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763 B
763 B
Exercise 7: NaN
The goal of this exercise is to learn to deal with missing data in NumPy and to manipulate NumPy arrays.
Let us consider a 2-dimensional array that contains the grades at the past two exams. Some of the students missed the first exam. As the grade is missing it has been replaced with a NaN
.
- Using
np.where
create a third column that is equal to the grade of the first exam if it exists and the second else. Add the column as the third column of the array.
Using a for loop or if/else statement is not allowed in this exercise.
import numpy as np
generator = np.random.default_rng(123)
grades = np.round(generator.uniform(low = 0.0, high = 10.0, size = (10, 2)))
grades[[1,2,5,7], [0,0,0,0]] = np.nan
print(grades)