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III : Descriptive Analytics with R
1
Welcome
Authors
Live Analytics Lab
Syllabus
I : Introduction to R Programming
Getting Started with R
2
Introduction to R
3
Purpose and Advantages of Using R
4
Setting Up the R Environment and IDEs
R Language Fundamentals
5
Basic Syntax, Variables, and Naming Conventions
6
Input and Output Statements
7
Basic Data Types and Type Casting
Operators and Data Structures Overview
8
Types of Operators in R
9
Role and Purpose of Data Structures in R
II : Data Structures and Operations in R
Vectors in R
10
Vectors: Creation, Sequence, and Length
11
Vector Operations: Sorting, Ordering, Recycling, and Missing Values
12
Arithmetic, Relational, and Logical Operations on Vectors
Lists in R
13
Lists: Creation, Accessing, and Modification
14
Operations on Lists: Appending, Nesting, and Manipulation
Matrices and Arrays
15
Matrices in R
16
Arrays in R
III : Descriptive Analytics with R
Working with Strings
17
Strings: Creation, Concatenation, and Substrings
18
Advanced String Operations and Functions
Data Frames and Factors
19
Data Frames: Creation, Access, and Manipulation
20
Advanced Data Frame Operations with dplyr
21
Factors: Creation, Levels, and Reordering
IV : Conditional Statements, Loops, and Functions
Conditional Statements
22
Conditional Statements: If, If-Else, and Switch
23
Logical Operators in Conditional Statements
Loops in R
24
Loops in R: For, While, and Repeat
25
Iterating Loops Over Data Structures
Functions in R
26
Functions: Purpose, Types, and Creation
27
Advanced Functions: Recursive, Closure, and Nested
References
III : Descriptive Analytics with R
Module III · 5 Topics
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
16
Arrays in R
17
Strings: Creation, Concatenation, and Substrings