R interview questions part 29
R interview questions part 29
Take as many assements as you can to improve your validate your skill rating
Total Questions: 20
1. What is NaN called?
Correct Answer is : Not a Number
2. How can we define ‘infinity’ in R language?
Correct Answer is : Inf
3. How can we define ‘infinity’ in R language?
Correct Answer is : Inf
4. What is the output of the following code? y <- c(TRUE, 2)
Correct Answer is : [1] 1 2
5. What is the output of the following code? y <- c(TRUE, 2)
Correct Answer is : [1] 1 2
6. What is the class defined by the following code? y<-c(2,”t”)
Correct Answer is : Character
7. What is the class defined by the following code? y<-c(2,”t”)
Correct Answer is : Character
8. What is the class defined in the following code? y<-c(FALSE,2)
Correct Answer is : Numeric
9. Which one of the following is not a basic datatype?
Correct Answer is : Data frame
10. How do you create an integer suppose 5 in R?
Correct Answer is : 5L
11. What is the output of the following code? x<- c (“a”,” b”) as.numeric(x)
Correct Answer is : [1] NA NA (Warning message: NAs introduced by coercion)
12. The dimension attribute is itself an integer vector of length _______
Correct Answer is : 2
13. How could be the matrix constructed by using the following code? m <- matrix(1:6, nrow = 2, ncol = 3)
Correct Answer is : column-wise
14. Matrices can be created by row-binding with the help of the following function.
Correct Answer is : rbind()
15. What is the function used to test objects (returns a logical operator) if they are NA?
Correct Answer is : is.na()
16. What is the function used to test objects (returns a logical operator) if they are NaN?
Correct Answer is : is.nan()
17. What is the function to set column names for a matrix?
Correct Answer is : colnames()
18. ______ let’s you perform SQL queries on your R data frames.
Correct Answer is : plyr
19. ______ splits a data frame and results an array (hence the da). Hopefully you’re getting the idea here.
Correct Answer is : daply
20. ________ makes it incredibly easy to fit time series models like ARIMA, ARMA, AR, Exponential Smoothing, etc.
Correct Answer is : forecast
