1. intro.py

import numpy as np
import matplotlib.pyplot as plt
import codecademylib3_seaborn

teacher_one_grades = [83.42, 88.04, 82.12, 85.02, 82.52, 87.47, 84.69, 85.18, 86.29, 85.53, 81.29, 82.54, 83.47, 83.91, 86.83, 88.5, 84.95, 83.79, 84.74, 84.03, 87.62, 81.15, 83.45, 80.24, 82.76, 83.98, 84.95, 83.37, 84.89, 87.29]
teacher_two_grades = [85.15, 95.64, 84.73, 71.46, 95.99, 81.61, 86.55, 79.81, 77.06, 92.86, 83.67, 73.63, 90.12, 80.64, 78.46, 76.86, 104.4, 88.53, 74.62, 91.27, 76.53, 94.37, 84.74, 81.84, 97.69, 70.77, 84.44, 88.06, 91.62, 65.82]

print("Teacher One mean: " + str(np.mean(teacher_one_grades)))
print("Teacher Two mean: " + str(np.mean(teacher_two_grades)))

plt.subplot(211)
plt.title("Teacher One Grades")
plt.xlabel("Grades")
plt.hist(teacher_one_grades)
plt.xlim(65, 105)


plt.subplot(212)
plt.title("Teacher Two Grades")
plt.xlabel("Grades")
plt.hist(teacher_two_grades, bins = 20)
plt.xlim(65, 105)

plt.tight_layout()
plt.show()