Python SciPy MCQ Questions And Answers

This section focuses on "Python SciPy" for Data Science. These Python SciPy Multiple Choice Questions (MCQ) should be practiced to improve the Data Science skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations.

1. SciPy stands for?

A. science library
B. source library
C. significant library
D. scientific library

View Answer

2. Which of the following is not correct sub-packages of SciPy?

A. scipy.cluster
B. scipy.source
C. scipy.interpolate
D. scipy.signal

View Answer

3. Which of the following is true?

A. By default, all the NumPy functions have been available through the SciPy namespace
B. There is no need to import the NumPy functions explicitly, when SciPy is imported.
C. SciPy is built on top of NumPy arrays
D. All of the above

View Answer

4. What will be output for the following code?

import numpy as np

print np.linspace(1., 4., 6)

A. array([ 1. , 2.2, 2.8, 3.4, 4. ])
B. array([ 1. , 1.6, 2.8, 3.4, 4. ])
C. array([ 1. , 1.6, 2.2, 2.8, 3.4, 4. ])
D. array([ 1. , 1.6, 2.2, 2.8, 4. ])

View Answer

5. How to import Constants Package in SciPy?

A. import scipy.constants
B. from scipy.constants
C. import scipy.constants.package
D. from scipy.constants.package

View Answer

6. what is constant defined for Boltzmann constant in SciPy?

A. G
B. e
C. R
D. k

View Answer

7. What will be output for the following code?

from scipy import linalg

import numpy as np

a = np.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]])

b = np.array([2, 4, -1])

x = linalg.solve(a, b)

print x

A. array([ 2., -2., 9., 6.])
B. array([ 2., -2., 9.])
C. array([ 2., -2.])
D. array([ 2., -2., 9., -9.])

View Answer

8. In SciPy, determinant is computed using?

A. determinant()
B. SciPy.determinant()
C. det()
D. SciPy.det()

View Answer

9. Which of the following is false?

A. scipy.linalg also has some other advanced functions that are not in numpy.linalg
B. SciPy version might be faster depending on how NumPy was installed.
C. Both A and B
D. None of the above

View Answer

10. What relation is consider between Eigen value (lambda), square matrix (A) and Eign vector(v)?

A. Av = lambda*v
B. Av =Constant * lambda*v
C. Av =10 * lambda*v
D. Av != lambda*v

View Answer

---

Discussion