# To improve the data-ink ratio, let's make the 
# following changes to the plot we created in the last step:
    # 1) Remove all of the axis tick marks.
    # 2) Hide the spines, which are the lines that 
    #    connects the tick marks, on each axis.

import pandas as pd
import matplotlib.pyplot as plt

women_degrees = pd.read_csv('percent-bachelors-degrees-women-usa.csv')
     
major_cats = ['Biology', 'Computer Science', 'Engineering', 'Math and Statistics']
fig = plt.figure(figsize=(12, 12))

for sp in range(0,4):
    ax = fig.add_subplot(2,2,sp+1)
    ax.plot(women_degrees['Year'], women_degrees[major_cats[sp]], c='blue', label='Women')
    ax.plot(women_degrees['Year'], 100-women_degrees[major_cats[sp]], c='green', label='Men')
    # Add your code here.

# Calling pyplot.legend() here will add the legend to the last subplot that was created.
plt.legend(loc='upper right')
plt.show()