Universal functions (ufuncs) in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a numpy array and apply the square root ufunc.

NumPy

import numpy as np
arr = np.array([1, 4, 9, 16])
sqrt_arr = np.[1](arr)
print(sqrt_arr)

Drag options to blanks, or click blank then click option'

Aexp

Bsqrt

Clog

Dsquare

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'square' instead of 'sqrt' which squares the numbers instead of square rooting.

Using 'log' or 'exp' which perform different mathematical operations.

The sqrt function computes the square root of each element in the array.

2fill in blank

medium

Complete the code to apply the numpy ufunc that calculates the exponential of each element.

NumPy

import numpy as np
arr = np.array([0, 1, 2])
exp_arr = np.[1](arr)
print(exp_arr)

Drag options to blanks, or click blank then click option'

Alog

Bsqrt

Cabs

Dexp

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'log' which calculates the logarithm, not the exponential.

Using 'sqrt' which calculates square roots.

The exp function calculates the exponential (e^x) of each element in the array.

3fill in blank

hard

Fix the error in the code by choosing the correct numpy ufunc to calculate the absolute values.

NumPy

import numpy as np
arr = np.array([-1, -2, 3])
abs_arr = np.[1](arr)
print(abs_arr)

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Aabs

Bfabs

Cabsolute

Dsign

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'abs', which is an alias but the full ufunc name is 'absolute'.

Using 'sign' which returns the sign of each element, not the absolute value.

Using 'fabs' which is specifically for floating-point absolute value.

The correct numpy ufunc for absolute values is absolute (with abs as an alias).

4fill in blank

hard

Complete the code to apply the numpy ufunc that calculates the base-10 logarithm of each element.

NumPy

import numpy as np
arr = np.array([1, 10, 100])
log_arr = np.[1](arr)
print(log_arr)

Drag options to blanks, or click blank then click option'

Alog

Bsqrt

Clog10

Dexp

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'log' which computes the natural logarithm (base e).

Using 'exp' or 'sqrt' which perform different operations.

The log10 ufunc computes the base-10 logarithm of each element in the array.

5fill in blank

hard

Complete the code to apply the floor ufunc, which rounds each element down to the nearest integer.

NumPy

import numpy as np
arr = np.array([0.7, 1.5, -1.8, -0.1])
floor_arr = np.[1](arr)
print(floor_arr)

Drag options to blanks, or click blank then click option'

Afloor

Bceil

Crint

Dfix

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ceil' which rounds up to the nearest integer.

Using 'fix' which rounds towards zero.

The floor ufunc rounds each element towards negative infinity to the nearest integer.