Welcome to the Developing Data Products MCQs Page

Dive deep into the fascinating world of Developing Data Products with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Developing Data Products, a crucial aspect of Data Science. In this section, you will encounter a diverse range of MCQs that cover various aspects of Developing Data Products, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Science.

Check out the MCQs below to embark on an enriching journey through Developing Data Products. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Science.

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Developing Data Products MCQs | Page 5 of 5

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Q41.

Which of the following sets the size of the buffer used in ufuncs?

bufsize(size)

setsize(size)

setbufsize(size)

all of the mentioned

Discuss

Answer: (c).setbufsize(size)

Q42.

Point out the wrong statement.

A universal function is a function that operates on ndarrays in an element-by-element fashion

In Numpy, universal functions are instances of the numpy.ufunction class

Many of the built-in functions are implemented in compiled C code

All of the mentioned

Discuss

Answer: (b).In Numpy, universal functions are instances of the numpy.ufunction class

Q43.

Which of the following attribute should be used while checking for type combination input and output?

.types

.type

.class

all of the mentioned

Discuss

Answer: (a)..types

Q44.

Which of the following returns an array of ones with the same shape and type as a given array?

all_like

ones_like

one_alike

all of the mentioned

Discuss

Answer: (b).ones_like

Q45.

Point out the wrong statement.

Each universal function takes array inputs and produces array outputs

Broadcasting is used throughout NumPy to decide how to handle disparately shaped arrays

The output of the ufunc is necessarily an ndarray, if all input arguments are ndarrays

All of the mentioned

Discuss

Answer: (c).The output of the ufunc is necessarily an ndarray, if all input arguments are ndarrays

Q46.

Which of the following set the floating-point error callback function or log object?

setter

settercall

setterstack

all of the mentioned

Discuss

Answer: (b).settercall

Q47.

Some ufuncs can take output arguments.

True

False

May be True or False

Can't say

Discuss

Answer: (b).False

Q48.

___________ decompose the elements of x into mantissa and twos exponent.

trunc

fmod

frexp

ldexp

Discuss

Answer: (c).frexp

Q49.

Which of the following function take only single value as input?

iscomplex

minimum

fmin

all of the mentioned

Discuss

Answer: (a).iscomplex

Q50.

The array object returned by __array_prepare__ is passed to the ufunc for computation.

True

False

May be True or False

Can't say

Discuss

Answer: (a).True

Page 5 of 5

Welcome to the Developing Data Products MCQs Page

Developing Data Products MCQs | Page 5 of 5

Explore more Topics under Data Science

Data Science Basics

Data Analysis with Python

Data Manipulation

Data Analysis and Research

Statistical Inference and Regression Models

Machine Learning

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