#' Title: Interactive Data Explorer Dashboard #' Author: [Your Name/Organization] #' Date: [Date] #' Version: 1.0.0 #' License: MIT
#' This Shiny application provides an interactive dashboard for exploring #' and visualizing datasets. Users can upload their own CSV files or work #' with built-in sample datasets, create customized plots, view data tables, #' and generate summary statistics.
#' ## Key Features: #' 1. Data Import: Upload CSV files or select from sample datasets #' 2. Interactive Visualization: Customizable scatter plots with ggplot2 #' 3. Data Table: Interactive DT table with search and pagination #' 4. Statistics: Summary statistics and correlation matrices #' 5. Dynamic UI: Variable selection updates based on loaded data #' 6. Data Export: Download filtered data as CSV #' 7. Responsive Design: Clean sidebar layout with tabbed interface
#' ## Prerequisites:
#'
#' Install R (>= 4.0.0) and RStudio from:
#' - R: https://cran.r-project.org/
#' - RStudio: https://posit.co/download/rstudio-desktop/
#'
#' ## Quick Start:
#'
#' 1. Copy the app.R file to your working directory
#' 2. Install required packages:
#'
required_packages <- c("shiny", "ggplot2", "DT")
install_if_missing <- function(pkg) { if (!require(pkg, character.only = TRUE)) { install.packages(pkg, dependencies = TRUE) library(pkg, character.only = TRUE) } }
#' ## Running the App:
#'
#' ### Option 1: In RStudio
#' 1. Open app.R in RStudio
#' 2. Click the "Run App" button (top-right of source pane)
#' 3. Or press Ctrl+Shift+Enter (Windows/Linux) or Cmd+Shift+Return (Mac)
#'
#' ### Option 2: From R Console
#'
#' ## File Structure:
#' #' project-folder/ #' ├── app.R # Main Shiny application #' ├── README.R # This documentation file #' ├── data/ # Optional: folder for data files #' │ ├── sample.csv #' │ └── your_data.csv #' ├── www/ # Optional: for static assets #' │ ├── style.css #' │ └── images/ #' └── tests/ # Optional: for test files #'
#' ## Step-by-Step Guide: #' #' ### 1. Launch the App #' - Run the app using one of the methods above #' - A browser window will open with the dashboard #' #' ### 2. Load Data #' - Option A: Click "Browse..." to upload a CSV file #' - Option B: Select a sample dataset from the dropdown #' #' ### 3. Create Visualizations #' - Choose variables for X and Y axes from dropdowns #' - Adjust point size with the slider #' - Select a plot theme #' - Check "Add trend line" for regression line #' - Click "Update Dashboard" to apply changes #' #' ### 4. Explore Data #' - Switch between tabs: #' - Plot: View and customize visualizations #' - Data Table: Browse/search the data #' - Statistics: View summaries and correlations #' - About: App documentation #' #' ### 5. Export Data #' - Use the "Download Filtered Data" button to save CSV
#' ## Included Datasets: #' #' 1. mtcars - Motor Trend car road tests (32 × 11) #' - Variables: mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb #' #' 2. iris - Edgar Anderson's iris data (150 × 5) #' - Variables: Sepal.Length, Sepal.Width, Petal.Length, Petal.Width, Species #' #' 3. diamonds - Diamond prices (53,940 × 10) #' - Variables: carat, cut, color, clarity, depth, table, price, x, y, z #' #' 4. mpg - Fuel economy data (234 × 11) #' - Variables: manufacturer, model, displ, year, cyl, trans, drv, cty, hwy, fl, class
#' ## How to Customize: #' #' ### 1. Add New Sample Dataset: #'
add_dataset_example <- function() {
}
#' ### 2. Change Default Plot Type: #'
add_plot_types <- function() {
}
#' ### 3. Add More Statistics: #'
add_statistics <- function() {
}
