim(-5, 5)









    Out[28]:





(-5, 5)

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 [48]:

    
f=np.random.randn(10)

plt.hist(f, bins=3, color='r')
plt.xlabel('x')
plt.ylabel('y')
plt.tick_params(length=0)
plt.title('y vs x')









    Out[48]:





<matplotlib.text.Text at 0x7f72c253a790>



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