- Installing R and R Studio
- The RStudio Interface
- Installing and Activating R Packages
- Setting the Working Directory
- Basic Operations in R
- Working With Variables
Online
₹ 449 2,999
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 449 ₹2,999
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
Introduction
Getting Started with R
Vectors
- Creating Vectors With the c() Function
- Creating Vectors Using the Colon Operator
- Creating Vectors With the rep() Function
- Creating Vectors With the seq() Function
- Creating Vectors of Random Numbers
- Creating Empty Vectors
- Indexing Vectors With Numeric Indices
- Indexing Vectors With Logical Indices
- Naming Vector Components
- Filtering Vectors
- The Functions all() and any()
- Sum and Product of Vector Components
- Vectorized Operations
- Treating Missing Values in Vectors
- Sorting Vectors
- Minimum and Maximum Values
- The ifelse() Function
- Adding and Multiplying Vectors
- Testing Vector Equality
- Vector Correlation
- Bonus Lecture: Learn Statistics with R
- Practical Exercises
Matrices and Arrays
- Creating Matrices With the matrix() Function
- Creating Matrices With the rbind() and cbind() Functions
- Naming Matrix Rows and Columns
- Indexing Matrices
- Filtering Matrices
- Editing Values in Matrices
- Adding and Deleting Rows and Columns
- Minima and Maxima in Matrices
- Applying Functions to Matrices (1)
- Applying Functions to Matrices (2)
- Applying Functions to Matrices (3)
- Adding and Multiplying Matrices
- Other Matrix Operations
- Creating Multidimensional Arrays
- Indexing Multidimensional Arrays
- Practical Exercises
Lists
- Create Lists With the list() Function
- Create Lists With the vector() Function
- Indexing Lists With Brackets
- Indexing Lists Using Objects Names
- Editing Values in Lists
- Adding and Removing List Objects
- Applying Functions to Lists
- Practical Example of List: the Regression Analysis Output
- Bonus Lecture: Data Analysis in R
- Practical Exercises
Factors
- Working With Factors
- Splitting a Vector By a Factor Levels
- The tapply() Function
- The by() Function
- Practical Exercises
Data Frames
- Creating Data Frames
- Loading Data Frames From External Files
- Writing Data Frames in External Files
- Indexing Data Frames As Lists
- Indexing Data Frames As Matrices
- Selecting a Random Sample of Entries
- Filtering Data Frames
- Editing Values in Data Frames
- Adding Rows and Columns to Data Frames
- Naming Rows and Columns in Data Frames
- Applying Functions to Data Frames
- Sorting Data Frames
- Shuffling Data Frames
- Merging Data Frames
- Practical Exercises
Program Structures
- For Loops
- While Loops
- Repeat Loops
- Nested For Loops
- Conditional Statements
- Nested Conditional Statements
- Loops and Conditional Statements
- User Defined Functions
- The Return Command
- More Complex Functions Examples
- Checking Whether an Integer Is a Perfect Square
- A Custom Function That Solves Quadratic Equations
- Binary Operations
- Practical Exercises
Working with Strings
- Creating Strings
- Printing Strings
- Concatenating Strings
- String Manipulation (1)
- String Manipulation (2)
- String Manipulation (3)
- Functions for Finding Patterns in Strings
- Functions for Replacing Patterns in Strings
- Regular Expressions
- Practical Exercises
Plotting in Base R
- Building Scatterplot Charts
- Setting Graphical Parameters (1)
- Setting Graphical Parameters (2)
- Adding a Trend Line to a Scatterplot
- Building a Clustered Scatterplot
- Plotting a Line Chart
- Setting the Line Parameters
- Overplotting Lines and Dots
- Plotting Two Lines in the Same Chart
- Plotting Bar Charts
- Setting the Bar Parameters
- Plotting Histograms
- Plotting Density Lines
- Plotting Pie Charts
- Plotting Boxplot Charts
- Plotting Functions
- Exporting Charts
- Bonus Lecture: More Advanced Plotting
- Practical Exercises
Download Links
- R Files and Data Frames