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https://github.com/exios66/matlab

MATLAB Development Sandbox
https://github.com/exios66/matlab
Last synced: about 2 months ago
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MATLAB Development Sandbox
Host: GitHub
URL: https://github.com/exios66/matlab
Owner: Exios66
License: mit
Created: 2024-11-06T03:44:25.000Z (2 months ago)
Default Branch: main
Last Pushed: 2024-11-06T04:14:05.000Z (2 months ago)
Last Synced: 2024-11-06T05:17:36.377Z (2 months ago)
Language: R
Size: 20.5 KB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

        # Advanced R Data Visualization Suite

## A Comprehensive Data Visualization and Analysis Platform

![R Version](https://img.shields.io/badge/R-%3E%3D%204.0.0-blue.svg)

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### Table of Contents

1. [Overview](#overview)

2. [Features](#features)

3. [Installation](#installation)

4. [Directory Structure](#directory-structure)

5. [Usage Guide](#usage-guide)

6. [Advanced Features](#advanced-features)

7. [Customization](#customization)

8. [Troubleshooting](#troubleshooting)

9. [Contributing](#contributing)

10. [License](#license)

## Overview

The Advanced R Data Visualization Suite is a comprehensive platform for data analysis, visualization, and reporting. It combines modern UI elements with powerful R-based analytics capabilities to provide a seamless data exploration experience.

## Features

### Core Capabilities

- **Data Import & Processing**

  - Multiple format support (CSV, XLSX, RDS, Feather)

  - Automated data cleaning

  - Advanced preprocessing options

  - Real-time data validation

- **Visualization Types**

  - Basic: Scatter, Line, Bar, Box plots

  - Advanced: Treemaps, Networks, Sunbursts, Sankey

  - Statistical: Correlation, Clustering, PCA

  - Interactive: 3D plots, Animated visualizations

- **Analysis Tools**

  - Descriptive statistics

  - Correlation analysis

  - Clustering algorithms

  - Time series analysis

  - Feature engineering

### User Interface

- Modern dashboard design

- Responsive layout

- Interactive controls

- Real-time preview

- Custom themes

## Installation

### Prerequisites

```r

Install required packages

install.packages(c(

```

```r

"shiny",

"shinydashboard",

"shinydashboardPlus",

"shinyjs",

"shinyWidgets",

"DT",

"waiter",

"fresh",

"bs4Dash",

"plotly",

"tidyverse",

"data.table",

"viridis",

"highcharter",

"leaflet",

"forecast",

"corrplot",

"gridExtra",

"GGally",

"ggridges",

"ggrepel",

"gganimate",

"networkD3",

"treemap",

"visNetwork",

"sunburstR",

"waffle",

"streamgraph",

"circlize",

"dendextend",

"rmarkdown"

))

```

### Setup Instructions

1. Clone the repository:

```bash

git clone https://github.com/Exios66/data-visualization-suite.git

```

   1. Set up the directory structure:

```bash

project_root/

├── app/

│ ├── global.R

│ ├── ui.R

│ ├── server.R

│ └── www/

│ └── custom.css

├── R/

│ ├── preprocessing.R

│ ├── themes.R

│ ├── advanced_visualizations.R

│ ├── statistical_visualizations.R

│ └── report_template.Rmd

└── data/

└── example_datasets/

```

1. Configure environment:

```bash

source("setup.R") # Sets up necessary directories and configurations

```

## Directory Structure

- `app/`: Main application files

- `R/`: Helper functions and modules

- `templates/`: Report templates

- `data/`: Example datasets and user data

- `www/`: Static assets and CSS

- `docs/`: Documentation

## Usage Guide

### Quick Start

1. Launch the application:

```bash

run_app.R

```

1. Import Data:

- Click "Data Import & Preprocessing"

- Upload your data file

- Select preprocessing options

- Create Visualizations:

  - Choose visualization type

  - Select variables

  - Customize appearance

  - Export or share results

### Advanced Usage

#### Custom Preprocessing

```r

Custom preprocessing pipeline

preprocess_data(data, steps = c(

"clean",

"transform",

"engineer"

), params = list(

outlier_threshold = 0.05,

scaling_method = "minmax",

feature_engineering = TRUE

))

```

#### Custom Visualizations

```r

Create advanced visualization

create_advanced_visualization(

data = processed_data,

viz_type = "network",

params = list(

layout = "force-directed",

node_size = "degree",

edge_weight = "correlation"

)

)

```

#### Theme Customization

1. Modify `www/custom.css`

## Advanced Features

### API Integration

The suite supports integration with external APIs:

```r

Example API connection

connect_api(

endpoint = "https://api.example.com/data",

auth_token = YOUR_TOKEN,

params = list(

date_range = c("2023-01-01", "2023-12-31"),

metrics = c("sales", "revenue")

)

)

```

### Automated Reporting

```r

Generate automated report

generate_report(

template = "executive_summary",

data = processed_data,

visualizations = plot_list,

output_format = "html"

)

```

### Batch Processing

```r

Process multiple datasets

batch_process(

data_dir = "data/raw",

output_dir = "data/processed",

preprocessing_steps = preprocessing_pipeline

)

```

## Customization

### Adding New Visualizations

1. Create new visualization function in `R/advanced_visualizations.R`

2. Register visualization in UI controls

3. Add processing logic in server function

### Custom Themes

1. Modify `www/custom.css`

2. Add theme definition in `R/themes.R`

3. Update theme selector in UI

## Troubleshooting

### Common Issues

1. **Data Import Errors**

   - Check file format compatibility

   - Verify file permissions

   - Ensure proper encoding

2. **Performance Issues**

   - Reduce dataset size

   - Enable caching

   - Optimize preprocessing steps

3. **Visualization Errors**

   - Verify data types

   - Check variable selections

   - Confirm sufficient memory

### Debug Mode

```r

Enable debug mode

options(shiny.trace = TRUE)

options(shiny.fullstacktrace = TRUE)

```

## Contributing

1. Fork the repository

2. Create feature branch

3. Commit changes

4. Submit pull request

### Development Guidelines

- Follow R style guide

- Add unit tests

- Update documentation

- Maintain backward compatibility

## License

MIT License - See LICENSE file for details

## Contact

For support or feature requests:

- Create an issue

- Email: 

- Documentation: