EzExplorer: Simple Data Analysis Tool

Welcome to EzExplorer!

This package is designed to automate the Exploratory Data Analysis (EDA) process. With this tool, you can obtain a summary of descriptive statistics and plot data distribution charts with just a single command.

📦 Installation

You can install the development version of this package directly from GitHub:

# install.packages("devtools")
devtools::install_github("AsalllB/EzExplorer")

🚀 Usage Example

Here we demonstrate how this package works on the famous iris dataset. Note that the plots below are generated automatically by the package:

library(EzExplorer)

# Load sample data
data(iris)

# Run quick analysis
# This function automatically detects numeric columns and plots them
results <- quick_analyze(iris)

#> Analysis Complete! Here is the summary:
#>                  Variable     Mean        SD
#> Sepal.Length Sepal.Length 5.843333 0.8280661
#> Sepal.Width   Sepal.Width 3.057333 0.4358663
#> Petal.Length Petal.Length 3.758000 1.7652982
#> Petal.Width   Petal.Width 1.199333 0.7622377

As you can see, the mean and standard deviation were calculated, and histograms were plotted automatically.

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🛠️ Developer Tips

If you want to contribute to this package or modify it, follow these steps:

1. Install Requirements: If you want to run the R code or update it, you can install the package dev dependencies by running:

Rscript setup.r

2. Update Documentation: If you change the R code or comments (roxygen2 headers), run this command to update NAMESPACE and .Rd files:

devtools::document()

3. Rebuild README: If you edit README.Rmd, you must regenerate README.md for GitHub to display changes correctly. Run:

rmarkdown::render("README.Rmd", output_format = "github_document")

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Created by: AsalB