R Programming Training in Mumbai

THE ART OF R PROGRAMMING

INTRODUCTION

• Why Use R for Your Statistical Work?
• Object-Oriented Programming
• Functional Programming?
• Functional Programming?

INSTALLING R

• Downloading R from CRAN
• Installing from Source

GETTING STARTED

How to Run R

• Interactive Mode
• Batch Mode

First R Session

Introduction to Functions

• Variable Scope
• Default Arguments

Preview of Some Important R Data Structures

• Vectors, the R
• Character Strings
• Matrices
• Lists
• Arrays
• Data Frames

VECTORS

Scalars, Vectors, Arrays, and Matrices

• Adding and Deleting Vector Elements
• Obtaining the Length of a Vector
• Matrices and Arrays as Vectors

Declarations

Common Vector Operations

• Vector Arithmetic and Logical Operations
• Vector Indexing
• Generating Useful Vectors with the : Operator
• Generating Vector Sequences with seq()
• Repeating Vector Constants with rep

Vectorized Operations

• Vector In, Vector Out
• Vector In, Matrix Out

NA and NULL Values

• Using NA
• Using NULL

Filtering

• Generating Filtering Indices
• Filtering with the subset() Function
• The Selection Function which

A Vectorized if-then-else: The ifelse() Function

• Extended Example: A Measure of Association
• Extended Example: Recoding an Abalone Data Set

Testing Vector Equality

Vector Element Names

More on c()

MATRICES AND ARRAYS

Creating Matrices

• General Matrix Operations
• Performing Linear Algebra Operations on Matrices
• Matrix Indexing
• Filtering on Matrices

Applying Functions to Matrix Rows and Columns

• Using the apply() Function
• Extended Example: Finding Outliers
• Adding and Deleting Matrix Rows and Columns
• Changing the Size of a Matrix

More on the Vector/Matrix Distinction

Avoiding Unintended Dimension Reduction

Naming Matrix Rows and Columns

Higher-Dimensional Arrays

LISTS

Creating Lists

General List Operations

• List Indexing
• Adding and Deleting List Elements
• Getting the Size of a List

Accessing List Components and Values

Applying Functions to Lists

• Using the lapply() and sapply() Functions

ARRAYS

• Naming Columns and Rows
• Accessing Array Elements
• Check if an Item Exists
• Amount of Rows and Columns
• Array Length
• Manipulating Array Elements
• Calculations Across Array Elements

DATA FRAMES

Creating Data Frames

• Accessing Data Frames

Other Matrix-Like Operations

• Extracting Subdata Frames
• More on Treatment of NA Values
• Using the rbind() and cbind() Functions and Alternatives .
• Applying apply()

Merging Data Frames

• Extended Example: An Employee Database

Applying Functions to Data Frames

• Using lapply() and sapply() on Data Frames

FACTORS AND TABLES

Factors and Levels

Common Functions Used with Factors

• The tapply() Function
• The split() Function
• The by() Function

Working with Tables

• Matrix/Array-Like Operations on Tables
• Extended Example: Extracting a

Other Factor- and Table-Related Functions

• The aggregate() Function
• The cut() Function

R PROGRAMMING STRUCTURES

Control Statements

• Loops
• Looping Over Non vector Sets
if-else

Arithmetic and Boolean Operators and Values

Default Values for Arguments

Return Values

• Deciding Whether to Explicitly Call return()
• Returning Complex Objects

Functions Are Objects

Environment and Scope Issues

The Top-Level Environment

• The Scope Hierarchy
• More on ls()
• Functions Have (Almost) No Side Effects

No Pointers in R

Writing Upstairs

• Writing to Nonlocals with the Super assignment Operator
• Writing to Nonlocals with assign()

When Should You Use Global Variables?

Replacement Functions

• What’s Considered a Replacement Function?

Tools for Composing Function Code

• Text Editors and Integrated Development Environments

The edit() Function

Writing Your Own Binary Operations

Anonymous Functions

DOING MATH AND SIMULATIONS IN R

Math Functions

• Extended Example
• Cumulative Sums and Products
• Minima and Maxima

Functions for Statistical Distributions

Sorting

Linear Algebra Operations on Vectors and Matrices

• Extended Example: Vector Cross Product
• Set Operations

Simulation Programming in R

• Built-In Random Variate Generators
• Obtaining the Same Random Stream in Repeated Runs

INPUT/OUTPUT

Accessing the Keyboard and Monitor

• Using the scan() Function
• Using the readline() Function
• Printing to the Screen

Reading and Writing Files

• Reading a Data Frame or Matrix from a File
• Reading Text Files
• Introduction to Connections
• Extended Example
• Accessing Files on Remote Machines via URLs
• Writing to a File
• Getting File and Directory Information

STRING MANIPULATION

An Overview of String-Manipulation Functions

• grep()
• nchar()
• paste()
• sprintf()
• substr
• strsplit()
• regexpr()

Regular Expressions

• Extended Example

R DATA INTERFACES

R - CSV Files

• Reading a CSV File
• Analyzing the CSV File
• Writing into a CSV File

R - Excel Files

• Install xlsx Package
• Reading the Excel File

R - Binary Files

• Writing the Binary File
• Reading the Binary File

R - XML Files

• Reading XML File
• XML to Data Frame

R - JSON Files

• Install rjson Package
• Read the JSON File
• Convert JSON to a Data Frame

R - Database

• RMySQL Package
• Connecting R to MySql
• Querying the Tables
• Query with Filter Clause
• Updating Rows in the Tables
• Inserting Data into the Tables
• Creating Tables in MySql
• Dropping Tables in MySql

GRAPHICS

Creating Graphs

• The Workhorse of R Base Graphics: The plot() Function
• R - Pie Charts
• R - Bar Charts
• R - Boxplots
• R - Histograms
• R - Line Graphs
• R - Scatterplots
• Starting a New Graph While Keeping the Old Ones
• Extended Example
• Adding Points: The points() Function
• Adding a Legend: The legend() Function
• Adding Text: The text() Function
• Pinpointing Locations: The locator() Function
• Restoring a Plot
• Customizing Graphs
• Changing Character Sizes: The cex
• Changing the Range of Axes: The xlim and ylim Options
• Graphing Explicit Functions
• Extended Example

Saving Graphs to Files

• R Graphics Devices
• Saving the Displayed Graph
• Closing an R Graphics Device

Creating Three-Dimensional Plots

R Statistics

R Statistics Intro

R Data Set

R Max and Min

R Mean Median Mode

R Percentiles

INSTALLING AND USING PACKAGES

Package Basics

Loading a Package from Your Hard Drive

Downloading a Package from the Web

Installing Packages Automatically

Installing Packages Manually

Listing the Functions in a Package

Download Syllabus - R Programming
This syllabus is not final and can be customized as per needs/updates