R Programming - (LAB PROGRAMS)

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Aim:

☛  Implement different data structures in R (Vectors, Lists, Data Frames)

Solution :

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Vectors in R:

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In R, a vector is a basic data structure used to store multiple values of the same type.It is a one-dimensional data structure and can hold numeric, character, logical, or other atomic types.

In R, To create a vector, we use c() function(combine function) and in this, the elements are separated by a comma(,).

Syntax:

vect_name<- c(e1,e2,e3,..)

Example:

Filename: VectorEx.R

# Numeric vector
numbers <- c(10, 20, 30, 40)
print("Numeric Vector:")
print(numbers)

# Character vector
subjects <- c("Math", "Science", "History")
print("Character Vector:")
print(subjects)

# Logical vector
flags <- c(TRUE, FALSE, TRUE)
print("Logical Vector:")
print(flags)

Output:

[1] "Numeric Vector:"
[1] 10 20 30 40
[1] "Character Vector:"
[1] "Math"    "Science" "History"
[1] "Logical Vector:"
[1]  TRUE FALSE  TRUE

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Lists in R

A list is a collection of elements of different types. Lists are particularly useful when you need to store heterogeneous data.

In other words, A list is a flexible data structure that can store elements of different types, including numbers, characters, vectors, matrices, other lists, and even functions.

In R, To create a list, we use list() function and in this, the elements are separated by a comma(,).

Syntax:

list_name<- list(e1,e2,e3,..)

Example:

Filename: ListEx.R

# Creating a list with different types
student <- list(
  name = "John",
  age = 21,
  scores = c(85, 90, 95),
  pass = TRUE
)

print("List Example:")
print(student)

# Accessing list elements
print(paste("Student name is", student$name))

Output:

[1] "List Example:"
$name
[1] "John"

$age
[1] 21

$scores
[1] 85 90 95

$pass
[1] TRUE

[1] "Student name is John"

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Data Frames in R

In R, A data frame is a two-dimensional array-like structure, or we can say it is a table in which each column contains the value of one variable, and row contains the set of value from each column. Data Frames are two-dimensional, heterogeneous data structures.

In R, To create a data frame we use the data.frame() function.

Syntax:

df <- data.frame(vector1, vector2, ..)

Example:

Filename: DataFrameEx.R

# Creating a data frame
students <- data.frame(
   Names = c("Madhu", "Durga", "Naveen"),
   Ages = c(22, 23, 21),
   Scores = c(85.5, 90.0, 78.5)
 )

print("Data Frame Example:")
print(students)

# Accessing a column
print("Names of students:")
print(students$Names)

Output:

[1] "Data Frame Example:"
   Names Ages Scores
1  Madhu   22   85.5
2  Durga   23   90.0
3 Naveen   21   78.5
[1] "Names of students:"
[1] "Madhu"  "Durga"  "Naveen"

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Related Content :

R Programming Lab Programs

1) Download and install R-Programming environment and install basic packages using install. packages() command in R.   View Solution

2) Learn all the basics of R-Programming (Data types, Variables, Operators etc,.)   View Solution

3) Write R command to
i) Illustrate summation, subtraction, multiplication, and division operations on vectors using vectors.
ii) Enumerate multiplication and division operations between matrices and vectors in R console   View Solution

4) Write R command to
i) Illustrates the usage of Vector subsetting and Matrix subsetting
ii) Write a program to create an array of 3×3 matrixes with 3 rows and 3 columns.   View Solution

5) Write an R program to draw i) Pie chart ii) 3D Pie Chart, iii) Bar Chart along with chart legend by considering suitable CSV file   View Solution

6) Create a CSV file having Speed and Distance attributes with 1000 records. Write R program to draw
i) Box plots
ii) Histogram
iii) Line Graph
iv) Multiple line graphs
v) Scatter plot
to demonstrate the relation between the cars speed and the distance.   View Solution

7) Implement different data structures in R (Vectors, Lists, Data Frames)   View Solution

8) Write an R program to read a csv file and analyze the data in the file using EDA (Explorative Data Analysis) techniques.   View Solution

9) Write an R program to illustrate Linear Regression and Multi linear Regression considering suitable CSV file   View Solution

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