Complete R Programming course: Beginner to Advanced Level
Master R: Clear Understanding of Data Aggregation, Tidyverse, reshape, tidyr, dplyr, data.table packages and so on!
Ratings 4.03 / 5.00
What You Will Learn!
- Advanced data analytics with dplyr package
- Advanced analytics with datatable package
- How to perform sorting, subscripting, Merging of R Data structures
- Data Aggregartion using dplyr and data table packages
- Data Aggregation with aggregate function
- Data Analysis with Apply family of functions: apply(), sapply(), tapply(), lapply()
- Importing data into R using tidyverse package
- Restructuring real datasets with reshape package
- Restructuring real world datasets with melt and cast functions
- Restructuring real datasets with tidy package package
- Restructuring real world datasets with gather and spare functions
- How to work with categorical data
- what are factors in R?
- Regular expression with grep & gsub function
- if statements: nested in statements
- How to use the switch function in r
- Complete explanations of the for loops and while loops using R
- How to use loops within your own functions
- How to create, manage and subscript R Data Structures
- Complete explanation and Application of Vectors, Matrices and Arrays with real datasets
- Complete explanation and Application of Dataframes and Lists
- Calling R Functions & How to write your own functions
- R for Complicated mathematics formulae
- Master R 4.2
- What is the Pipe Operator & How to use it
Description
*Learn R Programming by Coding Along*
Are you starting you R programming journey? Are you a complete beginner in programming?
This course is suitable for for!
Why learn R using this course?
This course covers all the theory needed for the understanding of writing a well neat R code. The latest version of R and R Studio is used to cover all the required concepts for everyone who wants to have a career in the fields like:
Data Analyst
Quantitative Analyst
Data Scientists
Financial Analysts and many other high paying careers
By the end of this course you will have mastered:
1. The Basics of R
R Data Types
R for Basic Maths
Complicated Arithmetic formulas using R programming
2. Data Structures in R
Vectors
Matrices
Arrays
Data frames
Lists
3. Working with Categorical Data
What is categorical Data?
Factors in R programming – what are factors in r
Creating factors
Regular expression – grep and gsub functions in r
4. Functions in R
Calling R functions
Writing R functions
5. if statements
Stand-alone statement
else if & else statements
using if statements in functions
nested if statements
switch function
6. Loops
what is a loop?
for loops
while loops
nested loops
using loops within a function
7. The apply family of functions
apply function
lapply function
sapply function
tapply function
8. Importing Data into R with tidyverse
read a csv file in r
read an excel file in r with tidyverse
9. Data Manipulation & Transformation in R
Sorting, Appending and Merging
Duplicated Values
Restructuring with reshape package
Melting and Casting
Restructuring with tidyr package
Gather and spare
Data Aggregation
10. dplyr package
Sorting
Subscripting
Merging
Aggregation
What is the pipe operator in r?
11. data.table package
Setting Key & Subscripting
Merging & Aggregation
I'm certain you will enjoy this course!
Who Should Attend!
- Beginner R programmers curious about working with data
- R programmers who are looking for a unique way of learning R
- R programmers who are not in a rush to master everything at once
Tags
- R (programming language)
- Statistical Modeling
Subscribers
30
Lectures
122
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