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Computer Science
Web Development
R and Shiny for Web Application Development
1. Introduction to R and Shiny
2. Fundamentals of R for Shiny
3. Core Concepts of a Shiny Application
4. Building the User Interface (UI)
5. The Server Logic and Reactivity
6. Enhancing User Experience and Design
7. Advanced Shiny Development
8. Debugging and Optimization
9. Deploying and Sharing Shiny Applications
2.
Fundamentals of R for Shiny
2.1.
R Data Types and Structures
2.1.1.
Basic Data Types
2.1.1.1.
Numeric Types
2.1.1.2.
Character Types
2.1.1.3.
Logical Types
2.1.2.
Data Structures
2.1.2.1.
Vectors
2.1.2.2.
Lists
2.1.2.3.
Data Frames
2.1.2.4.
Matrices
2.1.2.5.
Factors
2.2.
Data Import and Export in R
2.2.1.
Reading CSV Files
2.2.2.
Reading Excel Files
2.2.3.
Writing Data to Files
2.2.4.
Working with Databases
2.3.
Data Manipulation Basics
2.3.1.
Subsetting and Indexing
2.3.2.
Filtering and Selecting Data
2.3.3.
Aggregating and Summarizing Data
2.4.
Control Flow in R
2.4.1.
Conditional Statements
2.4.1.1.
if Statements
2.4.1.2.
else Statements
2.4.1.3.
else if Statements
2.4.2.
Looping Constructs
2.4.2.1.
for Loops
2.4.2.2.
while Loops
2.4.2.3.
repeat Loops
2.4.3.
Vectorized Operations
2.5.
Functions in R
2.5.1.
Writing Custom Functions
2.5.2.
Function Arguments and Defaults
2.5.3.
Return Values
2.5.4.
Scope and Environments
2.5.5.
Anonymous Functions
2.6.
Essential R Packages for Data Manipulation
2.6.1.
Installing and Loading Packages
2.6.2.
dplyr for Data Transformation
2.6.2.1.
Selecting Columns
2.6.2.2.
Filtering Rows
2.6.2.3.
Mutating Columns
2.6.2.4.
Summarizing Data
2.6.2.5.
Grouping Data
2.6.3.
ggplot2 for Data Visualization
2.6.3.1.
Creating Basic Plots
2.6.3.2.
Customizing Plot Appearance
2.6.3.3.
Faceting
2.6.3.4.
Themes
2.6.4.
data.table for High-Performance Data Handling
2.6.4.1.
Syntax and Usage
2.6.4.2.
Efficient Data Operations
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3. Core Concepts of a Shiny Application