In [1]:
p = 0.2 # probability of any student missing the class, as on any given day 20% students miss the class 
n = 10 # Total number of students

First Approach

In [2]:
from scipy.stats import binom

prob_of_0_student_missing_class = binom.pmf(0, n, p)
prob_of_1_student_missing_class = binom.pmf(1, n, p)
prob_of_2_student_missing_class = binom.pmf(2, n, p)

prob_of_at_max_2_students_missing_class = prob_of_0_student_missing_class + prob_of_1_student_missing_class + \
                                          prob_of_2_student_missing_class
In [3]:
prob_of_at_max_2_students_missing_class
Out[3]:
0.6777995264000003

Second Approach

In [4]:
Cumulative_prob_of_2_students_missing_class = binom.cdf(2, n, p)
In [5]:
Cumulative_prob_of_2_students_missing_class
Out[5]:
0.6777995264000001