R Tutorial

Fundamentals of R

Variables

Input and Output

Decision Making

Control Flow

Functions

Strings

Vectors

Lists

Arrays

Matrices

Factors

DataFrames

Object Oriented Programming

Error Handling

File Handling

Packages in R

Data Interfaces

Data Visualization

Statistics

Machine Learning with R

Creating, Listing, and Deleting Objects in Memory using R

Managing objects in R's memory is essential for keeping your R workspace organized and avoiding unnecessary memory consumption. Here's a tutorial on creating, listing, and deleting objects in R:

1. Creating Objects in R

Objects in R can be variables, data frames, vectors, lists, functions, etc.

1.1. Variables

x <- 10
y <- "Hello, R!"
z <- TRUE

1.2. Vectors

numeric_vector <- c(1, 2, 3, 4, 5)
character_vector <- c("apple", "banana", "cherry")

1.3. Data Frames

Using the built-in mtcars dataset as an example:

data(mtcars)
my_df <- mtcars[1:10,]

1.4. Lists

my_list <- list(name="John", age=25, scores=c(90, 85, 88))

2. Listing Objects in R

To see all the objects currently in your R workspace:

ls()

This will return a character vector of object names.

If you want more details about the objects, such as their type and size, you can use:

ls.str()

3. Deleting Objects in R

3.1. Deleting a Single Object

To delete a single object:

rm(x)   # This will remove the variable 'x' from the memory.

3.2. Deleting Multiple Objects

To remove multiple objects at once:

rm(y, z)   # This will remove both 'y' and 'z'.

3.3. Deleting All Objects

To clear your entire workspace:

rm(list=ls())

This is useful if you want to start fresh or if you have a large number of objects that you no longer need.

4. Checking Memory Usage

It's sometimes useful to check how much memory your R objects are consuming, especially with large datasets.

To get an overview of memory usage:

object.size(my_df)   # Returns the size of 'my_df' in bytes.

5. Saving and Loading Objects

5.1. Saving Objects to a File

You can save one or multiple objects to a file:

save(my_list, my_df, file="my_data.RData")

5.2. Loading Objects from a File

To load saved objects back into your R workspace:

load("my_data.RData")

Conclusion

Effectively managing objects in R's memory is crucial, especially when working on complex projects or dealing with large datasets. Regularly cleaning up unnecessary objects, saving important objects to files, and monitoring memory usage can help keep your R sessions efficient and organized.

Assigning variables and objects in R programming:

# Assigning a variable
x <- 5

# Creating a vector
my_vector <- c(1, 2, 3, 4, 5)

# Creating a data frame
my_df <- data.frame(Name = c("John", "Alice"), Age = c(25, 30))

Listing objects in R workspace:

# Listing objects in the workspace
ls()

Viewing and exploring objects in R:

# Viewing the contents of an object
print(my_vector)

# Exploring structure of an object
str(my_df)

# Summary statistics of an object
summary(my_vector)

Deleting objects from memory in R:

# Deleting a single object
rm(x)

# Deleting multiple objects
rm(my_vector, my_df)

Clearing R workspace and memory:

# Clearing the entire workspace
rm(list = ls())

# Alternatively, restart R session to clear all objects and memory

R ls() function for listing objects:
```
# Using ls() to list objects
ls()
```
- You can also use ls() with patterns to filter objects:
```
ls(pattern = "my_")
```