Introduction to R Programming [Video]

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Introduction to R Programming [Video]

Selva Prabhakaran

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Practice and apply R programming concepts for effective statistical and data analysis
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Video Details

ISBN 139781786463869
Course Length3 hours 46 minutes

Video Description

Data is everywhere, and statisticians and analysts everywhere need to handle this data efficiently and tactfully. In comes R, a powerful programming language, arming developers with the tools to cater to their needs. This course will give you everything you need to start making software that can unlock your statistics and data.

The course is broken down into three parts. The first part will introduce R Studio and the basics of R—using packages and teaching you programming concepts such as variables, vectors, arrays, loops, and matrices. By solving coding challenges, you will gain a strong foundation for data munging.

With the basics mastered, we will take you through a number of topics such as handling dates with the lubridate package, handling strings with the stringr package, writing functions, debugging, error handling, and writing an apply family of functions. When you’ve mastered data munging, we’ll focus on visualizing data using base graphics.

Naturally, the next step is to learn how to make statistical inferences. We walk you through the fundamentals of univariate and bivariate analysis, computing confidence intervals, interpreting p values, and working with statistical significance. You’ll see how and when to use some of the commonly used statistical tests. With that, you will be ready for your first full-scale data analysis project to test the skills you’ve learned.

Finally, you will glimpse two powerful packages for data munging, the dplyr and data.table, which have both seen a rise in the R community. It is imperative to learn about both of these packages because much modern R code has been written using them.

With the help of interesting examples and coding challenges, this course will ensure that you have all the hacks and tricks you need to get started with R.

Style and Approach

You’ll learn all of R fundamentals and establish a strong understanding of the concepts behind data analysis. The course follows a pragmatic approach where you’ll find step-by-step instructions of the functions, tools, and concepts, and the reason you’re learning about them. Most of the videos on the course close with coding challenges, putting your newly learned skills into practical use immediately.

Table of Contents

Installation and Setup
The Course Overview
Installing R
Installing RStudio
Installing Packages
Working with Vectors
Data Types and Data Structures
Vectors
Random Numbers, Rounding, and Binning
Missing Values
The which() Operator
R Essentials
Lists
Set Operations
Sampling and Sorting
Check Conditions
For Loops
Dataframes and Matrices
Dataframes
Importing and Exporting Data
Matrices and Frequency Tables
Merging Dataframes
Aggregation
Melting and Cross Tabulations with dcast()
Core Programming
Dates
String Manipulation
Functions
Debugging and Error Handling
Fast Loops with apply()
Fast Loops with sapply(), lapply() and vapply()
Making Plots with Base Graphics
Creating and Customizing an R Plot
Drawing Plots with 2 Y Axes
Multiplots and Custom Layouts
Creating Basic Graph Types
Statistical Inference
Univariate Analysis
Normal Distribution, Central Limit Theorem, and Confidence Intervals
Correlation and Covariance
Chi-sq Statistic
ANOVA
Statistical Tests
R Very Own Project
Project 1 – Data Munging and Summarizing
Project 2 – Visualization with Base Graphics
Project 3 – Statistical Inference
DPlyR and Pipes
Pipes with Magrittr
The 7 Data Manipulation Verbs
Aggregation and Special Functions
Two Table Verbs
Working With Databases
data.table
Understanding Basics, Filter, and Select
Understanding Syntax, Creating and Updating Columns
Aggregating Data, .N, and .I
Chaining, Functions, and .SD
Fast Loops with set(), Keys, and Joins

What You Will Learn

  • Create and master the manipulation of vectors, lists, dataframes, and matrices
  • Write conditional control structures, and debug and handle errors for efficient error handling
  • See how to use the apply family of functions and write functions used within the apply function.
  • Handle dates using lubridate and manipulate strings with stringr package
  • Melt, reshape, aggregate, and cross-tabulate with dcast from dataframes
  • Make and customize various types of charts in base graphics for exceptional data representation
  • Perform univariate and bivariate analysis and do statistical tests
  • Work with databases without having to write SQL using the dplyr package
  • Write readable and expressive code using pipes from magrittr and dplyr’s verbs
  • Perform efficient, high-speed data munging with data.table
  • Work on a full-scale data analysis / data munging project

Authors

Table of Contents

Installation and Setup
The Course Overview
Installing R
Installing RStudio
Installing Packages
Working with Vectors
Data Types and Data Structures
Vectors
Random Numbers, Rounding, and Binning
Missing Values
The which() Operator
R Essentials
Lists
Set Operations
Sampling and Sorting
Check Conditions
For Loops
Dataframes and Matrices
Dataframes
Importing and Exporting Data
Matrices and Frequency Tables
Merging Dataframes
Aggregation
Melting and Cross Tabulations with dcast()
Core Programming
Dates
String Manipulation
Functions
Debugging and Error Handling
Fast Loops with apply()
Fast Loops with sapply(), lapply() and vapply()
Making Plots with Base Graphics
Creating and Customizing an R Plot
Drawing Plots with 2 Y Axes
Multiplots and Custom Layouts
Creating Basic Graph Types
Statistical Inference
Univariate Analysis
Normal Distribution, Central Limit Theorem, and Confidence Intervals
Correlation and Covariance
Chi-sq Statistic
ANOVA
Statistical Tests
R Very Own Project
Project 1 – Data Munging and Summarizing
Project 2 – Visualization with Base Graphics
Project 3 – Statistical Inference
DPlyR and Pipes
Pipes with Magrittr
The 7 Data Manipulation Verbs
Aggregation and Special Functions
Two Table Verbs
Working With Databases
data.table
Understanding Basics, Filter, and Select
Understanding Syntax, Creating and Updating Columns
Aggregating Data, .N, and .I
Chaining, Functions, and .SD
Fast Loops with set(), Keys, and Joins

Video Details

ISBN 139781786463869
Course Length3 hours 46 minutes
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From 1 reviews

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