Pluralsight - R Programming Fundamentals (2014) [147 mp4] Free Download

Pluralsight – R Programming Fundamentals (2014) [147 mp4]
English | Size: 0.98 GB (1,051,271,920 bytes )
Category: Pluralsight

R is a powerful and widely used open source software and programming environment for data analysis. Companies across the globe use R as an essential tool for various types of analysis to get key insights from data and to make key decisions. This course will provide everything you need to know to get started with the R framework, and contains a number of demos to provide hands-on practice in order to become an efficient and productive R programmer. By the end of this course, you will also learn to play with data and to extract key information using various R functions and constructs.

In this course, you will learn various constructs of R programming and get hands-on practice in order to become an efficient and productive R programmer.

by Abhishek Kumar

……Table of contents

……Getting Started 50:40

Course Introduction 3:11

R Overview 1:59

Why R? 6:23

Why Learn R Programming? 2:23

Install R on Windows 3:39

Install R on Linux 3:59

Install R on Mac 2:34

Hello World in R 6:41

Editors and IDEs for R 4:52

Install RStudio on Windows 1:56

Install RStudio on Linux 2:13

Install RStudio on Mac 1:49

RStudio Desktop Overview 8:05

Course Structure 0:48

……Getting Help for R 36:18

Introduction 0:45

Outline 0:34

Built-In Help 0:59

Built-In Help: Using Help Commands 5:52

Built-In Help: Using Demo Commands 3:57

Built-In Help: Using Vignettes 4:58

Web Search 8:31

Community Support 0:57

Community Support: Mailing List 1:35

Community Support: Forums 0:57

Community Support: Blogs 1:03

How to Ask a Question? 3:51

Summary 2:12

……R – Variables and Operators 47:32

Introduction 0:36

Outline 0:37

Variable 0:56

Naming Convention 1:25

Naming Guide 2:11

Assign Variable 3:03

Environments and Variables 6:56

Operators 1:02

Arithmetic Operators 6:57

Special Numbers : Inf, NaN, NA 6:10

Logical Operators 3:29

Vectorized Operations 2:25

Types of Vectorized Operations 9:20

Summary 2:16

……R – Data Structures (Part 1) 46:52

Introduction 1:20

Outline 0:49

Data Structures in R 3:33

Atomic Vector 11:17

Common Operations on Atomic Vectors 9:08

Factor 6:48

List 6:09

Common Operation on Lists 5:39

Summary 2:05

……R – Data Structures (Part 2) 36:19

Introduction 0:40

Outline 0:29

Data Frame 6:50

Common Operation on Data Frames 8:41

Matrix 6:41

Common Operation on Matrices 5:43

Array 4:56

Summary 2:16

……R – Functions 35:50

Introduction 0:44

Outline 0:57

Functions Overview 2:31

Demo: Functions Overview 4:29

Function Components 1:19

Function Naming Guidelines 1:22

Argument Matching 2:06

Arguments With Default Values 3:00

Additional Arguments Using Ellipsis 4:32

Lazy Evaluation 3:36

Multiple Return Values 2:31

Functions as Objects 3:48

Anonymous Function 2:38

Summary 2:10

……R – Flow Control 49:45

Introduction 0:58

Outline 1:02

If 4:52

If-Else 2:35

Multiple If-Else 4:09

Switch 5:39

Vectorized If 4:57

Repeat 1:57

Repeat With Break 2:10

Repeat With Next 2:27

While 2:49

For 2:26

Apply 1:51

Demo: Apply – Part 1 3:12

Demo: Apply – Part 2 4:32

Functions in Apply Family 0:46

Summary 3:13

……R – Packages 27:45

Introduction 0:58

Outline 0:28

About R Package 4:11

Load R Package 1:24

Demo: Load R Package – Part 1 3:58

Demo: Load R Package – Part 2 1:42

Install R Package 2:48

Demo: Install R Package 5:56

Manage R Package 3:47

Summary 2:28

……R – Import Data 38:48

Introduction 0:40

Outline 0:57

Working Directory 1:02

Demo: Working Directory 2:37

Import CSV Files 1:45

Demo: Import CSV Files 2:56

Import Table 2:24

Demo: Import Table 3:16

Import from URL 1:14

Demo: Import from URL 2:21

Import XML Files 0:27

Demo: Import XML Files 2:32

Import Excel Files 1:04

Demo: Import Excel Files 3:41

Import Other File Types 1:48

Import Built-In Datasets 1:08

Demo: Import Built-In Datasets 1:55

Import from Database 2:41

Demo: Import Database Using RODBC Package 2:31

Summary 1:43

……Exploring Data With R 50:44

Introduction 1:31

Outline 0:46

Types of Data 2:42

Overall Structure 0:33

Example Dataset 0:52

Demo: Overall Structure 2:16

Analysis of Continuous Data 0:29

Central Tendency (Mean) 1:25

Demo: Central Tendency (Mean) 1:07

Central Tendency (Median) 1:03

Demo: Central Tendency (Median) 0:57

Central Tendency: Why Not Sufficient? 1:31

Spread (Range) 1:01

Demo: Spread (Range) 1:23

Spread (Quartiles) 2:41

Demo: Spread (Quartiles) 2:07

Spread (Box Plot) 4:11

Demo: Spread (Box Plot) 2:35

Spread (Histogram) 1:17

Demo: Spread (Histogram) 1:23

Spread (Variance and Standard Deviation) 3:41

Demo: Spread (Variance and Standard Deviation) 1:09

Analysis of Categorical Data 0:36

Frequency Distribution 1:12

Demo: Frequency Distribution 1:46

Category Statistics 1:19

Demo: Category Statistics 6:42

Summary 2:16

Abhishek Kumar is a software architect and developer. His work focuses on developing enterprise level applications for process industries, especially in the area of optimization, pattern recognition, and fault detection.

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Pluralsight – R Programming Fundamentals (2014) [147 mp4]

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