R interview questions part 10
R interview questions part 10
Take as many assements as you can to improve your validate your skill rating
Total Questions: 20
1. To bind a row onto an already existing matrix, the ______ function can be used.
Correct Answer is : Rbind
2. Which of the following is a 3-dimensional dataset?
Correct Answer is : Iris
3. Which dimension corresponds to the explanatory variables collected for each species?
Correct Answer is : Second
4. Using the ________ vector, we create a species factor and bind it to the columns of iris.df.
Correct Answer is : snames
5. Accessing elements is achieved through a process called ________
Correct Answer is : Indexing
6. Which are indexed by either row or column using a specific name or number?
Correct Answer is : Data frames
7. What should we use to access elements with a value greater than five?
Correct Answer is : Subsetting commands
8. Lists can be created using the _______ function.
Correct Answer is : List
9. First component of the list can be accessed by _____________
Correct Answer is : Name of the component
10. How can we access the first component of the list?
Correct Answer is : Number of the position
11. The first component can be accessed using __________ operator.
Correct Answer is : Extraction
12. To extract a sublist, we use _________ brackets.
Correct Answer is : Single
13. The length of a list is ______ to the number of components in that list.
Correct Answer is : Equal
14. Which function can be used to determine the names assigned to a list?
Correct Answer is : Names
15. Joining two lists can be achieved either using the _________ function.
Correct Answer is : Concat
16. Which function gives the list as output?
Correct Answer is : Spline
17. Density function gives output as ________
Correct Answer is : Lists
18. Locator function gives output as ___________
Correct Answer is : Lists
19. The _________ function returns a list of densities (y) corresponding to bin values (x).
Correct Answer is : Spline
20. _________ is new package that makes it easy to “tidy” your data.
Correct Answer is : tidyneat
