A comprehensive collection of 8 interactive R Shiny applications for data analysis, visualization, and decision-making. Each application is deployed and accessible via web browser.
All applications are deployed and ready to use:
| # | Application | Description | Live Demo |
|---|---|---|---|
| 1 | Business Analytics Dashboard | Track sales, KPIs, and customer churn | Launch App |
| 2 | Data Explorer | Upload and explore datasets with visualizations | Launch App |
| 3 | Statistical Lab | Interactive statistical tools and simulations | Launch App |
| 4 | Model Deployment Hub | Deploy and test ML models | Launch App |
| 5 | Financial Analysis Suite | Portfolio optimization and forecasting | Launch App |
| 6 | Geospatial Explorer | Interactive maps of Kenya | Launch App |
| 7 | Quality Control Monitor | SPC charts and process monitoring | Launch App |
| 8 | Survey Analyzer | Analyze surveys with NPS metrics | Launch App |
Access all applications from a single hub: Shiny Apps Launcher
What it does: Helps you understand your business performance
- See total sales, profits, and orders at a glance
- Track how sales change over time
- Identify which products sell best
- Analyze customer churn (who's leaving and why)
- Filter data by date, region, or category
Best for: Business owners, sales managers, analysts
What it does: Lets you upload and explore your own data
- Upload CSV, Excel, or other data files
- See summary statistics automatically
- Create charts and graphs with a few clicks
- Filter and search through your data
- Download cleaned data
Best for: Anyone who works with data and wants quick insights
What it does: Interactive tools for statistics and testing
- Confidence Intervals: See how sample size affects accuracy
- A/B Testing: Calculate if your test results are significant
- Distributions: Explore normal, t, chi-square distributions
- Regression: Check if your model assumptions are met
- Central Limit Theorem: Visualize this important concept
Best for: Students, researchers, data scientists learning statistics
What it does: Test machine learning models with your own data
- Random Forest Model: Predict iris flower species
- Linear Regression: Predict car fuel efficiency
- See how accurate the models are
- Understand which features matter most
- Get instant predictions
Best for: Data scientists, ML practitioners, students
What it does: Analyze stocks and optimize investment portfolios
- Forecasting: Predict future stock prices using ARIMA/ETS
- Portfolio Optimization: Find the best mix of stocks
- Risk Analysis: Calculate Value at Risk (VaR)
- Interactive charts for financial data
- Download analysis results
Best for: Investors, financial analysts, portfolio managers
What it does: Create interactive maps of Kenya
- Plot points on a map of Kenya
- Create heatmaps to show density
- Cluster nearby points automatically
- Color-code regions by values
- Filter and analyze spatial data
Best for: Researchers, NGOs, businesses analyzing geographic data in Kenya
What it does: Monitor manufacturing quality and processes
- Control Charts: Track if your process is stable
- Capability Analysis: See if you meet specifications (Cp, Cpk)
- Real-time Monitoring: Add new measurements and see results
- Identify out-of-control points
- Calculate defect rates (PPM)
Best for: Manufacturing engineers, quality managers, Six Sigma practitioners
What it does: Analyze survey responses and calculate NPS
- Upload survey data (CSV, Excel, SPSS)
- Calculate Net Promoter Score (NPS) automatically
- See satisfaction ratings and distributions
- Cross-tabulate responses
- Generate downloadable reports
Best for: Market researchers, customer success teams, HR departments
- R Shiny - Interactive web framework
- bslib - Modern Bootstrap 5 theming
- plotly - Interactive visualizations
- DT - Interactive data tables
- leaflet - Interactive maps
- dplyr - Data manipulation
- ggplot2 - Static visualizations
R/
├── apps/ # Individual applications
│ ├── 01_business_analytics/
│ ├── 02_data_explorer/
│ ├── 03_statistical_lab/
│ ├── 04_model_deployment/
│ ├── 05_financial_analysis/
│ ├── 06_geospatial_explorer/
│ ├── 07_quality_control/
│ └── 08_survey_analyzer/
├── shared/ # Shared utilities
│ ├── theme.R # UI theming
│ ├── ui_components.R # Reusable components
│ └── data_utils.R # Data generation
├── launcher.R # Main launcher app
├── README.md # This file
└── APPS_GUIDE.md # Detailed app guide
- R (version 4.0 or higher)
- RStudio (recommended)
- Clone the repository
git clone https://github.com/SHIVOGOJOHN/dataml.git
cd dataml- Install required packages
source("install_packages.R")Or install manually:
install.packages(c(
"shiny", "shinydashboard", "bslib", "plotly", "DT",
"dplyr", "ggplot2", "readr", "readxl", "leaflet",
"quantmod", "forecast", "randomForest", "caret",
"qcc", "haven", "shinyjs"
))- Run the launcher
shiny::runApp("launcher.R")Or run individual apps:
shiny::runApp("apps/01_business_analytics")- Clean, professional interface using Bootstrap 5
- Responsive design works on desktop and mobile
- Consistent theming across all applications
- Interactive charts and visualizations
- Intuitive navigation
- Clear instructions and tooltips
- Sample data included for testing
- Download capabilities for results
- Deployed on shinyapps.io
- Optimized performance
- Error handling
- Input validation
- APPS_GUIDE.md - Detailed guide for each application
- README.md - This file
- INSTALL.md - Installation instructions
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License.
John Shivogo
- GitHub: @SHIVOGOJOHN
- Portfolio: shivogojohn
- Built with R Shiny
- Deployed on shinyapps.io
- Uses modern web design principles
- Inspired by real-world business needs
For questions or issues, please open an issue on GitHub or contact me directly.
⭐ If you find this project useful, please consider giving it a star!