R Tutorial

• Introduction to R Programming Language
• R vs Python
• Environments in R Programming
• Introduction to R Studio
• How to Install R Studio on Windows and Linux?
• Creation and Execution of R File in R Studio
• Clear the Console and the Environment in R Studio
• Hello World in R Programming

Fundamentals of R

• Basic Syntax
• Comments
• Operators
• Keywords
• Data Types

Variables

• Introduction to Variables
• Scope of Variable
• Dynamic Scoping
• Lexical Scoping
• Lexical Scoping vs Dynamic Scoping

Input and Output

• Taking Input from User
• Printing Output of R Program
• Print the Argument to the Screen - print() Function

Decision Making

• Decision Making - if, if-else, if-else-if ladder, nested if-else, and switch
• if statement
• if-else statement
• Switch case

Control Flow

• Introduction to Control Statements
• Loops (for, while, repeat)
• For loop
• while loop
• Repeat loop
• goto statement
• Break and Next statements
• Next Statement

Functions

• Introduction to Functions
• Function Arguments
• Types of Functions
• Recursive Functions
• Conversion Functions

Strings

• Introduction to Strings
• Working with Text
• String Manipulation
• Concatenate Two Strings
• String Matching
• How to find a SubString?
• Finding the length of string - nchar() method
• Adding elements in a vector - append() method
• Convert string from Lowercase to Uppercase - toupper() function
• Convert String from Uppercase to Lowercase - tolower() method
• Splitting Strings - strsplit() method
• Print a Formatted string - sprintf() Function

Vectors

• Introduction to Vectors
• Operations on Vectors
• Append Operation on Vectors
• Dot Product of Vectors
• Types of Vectors
• Assigning Vectors 
• Getting and Setting Length of the Vectors - length() Function
• Creating a Vector of sequenced elements - seq() Function
• Get the Minimum and Maximum element of a Vector - range() Function
• Formatting Numbers and Strings - format() Function
• Replace the Elements of a Vector - replace() Function
• Sorting of a Vector - sort() Function
• Convert elements of a Vector to Strings - toString() Function
• Extracting Substrings from a Character Vector - substring() Function

Lists

• Introduction to Lists
• Two Dimensional List
• Operations on Lists
• List of Vectors
• List of Dataframes
• Named List
• Check if the Object is a List - is.list() Function
• Convert an Object to List - as.list() Function
• Check if an Object of the Specified Name is Defined or not - exists() Function
• Apply a Function over a List of elements - lapply() Function
• Performing Operations on Multiple Lists simultaneously - mapply() Function

Arrays

• Introduction to Arrays
• Multidimensional Array
• Array Operations
• Sorting of Arrays
• Convert values of an Object to Logical Vector - as.logical() Function
• Performing different Operations on Two Arrays - outer() Function
• Intersection of Two Objects - intersect() Function
• Get Exclusive Elements between Two Objects - setdiff() Function

Matrices

• Introduction to Matrices
• Create Matrix from Vectors
• Operations on Matrices
• Matrix Multiplication
• Algebraic Operations on a Matrix
• Combining Matrices
• Matrix Transpose
• Inverse of Matrix
• Working with Sparse Matrices
• Check if the Object is a Matrix - is.matrix() Function
• Convert an Object into a Matrix - as.matrix() Function
• Get or Set Dimensions of a Matrix - dim() Function
• Calculate Cumulative Sum of a Numeric Object - cumsum() Function
• Compute the Sum of Rows of a Matrix or Array - rowSums Function

Factors

• Introduction to Factors
• Level Ordering of Factors
• Convert Factor to Numeric and Numeric to Factor
• Check if a Factor is an Ordered Factor - is.ordered() Function
• Convert an Unordered Factor to an Ordered Factor  - as.ordered() Function
• Checking if the Object is a Factor - is.factor() Function
• Convert a Vector into Factor - as.factor() Function

DataFrames

• Introduction to Data Frames
• Matrix vs Dataframe
• DataFrame Operations
• DataFrame Manipulation
• Joining of Dataframes
• The Factor Issue in a DataFrame
• Data Reshaping
• Creating a Data Frame from Vectors
• Data Wrangling - Data Transformation
• Data Wrangling - Working with Tibbles
• Melting and Casting
• Subsetting of DataFrames
• Handling Missing Values
• Convert an Object to Data Frame - as.data.frame() Function
• Get the number of columns of an Object - ncol() Function
• Get the number of rows of an Object - nrow() Function
• Get Addition of the Objects passed as Arguments - sum() Function
• Create Subsets of a Data frame - subset() Function