#' ## CSV File Requirements: #' - File extension: .csv or .txt #' - First row should contain column names #' - Comma-separated values (or adjust read.csv() parameters) #' - Missing values should be empty or NA #' - For best results with plotting, include numeric columns
example_data <- data.frame( ID = 1:10, Value = rnorm(10), Category = sample(c("A", "B", "C"), 10, replace = TRUE), Date = seq.Date(Sys.Date(), by = "day", length.out = 10) )
#' ## Common Issues: #' #' ### 1. "Package not found" error #' - Run: install.packages(c("shiny", "ggplot2", "DT")) #' - Restart R session #' #' ### 2. CSV file won't upload #' - Check file is actually CSV format #' - Ensure file size < 5MB (adjust limits in fileInput) #' - Check for special characters in column names #' #' ### 3. Plot doesn't update #' - Click "Update Dashboard" button #' - Ensure numeric variables are selected #' - Check R console for error messages #' #' ### 4. App runs but browser doesn't open #' - Check browser isn't blocking popups #' - Access manually at: http://127.0.0.1:XXXX #' - Check RStudio Viewer pane
#' ## Package Dependencies: dependencies <- list( shiny = "Web application framework", ggplot2 = "Data visualization", DT = "Interactive data tables", dplyr = "Data manipulation (optional, for extensions)", tidyr = "Data tidying (optional, for extensions)", plotly = "Interactive plots (optional, for extensions)" )
check_dependencies <- function() { cat("Checking dependencies...\n") for (pkg in names(dependencies)) { if (requireNamespace(pkg, quietly = TRUE)) { cat(sprintf("✓ %s: %s\n", pkg, dependencies[[pkg]])) } else { cat(sprintf("✗ %s: NOT INSTALLED (%s)\n", pkg, dependencies[[pkg]])) } } }
#' ## Ideas for Extensions: #' #' 1. Add Machine Learning #' - Regression/classification models #' - Model performance metrics #' - Prediction interface #' #' 2. Additional Visualizations #' - Time series plots #' - Heatmaps #' - Network graphs #' #' 3. Data Processing #' - Data cleaning tools #' - Variable transformation #' - Missing value imputation #' #' 4. Report Generation #' - PDF/HTML reports #' - Automated summaries #' - Export plots to images
#' ## How to Contribute: #' #' 1. Fork the repository #' 2. Create a feature branch #' 3. Make your changes #' 4. Test thoroughly #' 5. Submit a pull request #' #' ## Code Style: #' - Use consistent indentation (2 spaces) #' - Comment complex logic #' - Follow tidyverse style guide where applicable #' - Use meaningful variable names
#' ## License: #' MIT License - See LICENSE file for details #' #' ## Citation: #' If you use this app in research, please cite: #' [Your preferred citation format] #' #' ## Acknowledgments: #' - R Core Team #' - Shiny developers #' - Tidyverse team #' - CRAN maintainers
#' ## Support: #' - RStudio Community: https://community.rstudio.com #' - Stack Overflow (tag: r, shiny) #' - GitHub Issues: [Your repo link] #' #' ## Documentation Links: #' - Shiny: https://shiny.posit.co/ #' - ggplot2: https://ggplot2.tidyverse.org/ #' - DT: https://rstudio.github.io/DT/
#' ## Changelog: #' #' ### v1.0.0 [Date] #' - Initial release #' - Basic data upload and visualization #' - Interactive data table #' - Summary statistics #' - Sidebar layout with tabs #' #' ### v1.1.0 [Planned] #' - Add more plot types #' - Data preprocessing tools #' - User authentication #' - Theming options
cat("\n") cat("=======================================================================\n") cat("Shiny Data Explorer Dashboard README\n") cat("=======================================================================\n") cat("To use this app:\n") cat("1. Ensure all packages are installed\n") cat("2. Run: shiny::runApp('app.R')\n") cat("3. Open browser to: http://127.0.0.1:PORT\n") cat("=======================================================================\n")