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III : Descriptive Analytics with R
Welcome
Syllabus
I : Introduction to R Programming
Getting Started with R
1
Introduction to R
2
Purpose and Advantages of Using R
3
Setting Up the R Environment and IDEs
R Language Fundamentals
4
Basic Syntax, Variables, and Naming Conventions
5
Input and Output Statements
6
Basic Data Types and Type Casting
Operators and Data Structures Overview
7
Types of Operators in R
8
Role and Purpose of Data Structures in R
II : Data Structures and Operations in R
Vectors in R
9
Vectors: Creation, Sequence, and Length
10
Vector Operations: Sorting, Ordering, Recycling, and Missing Values
11
Arithmetic, Relational, and Logical Operations on Vectors
Lists in R
12
Lists: Creation, Accessing, and Modification
13
Operations on Lists: Appending, Nesting, and Manipulation
Matrices and Arrays
14
Matrices in R
15
Arrays in R
III : Descriptive Analytics with R
Working with Strings
16
Strings: Creation, Concatenation, and Substrings
17
Advanced String Operations and Functions
Data Frames and Factors
18
Data Frames: Creation, Access, and Manipulation
19
Advanced Data Frame Operations with dplyr
20
Factors: Creation, Levels, and Reordering
IV : Conditional Statements, Loops, and Functions
Conditional Statements
21
Conditional Statements: If, If-Else, and Switch
22
Logical Operators in Conditional Statements
Loops in R
23
Loops in R: For, While, and Repeat
24
Iterating Loops Over Data Structures
Functions in R
25
Functions: Purpose, Types, and Creation
26
Advanced Functions: Recursive, Closure, and Nested
References
Contents
Working with Strings
Data Frames and Factors
III : Descriptive Analytics with R
Working with Strings
Strings: Creation, Concatenation, and Substrings
Advanced String Operations and Functions
Data Frames and Factors
Data Frames: Creation, Access, and Manipulation
Advanced Data Frame Operations with dplyr
Factors: Creation, Levels, and Reordering
15
Arrays in R
16
Strings: Creation, Concatenation, and Substrings