Object Oriented Programming

• Introduction to Object-Oriented Programming
• Classes
• Objects
• Encapsulation
• Polymorphism
• Inheritance
• Abstraction
• Looping over Objects
• Creating, Listing, and Deleting Objects in Memory
• S3 class
• Explicit Coercion
• R6 Classes
• Getting attributes of Objects - attributes() and attr() Function
• Get or Set names of Elements of an Object - names() Function
• Get the Minimum element of an Object - min() Function
• Get the Maximum element of an Object - max() Function

Error Handling

• Introduction to Error Handling
• Condition Handling
• Debugging in R Programming

File Handling

• Introduction to File Handling
• Reading Files
• Writing to Files
• Read Lines from a File - readLines() Function
• Working with Binary Files

Packages in R

• Introduction to Packages
• dplyr Package
• ggplot2 package
• Grid and Lattice Packages
• Shiny Package
• tidyr Package
• What Are the Tidyverse Packages?
• Data Munging

Data Interfaces

• Data Handling
• Importing Data in R Script
• How To Import Data from a File?
• Exporting Data from scripts 
• Working with CSV files 
• Working with XML Files
• Working with Excel Files
• Working with JSON Files 
• Reading Tabular Data from files
• Working with Databases
• Database Connectivity
• Manipulate Data Frames Using SQL

Data Visualization

• Graph Plotting
• Graphical Models
• Plotting Graphs using Two Dimensional List
• Data Visualization
• Charts and Graphs
• Add Titles to a Graph
• Adding Colors to Charts
• Adding Text to Plots
• Adding axis to a Plot
• Set or View the Graphics Palette
• Plotting of Data using Generic plots
• Bar Charts
• Line Graphs
• Adding Straight Lines to a Plot
• Addition of Lines to a Plot
• Histograms
• Pie Charts
• Scatter plots
• Create One Dimensional Scatterplots
• Create a Plot Matrix of Scatterplots
• Create Dot Charts
• Boxplots in R Language
• Stratified Boxplot
• Create a Heatmap
• Pareto Chart
• Waffle Chart
• Draw a Quantile-Quantile Plot
• Creating 3D Plots
• Describe Parts of a Chart in Graphical Form
• Principal Component Analysis
• Social Network Analysis

Statistics

• Introduction to Statistics
• Calculate the Mean, Median, and Mode
• Calculate the Average, Variance, and Standard Deviation
• Homogeneity of Variance Test
• Covariance and Correlation 
• Correlation Matrix
• Visualize correlation matrix using correlogram 
• Distance Matrix by GPU 
• Descriptive Analysis
• Normal Distribution 
• Binomial Distribution 
• Compute the Negative Binomial Density
• Poisson Functions
• ANOVA Test
• MANOVA Test
• Naive Bayes Classifier
• K-NN Classifier
• Central Tendency
• Variability
• Skewness and Kurtosis
• Absolute and Relative Frequency
• Permutation Hypothesis Test
• AB Testing
• Completely Randomized Design
• Randomized Block Design
• Bartlett’s Test
• Tree Entropy
• Compute Summary Statistics of Subsets
• Hypothesis Testing
• Bootstrapping
• Time Series Analysis
• T-Test Approach

Machine Learning with R

• Introduction to Machine Learning
• Setting up Environment for Machine Learning
• Supervised and Unsupervised Learning
• Classification
• Regression and its Types
• Regression Analysis
• Decision Tree
• Random Forest Approach
• Root-Mean-Square Error
• Clustering
• Hierarchical Clustering
• DBScan Clustering
• Deep Learning
• Building a Simple Neural Network
• How Neural Networks are used for Regression?
• Multi Layered Neural Networks
• Survival Analysis
• Stem and Leaf Plots

Adding axis to a Plot in R

In R, the base graphics system provides a straightforward way to produce plots and customize them. One of the common customizations is adding and adjusting the axes. In this tutorial, I'll guide you through adding and customizing axes to a basic scatter plot using R's base graphics.

1. Creating a Basic Scatter Plot:

We'll start by creating a basic scatter plot using plot():

# Sample data
x <- c(1, 2, 3, 4, 5)
y <- c(1.1, 2.1, 3.1, 4.2, 5)

# Basic scatter plot
plot(x, y, xlab="", ylab="", xaxt="n", yaxt="n")

The parameters xlab and ylab are set to empty to remove axis labels initially. The xaxt="n" and yaxt="n" options remove the x and y axes respectively.

