# R Programming For Absolute Beginners

Learn the basics of writing code in R - your first step to become a data scientist

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# R Programming For Absolute Beginners

## What you'll learn

## Requirements

ConClusion

**If you have decided to learn R as your data science programming language, you have made an excellent decision!**

R is the most widely used tool for statistical programming. It is powerful, versatile and easy to use. It is the first choice for thousands of data analysts working in both companies and academia. This course will help you master the basics of R in a short time, as a first step to become a skilled R data scientist.

The course is meant for absolute beginners, so you don’t have to know anything about R before starting. (You don’t even have to have the R program on your computer; I will show you how to install it.) But after graduating this course you will have the most important R programming skills – and you will be able to further develop these skills, by practicing, starting from what you will have learned in the course.

This course contains about 100 video lectures in nine sections.

11 sections • 119 lectures • 9h 32m total length

- Preview04:22

- Preview05:44
The RStudio Interface

12:58Installing and Activating R Packages

04:44Setting the Working Directory

02:14Basic Operations in R

03:17Working With Variables

10:23

Creating Vectors With the c() Function

05:57Creating Vectors Using the Colon Operator

04:03Creating Vectors With the rep() Function

04:30Creating Vectors With the seq() Function

07:42Creating Vectors of Random Numbers

08:05Creating Empty Vectors

03:13Indexing Vectors With Numeric Indices

09:44Indexing Vectors With Logical Indices

01:33Naming Vector Components

01:51Filtering Vectors

08:11The Functions all() and any()

06:24Sum and Product of Vector Components

02:56Vectorized Operations

07:13Treating Missing Values in Vectors

03:24Sorting Vectors

03:35Minimum and Maximum Values

02:10The ifelse() Function

07:00Adding and Multiplying Vectors

03:09Testing Vector Equality

09:16Vector Correlation

04:11Bonus Lecture: Learn Statistics with R

00:05Practical Exercises

00:05

Creating Matrices With the matrix() Function

07:42Creating Matrices With the rbind() and cbind() Functions

03:26Naming Matrix Rows and Columns

02:32Indexing Matrices

10:14Filtering Matrices

04:37Editing Values in Matrices

03:17Adding and Deleting Rows and Columns

07:46Minima and Maxima in Matrices

04:34Applying Functions to Matrices (1)

03:27Applying Functions to Matrices (2)

10:25Applying Functions to Matrices (3)

04:08Adding and Multiplying Matrices

03:08Other Matrix Operations

04:52Creating Multidimensional Arrays

06:31Indexing Multidimensional Arrays

05:12Practical Exercises

00:06

Create Lists With the list() Function

07:30Create Lists With the vector() Function

02:00Indexing Lists With Brackets

06:32Indexing Lists Using Objects Names

03:49Editing Values in Lists

02:48Adding and Removing List Objects

03:32Applying Functions to Lists

09:30Practical Example of List: the Regression Analysis Output

07:08Bonus Lecture: Data Analysis in R

00:05Practical Exercises

00:05

Working With Factors

12:50Splitting a Vector By a Factor Levels

03:41The tapply() Function

03:03The by() Function

03:03Practical Exercises

00:05

Creating Data Frames

06:00Loading Data Frames From External Files

06:56Writing Data Frames in External Files

03:40Indexing Data Frames As Lists

04:34Indexing Data Frames As Matrices

06:50Selecting a Random Sample of Entries

04:04Filtering Data Frames

05:56Editing Values in Data Frames

03:20Adding Rows and Columns to Data Frames

06:14Naming Rows and Columns in Data Frames

02:47Applying Functions to Data Frames

05:28Sorting Data Frames

06:49Shuffling Data Frames

02:02Merging Data Frames

06:06Practical Exercises

00:05

For Loops

11:29While Loops

05:59Repeat Loops

03:00Nested For Loops

06:52Conditional Statements

07:51Nested Conditional Statements

02:24Loops and Conditional Statements

04:09User Defined Functions

07:47The Return Command

04:40More Complex Functions Examples

05:04Checking Whether an Integer Is a Perfect Square

03:29A Custom Function That Solves Quadratic Equations

04:11Binary Operations

05:10Practical Exercises

00:06

Creating Strings

07:14Printing Strings

11:31Concatenating Strings

08:21String Manipulation (1)

03:51String Manipulation (2)

06:42String Manipulation (3)

02:13Functions for Finding Patterns in Strings

11:35Functions for Replacing Patterns in Strings

02:21Regular Expressions

16:30Practical Exercises

00:05

Building Scatterplot Charts

03:21Setting Graphical Parameters (1)

07:50Setting Graphical Parameters (2)

06:44Adding a Trend Line to a Scatterplot

01:32Building a Clustered Scatterplot

06:30Plotting a Line Chart

01:54Setting the Line Parameters

04:12Overplotting Lines and Dots

02:40Plotting Two Lines in the Same Chart

03:11Plotting Bar Charts

02:35Setting the Bar Parameters

02:04Plotting Histograms

03:07Plotting Density Lines

02:38Plotting Pie Charts

04:58Plotting Boxplot Charts

03:53Plotting Functions

02:14Exporting Charts

04:13Bonus Lecture: More Advanced Plotting

00:08Practical Exercises

00:05

R Files and Data Frames

00:01

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