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 [32]:

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

plt.scatter(x,y,color='red')
plt.grid(True)
plt.box(False)
plt.xlabel('random x values')
plt.ylabel('random y values')
plt.title('TITLE')









    Out[32]:





<matplotlib.text.Text at 0x7f8cebc0bad0>

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 [54]:

    
a=np.random.randn(1,10)
x=a[0,:]
plt.hist(x,bins=15,histtype='bar',color='green')
plt.title('MY HISTOGRAM')
plt.xlabel('RANDOM X VALUES')
plt.ylabel('FREQUENCY')









    Out[54]:





<matplotlib.text.Text at 0x7f8ceac9bd50>



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