https://github.com/nabilshadman/r-data-analysis
A modular R framework for data analysis, with emphasis on data processing and reproducible workflows.
https://github.com/nabilshadman/r-data-analysis
data-analysis data-cleaning data-manipulation data-science descriptive-statistics programming r r-studio statistical-analysis statistical-computing t-test
Last synced: 24 days ago
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A modular R framework for data analysis, with emphasis on data processing and reproducible workflows.
- Host: GitHub
- URL: https://github.com/nabilshadman/r-data-analysis
- Owner: nabilshadman
- License: mit
- Created: 2021-06-17T04:24:15.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2024-12-04T18:11:22.000Z (5 months ago)
- Last Synced: 2025-02-09T13:13:00.720Z (3 months ago)
- Topics: data-analysis, data-cleaning, data-manipulation, data-science, descriptive-statistics, programming, r, r-studio, statistical-analysis, statistical-computing, t-test
- Language: R
- Homepage:
- Size: 28.3 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# R Data Analysis Framework
[](https://opensource.org/licenses/MIT)
[](https://shields.io/)
A modular R framework for data analysis, data manipulation, and visualization. This library provides functions for handling data, with emphasis on reproducibility and clean code practices.
## Overview
This framework implements data analysis workflows focusing on:
- Geometric calculations and transformations
- Descriptive statistics and data summarization
- Statistical hypothesis testing
- Data preprocessing and cleaning
- Correlation analysis
## Installation
```r
# Clone repository
git clone https://github.com/username/r-statistical-analysis.git
# Install required R packages
install.packages(c("stats", "utils", "base"))
```
## Project Structure
```
.
├── assignment1/
│ ├── assignment1.R # Core statistical functions
│ └── chol.txt # Sample cholesterol dataset
├── assignment2/
│ ├── assignment2.R # Data preprocessing utilities
│ └── Assignment2.RData # Multi-dataset RData file
└── README.md
```
## Core Features
### Geometric Analysis Module
- Circle and sphere calculations (area, volume, circumference)
- Multi-dimensional geometric transformations
- Configurable precision and rounding
### Statistical Analysis Tools
- Descriptive statistics generation
- Two-sample t-test automation
- Missing value handling
- Outlier detection and processing
### Data Processing Utilities
- Data normalization
- Correlation analysis for metrics
- Categorical data imputation
- Flexible data frame operations
## Usage Examples
### Basic Circle Calculations
```r
# Calculate circle area
calCircle('ac', 4)
# Multiple calculations
calCircle2(c('AC', 'VS'), seq(5,25,5))
```
### Statistical Analysis
```r
# Generate descriptive statistics
table1(patient_num, c("GLUC", "TGL", "HDL", "LDL"))
# Perform t-tests
myTtest(dat=chol, classVar="sex", numVar=c("age", "chol", "tg"))
```
### Data Preprocessing
```r
# Handle missing values
impute(dat=patient, varlist=c("LDL", "HRT", "MAMM"))
# Calculate correlations
myCorTest(chol, "bmi", c("sbp", "dbp", "vldl", "hdl", "ldl"))
```
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/enhancement`)
3. Commit changes (`git commit -am 'Add enhancement'`)
4. Push to branch (`git push origin feature/enhancement`)
5. Create Pull Request
## License
This project is licensed under the MIT License - see [LICENSE](LICENSE) for details.
## Citation
If you use this framework in your research, please cite:
```bibtex
@software{r_data_analysis,
author = {Shadman, Nabil},
title = {R Data Analysis Framework},
year = {2020},
url = {https://github.com/nabilshadman/r-data-analysis}
}
```