%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

"""
Explanation: Visualization 1: Matplotlib Basics Exercises
End of explanation
"""


a= 10
x = np.random.rand(a)
y = np.random.rand(a)
colors = np.random.rand(a)
area = np.pi * (12 * np.random.rand(a))**2
plt.scatter(x, y, s=area, c=colors, alpha=0.5)
plt.xlabel('x')
plt.ylabel('y')
plt.title('Dots Are Fun')
plt.show()

"""
Explanation: 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.
End of explanation
"""


np.random.randn
plt.hist(x, bins=10, normed = True)
plt.xlabel('x')
plt.ylabel('y')

plt.show()



"""
Explanation: 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.
End of explanation
"""


