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

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


x = np.random.randn(25)
y= np.random.randn(25)
plt.scatter(x,y, c = 'c', alpha = 0.7 , s=60, marker = '*')
plt.xlabel('x')
plt.ylabel('y')
plt.title('Random Data')
plt.box(False)

"""
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
"""


data = np.random.randn(100)
plt.hist(data, bins=10, color="green", alpha=0.6)
plt.title('Random Data Histogram')
plt.xlabel('Number')
plt.ylabel('Times Generated')
plt.box(False)

"""
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
"""


