1. Uczyć się
    2. /
  2. Courses
    3. /
  3. Introduction to Python
Connected

Exercise

NumPy Side Effects

numpy is great for doing vector arithmetic. If you compare its functionality with regular Python lists, however, some things are different.

First, numpy arrays cannot contain elements with different types. If you mix types, like booleans and integers, numpy automatically converts them to a common type. Booleans like True and False are treated as 1 and 0 when combined with numbers, so the array ends up as integers.

Second, the typical arithmetic operators, such as +, -, * and / have a different meaning for regular Python lists and numpy arrays.

Select the code that results in the following output:

np.array([True, 1, 2]) + np.array([3, 4, False])

The numpy package is already imported as np. You can run each option in the IPython Shell to see the output.

Instrukcje

50 XP

Możliwe odpowiedzi