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Welcome to the Formats,Objects and Operations MCQs Page

Dive deep into the fascinating world of Formats,Objects and Operations with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Formats,Objects and Operations, a crucial aspect of R Programming. In this section, you will encounter a diverse range of MCQs that cover various aspects of Formats,Objects and Operations, 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 R Programming.

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Check out the MCQs below to embark on an enriching journey through Formats,Objects and Operations. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of R Programming.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Formats,Objects and Operations. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Formats,Objects and Operations MCQs | Page 9 of 10

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Q81.
The dplyr package can be installed from CRAN using __________

a.

installall.packages(“dplyr”)

b.

install.packages(“dplyr”)

c.

installed.packages(“dplyr”)

d.

installed.packages(“dpl”)

Discuss
Answer: (b).install.packages(“dplyr”)
Q82.
Which of the following object is masked from ‘package: stats’?

a.

filter

b.

union

c.

set difference

d.

get difference

Discuss
Answer: (a).filter
Q83.
The _________ function can be used to select columns of a data frame that you want to focus on.

a.

select

b.

rename

c.

get

d.

set

Discuss
Answer: (a).select
Q84.
Point out the correct statement?

a.

You can also omit variables using the select() function by using the negative sign

b.

The arrange() function also allows a special syntax that allows you to specify variable names based on patterns

c.

Reordering rows of a data frame is normally easier to do in R

d.

The dplyr package provides any “new” functionality to R

Discuss
Answer: (a).You can also omit variables using the select() function by using the negative sign
Q85.
________ function is similar to the existing subset() function in R but is quite a bit faster.

a.

rename

b.

filter

c.

set

d.

subset

Discuss
Answer: (b).filter
Q86.
Columns can be arranged in descending order too by using the special ____ operator.

a.

asc()

b.

desc()

c.

descending()

d.

subset

Discuss
Answer: (b).desc()
Q87.
Point out the wrong statement?

a.

Renaming a variable in a data frame in R is surprisingly hard to do

b.

The mutate() function exists to compute transformations of variables in a data frame

c.

mute() function, which does the same thing as mutate() but then drops all non-transformed variables

d.

The data frame is a key data structure in statistics and in R

Discuss
Answer: (c).mute() function, which does the same thing as mutate() but then drops all non-transformed variables
Q88.
The _________ function is used to generate summary statistics from the data frame within strata defined by a variable.

a.

groupby()

b.

group()

c.

group_by()

d.

arrange

Discuss
Answer: (c).group_by()
Q89.
The ______ operator allows you to string operations in a left-to-right fashion.

a.

%>%>

b.

%>%

c.

>%>%

d.

>>>>%%%

Discuss
Answer: (b).%>%
Q90.
There is an SQL interface for relational databases via the _______ package.

a.

DIB

b.

DB2

c.

DBI

d.

DIB21

Discuss
Answer: (c).DBI
Page 9 of 10

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