Input Data in R Language: c() & scan() Function

Introduction to Input Data in R Language

There are many ways to input data in R Language. Here, I will concentrate only on typing data directly at the keyboard using c() and scan() functions, which are very common ways to input data in R language.

Traditional statistical computer software such as Minitab, SPSS, and SAS, etc., are designed to transform rectangular datasets (a dataset whose rows represent the observations and columns represent the variables) into printed reports and graphs. However, R and S languages are designed to transform data objects into other data objects (such as reports, and graphs).

S and R language both support rectangular datasets, in the form of data frames and other data structures. Here we will learn to know about data in R to work efficiently as a statistical data analyst.

Data Input Functions in R

There are many ways to input data in R and S-Plus. Let us learn to type data directly on the keyboard.

Input Data Using c() Function

The best choice is to enter small datasets directly on the keyboard. Remember that it is impractical to enter a large data set directly at the keyboard.

Let us use the c() function to enter the vector of numbers directly as:

x    <- c(1, 3, 5, 7, 9)
char <- c('a', 'b', 'c', 'd')
TF   <- c(TRUE, FALSE)
Input Data in R Language

Note that the character strings can be directly inputted in single or double quotation marks. For example, "a" and 'a' both are equivalent.

Input Data Using Scan() Function in R

It is also very convenient to use the scan() function in R, which prompts with the index of the next entry.  Consider the example,

xyz <- scan()
1: 10 20 30 35
5: 40 35 25
8: 9 100 50
11:
Read 10 items

The number before the colon on each of the inputted lines is the index of the next data entry point (observation) to be entered. Note that entering a blank line terminates the scan() function input behavior.

Click the following links to learn about data entry (import and export internal and external data) in R Language

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This quiz “R Language Test” will help you to check your ability to execute some basic operations on objects in the R language, and it will also help you to understand some basic concepts. This quiz about R Language Test will help you to improve your computational understanding. Let us start with R Language Test Quiz.

Online MCQs about R Programming Language with Answers

1. When working in R, for which part of the data analysis process do analysts use the tidyr package?

 
 
 
 

2. ____ ____is used to apply a function over subsets of a vector

 
 
 
 

3. Which of the following is a base package for the R language?

 
 
 
 

4. An analyst is checking the value of the variable x using a logical operator, so they run the following code:

x > 35 & x < 65

Which values of x would return TRUE when the analyst runs the code? Select all that apply.

 
 
 
 

5. Which of the following method make a vector of repeated values?

 
 
 
 

6. _______ applies a function over the margins of an array

 
 
 
 

7. R comes with a ________ to help you optimize your code and improve its performance.

 
 
 
 

8. What would be the output of the following code?

> x <- 1:4
> y <- 6:9
> z <- x + y
> z

 
 
 
 

9. R functionality is divided into a number of

 
 
 
 

10. Why would a data analyst want to use the CRAN network when working with RStudio?

 
 
 
 

11. Which of the following is an example of a vectorized operation for subtraction operation

> x<- 1:4
> y<- 6:9

 
 
 
 

12. The lapply( ) function takes _______ arguments

 
 
 
 
 

13. _______ loop over a list and evaluate a function on each element

 
 
 
 

14. Which of the following is used for Statistical analysis in R language?

 
 
 
 

15. What would be the output of the following code?
> x <- 1:4
> x > 2

 
 
 
 

16. ______ function is same as lapply( )

 
 
 
 

17. The ________ function takes a vector or other objects and splits it into groups determined by a factor or list of factors.

 
 
 
 

18. What would be the value of the following expression?

> log(-1)

 
 
 
 

19. The debug( ) flags a function for ______ mode in R mode.

 
 
 
 

20. A matrix is _______ dimensional rectangular data set.

 
 
 
 

The R language Test covers some looping functions such asapply(), lapply(), mapply(), sapply(), and tapply(). Results from the execution of r codes are also asked.

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Online R Language Test

  • Which of the following is a base package for the R language?
  • R comes with a to help you optimize your code and improve its performance.
  • The debug( ) flags a function for mode in R mode.
  • A matrix is _________ a dimensional rectangular data set.
  • The function takes a vector or other objects and splits it into groups determined by a factor or list of factors.
  • The lapply( ) function takes arguments
  • ________is used to apply a function over subsets of a vector
  • ________ applies a function over the margins of an array
  • _________ function is the same as lapply( ) __________ loop over a list and evaluate a function on each element
  • Which of the following methods makes a vector of repeated values?
  • Which of the following is used for Statistical analysis in R language?
  • R functionality is divided into a number of
  • Which of the following is an example of a vectorized operation for subtraction operation > x<- 1:4 > y<- 6:9 What would be the output of the following code? > x <- 1:4 > y <- 6:9 > z <- x + y > z
  • What would be the output of the following code? > x <- 1:4 > x > 2
  • What would be the value of the following expression? > log(-1)
  • “An analyst is checking the value of the variable x using a logical operator, so they run the following code:x > 35 & x < 65
    Which values of x would return TRUE when the analyst runs the code? Select all that apply.”
  • When working in R, for which part of the data analysis process do analysts use the tidyr package?
  • Why would a data analyst want to use the CRAN network when working with RStudio?

R Programming Language

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MCQs R Programming Language 2

This quiz “MCQs R Programming Language” will help you to check your ability to execute some basic operations on objects in the R language, and it will also help you to understand some basic concepts. This MCQs R Programming Language Quiz will also improve computational understanding. Let us start with the test “MCQs R Programming Language” with Answers.

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MCQs R Programming Language 1

  • The R language is a dialect of which of the following programming languages?
  • The definition of free software consists of four freedoms (freedoms 0 through 3). Which of the following is NOT one of the freedoms that are part of the definition?
  • In R language the following are all atomic data types EXCEPT
  • If I execute the expression x <- 4 in R language, what is the class of the object “x” as determined by the “class()” function?
  • What is the class of the object defined by the expression x <- c(4, “a”, TRUE)?
  • If I have two vectors x <- c(1,3, 5) and y <- c(3, 2, 10), what is produced by the expression rbind(x, y)?
  • A key property of vectors in R language is that
  • Suppose I have a list defined as x <- list(2, “a”, “b”, TRUE). What does x[[2]] give me?
  • Suppose I have a vector x <- c(3, 5, 1, 10, 12, 6) and I want to set all elements of this vector that are less than 6 to be equal to zero. What R code achieves this?
  • ____________ is a function in R to get the number of observations in a data frame
  • What function is used to test the missing observation in a data frame
  • Which of the following statements about RStudio’s integrated development environment are correct?
  • Suppose I have a vector x <- 1:4 and y <- 2:3. What is produced by the expression x + y?
  • Which of the following statements about RStudio’s integrated development environment are correct?
  • A data analyst writes the code summary(penguins) to display a summary of the penguins dataset. Where in RStudio can the analyst execute the code?
  • What should you use to assign a value to a variable in R?
  • Which of the following examples is the proper syntax for a function in R?
  • What is the benefit of using the R programming language for data analysis?
  • Which of the following examples can you use in R for date/time data?
  • A data analyst inputs the following calculation in their R programming: $$basket_1 * 20 + basket_2 * 15 $$ Which arithmetic operators are the analyst using?
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