2. Adding Custom Axes:

Now, we will add custom axes to the plot:

# Add x-axis at the bottom
axis(side=1, at=seq(1, 5, 1))

# Add y-axis on the left
axis(side=2, at=seq(1, 6, 1))

The side parameter determines the side on which the axis is drawn:

• 1 = bottom
• 2 = left
• 3 = top
• 4 = right

The at parameter specifies the locations at which tick marks are to be drawn.

3. Customizing Axes:

3.1. Custom Labels:

You can provide custom labels to the axis ticks using the labels parameter:

axis(side=1, at=seq(1, 5, 1), labels=c("one", "two", "three", "four", "five"))

3.2. Change Axis Line and Tick Marks:

To modify the appearance of the axis line and tick marks, you can use the lty, lwd, and tck parameters:

axis(side=2, at=seq(1, 6, 1), lty=2, lwd=2, tck=-0.02)

Here, lty is the line type, lwd is the line width, and tck is the length of the tick mark (negative value indicates the tick marks are drawn inside the plot area).

3.3. Adding Axis Labels:

mtext(text="X-Axis Label", side=1, line=3)
mtext(text="Y-Axis Label", side=2, line=3)

The line parameter indicates the number of lines away from the plot at which the text should be written.

4. Finishing the Plot:

You can add other elements, such as a title or grid lines, to finish off your plot:

title("Scatter Plot with Custom Axes")
grid()

This tutorial gives you a basic overview of how to add and customize axes in R's base graphics system. Remember, there are other packages like ggplot2 that provide even more flexible and powerful plotting capabilities.

1. R plot add axis example: Add custom axes to a plot in R:

   # R plot add axis example
   x <- c(1, 2, 3, 4, 5)
   y <- c(2, 4, 6, 8, 10)
   plot(x, y, type = "l", col = "blue", xlab = "X-axis", ylab = "Y-axis")
   

2. Add x-axis and y-axis labels in R plot: Label the x-axis and y-axis for better clarity:

   # Adding axis labels
   x <- c(1, 2, 3, 4, 5)
   y <- c(2, 4, 6, 8, 10)
   plot(x, y, type = "l", col = "blue", xlab = "Time", ylab = "Value")
   

3. Change axis ticks in R plot: Modify axis ticks to control the intervals:

   # Changing axis ticks
   plot(x, y, type = "l", col = "blue", xaxt = "n")
   axis(1, at = c(1, 3, 5), labels = c("Jan", "Mar", "May"))
   

4. Adjusting axis limits in R plot: Set custom axis limits for a specific range:

   # Adjusting axis limits
   plot(x, y, type = "l", col = "blue", ylim = c(0, 12))
   

5. Rotating axis labels in R plot: Rotate axis labels for better readability:

   # Rotating axis labels
   plot(x, y, type = "l", col = "blue", xlab = "Time", ylab = "Value")
   par(las = 2)  # Rotate x-axis labels
   

6. Multiple axes in a single R plot: Display multiple axes in a single plot:

   # Multiple axes
   x <- seq(0, 2 * pi, length.out = 100)
   y1 <- sin(x)
   y2 <- cos(x)
   par(mar = c(5, 4, 4, 5) + 0.1)
   plot(x, y1, type = "l", col = "blue", xlab = "Angle", ylab = "sin(x)")
   par(new = TRUE)
   plot(x, y2, type = "l", col = "red", xaxt = "n", yaxt = "n", xlab = "", ylab = "")
   

7. Hide axis in R plot: Hide one or both axes in an R plot:

   # Hide axis
   plot(x, y, type = "l", col = "blue", xaxt = "n", yaxt = "n", xlab = "", ylab = "")
   

8. Logarithmic axis in R plot: Use a logarithmic scale for one or both axes:

   # Logarithmic axis
   x <- c(1, 10, 100, 1000)
   y <- c(2, 4, 6, 8)
   plot(x, y, type = "l", col = "blue", log = "x")
   

9. Secondary axis in R plot: Add a secondary axis to the plot:

   # Secondary axis
   x <- seq(0, 10, by = 1)
   y1 <- x^2
   y2 <- x^3
   plot(x, y1, type = "l", col = "blue", xlab = "X", ylab = "Y1")
   par(new = TRUE)
   plot(x, y2, type = "l", col = "red", xlab = "", ylab = "", axes = FALSE)
   axis(side = 4)