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GWalkR: Your One-Stop R Package for Exploratory Data Analysis with Visualization

Start Exploratory Data Analysis (EDA) in R with a Single Line of Code! GWalkR is an interactive Exploratory Data Analysis (EDA) Tool in R. It integrates the htmlwidgets with Graphic Walker. It can simplify your R data analysis and data visualization workflow, by turning your data frame into a Tableau-style User Interface for visual exploration.

If you prefer using Python, you can check out PyGWalker!

Getting Started

📦 Setup GWalkR

install.packages("GWalkR")
library(GWalkR)

📈 Start Your Data Exploration in a Single Line of Code

data(iris)
gwalkr(iris)

🚀 Switch to Kernel Computation for Large Datasets

gwalkr(large_df, kernelComputation = TRUE)

Here is a tutorial with more details.

Please note that the kernel mode will be running in a Shiny app which will block your R console. You can stop the app to use the console.

Main Features

Get an overview of your data frame under 'Data' tab.

Creat data viz with simple drag-and-drop operations.

Find interesting data points? Brush them and zoom in!

Empower your R notebook (R Markdown).

Showcase your data insights with editable and explorable charts on a webpage (example)!

Development

We encourage developers from the amazing open-source community to help improve this R package!

Because the built web library is not tracked by git, the source code here is not directly runnable. Please follow the steps below to run the source code on your own device:

1. Run git clone https://github.com/Kanaries/GWalkR.git to clone this repository.
2. Go to /web_app and yarn install.
3. You can now implement your features either in the web app by changing the TypeScript code, or in the R scripts under /R.
4. Run yarn run build to build the web app, and make sure the built library can be found under /inst/htmlwidgets/lib/.
5. In R Studio, run devtools::load_all("{DIR_OF_GWALKR}") to load the package (make sure you've removed the installed GWalkR from CRAN before that).

For more information about R package development, please refer to this book, R Packages.