import matplotlib.pyplot as plt

measures = [-1.2, 1.2, -5.3, -9.9, 0.7, -7.5, 0.4, 2.8, 2.7, 4.8,
            1.3, 1.1, 6.6, 4.2, 5.8, 6.5, 2.4, 3.4, 5.9, 2.4, -0.9,
            -1.5, 4.1, 8.3, 7.9, 9.2, 9.9, 6.0]
old_values = [1.3, 5, 6, -2.1, 3.1, 2, 1.9, -5]

# Draw a boxplot from statistics in the list measures:
# plt.boxplot(measures) # boxplot
# plt.show() # the small circles are outliers

# Two boxplots in one window:
data = [measures, old_values]
fig, ax1 = plt.subplots() # fig for saving the image
ax1.set_title('Basic Plot')
ax1.set_xticklabels(['2021','1998'])
ax1.grid() # gives only horizontal lines, since no numbers on x-axis

# annotate: xy: where the interesting thing is, xytext= place the text here.
plt.annotate('Current values', xy=(1,10), xytext=(0.8, 10))
plt.annotate('Old values', xy=(1, 10), xytext=(1.9, 10))
plt.annotate('Outlier', xy=(1, -7.5), xytext=(1.4, 0), arrowprops=dict(facecolor='red'))
plt.boxplot(data)
fig.savefig("7_2.png") # Save the image
plt.show()