Rattle the Next Generation Data Scientist

Rattle has been in development and use for almost 20 years as a Data Mining and now Data Science toolkit for the apprentice and practising Data Scientist. The open source software and it books and papers have been used by educators, consultants, and practitioners across industry and government, to turn data into knowledge, through machine learning and artificial intelligence.

But now, it is time for a refresh. To install the new Rattle visit the Installers.

RattleNG, available from github, remains sympathetic to the original Rattle user interface, functionality, and goals, as presented in the Rattle book. However, it brings to the community a modern user interface refresh implemented in Flutter. The underlying R foundations remain firmly in place and encapsulated within a more readily extensible framework. A new edition of the Rattle book will soon be available.

Over the past 15 years we have also matured in how we deliver data science and analytics. RattleNG delivers a new perspective on scripting data science in R through templates as introduced in my more recent book, The Essentials of Data Science (https://bit.ly/essentials_data_science). The concept of templates for data science now provides the foundations for a flexible and extensible application in RattleNG.

You can also review my Desktop Data Mining Survival Guide published online by Togaware, available from (https://datamining.togaware.com).

The detailed coding documentation for our new Flutter/Dart based RattleNG is available online from the Solid Community AU.

The RattleNG rewrite is being lead by Professor Graham Williams (the original Rattle author), Chief Scientist of the Software Innovation Institute of the Australian National University. Significant contributions have also been made by Yixiang Yin.

Quick Start and Current Status 2024-07-07

You will need to install R, separate to the app itself. Visit https://www.r-project.org/ for details.

Then install RattleNG for your operating system as detailed in the installers README.

Then:

Start RattleNG.
Tap the Script tab to see the R code that has been run.
Tap the Console tab to see the R code being run within an R session. You can even type R commands there to have them run.
Tap the Dataset tab to return the to the startup screen for RattleNG. Tap the Dataset button and then choose Demo to load the rattle::weather dataset. You can also load your own CSV or TXT file by tapping the Filename button instead. The result panel of the page will provide view or summary of the dataset.
Tap the right pointing arrow to view the Roles page where you can specify the role for each variable. Defaults will have been set.
Notice the toggle buttons to the top right of the Dataset page: Cleanse, Normalise and Partition. Hover the mouse to view the tooltips.
To build an AI model, tap the Model tab and then the Tree radio button (selected by default) and then the Build button to build and view a decision tree from a CSV dataset. Scroll through the pages to the page showing the decision tree, textually and visually.
Tap the Script tab and scroll the window to view the latest R commands run. Then tap the Export button to save the full script to script.R (no options currently to change the name or location of the saved script file).
From your own command line run Rscript script.R

Currently implemented features as of version 6.3.9 (2024-10-18):

Dataset
- Demo
- CSV
- TXT
- Roles
Explore
- Summary
- Visual
- Missing
- Correlation
- Tests
Transform
- Impute
- Rescale
- Recode
- Cleanup
Model
- Cluster
- Neural
- Tree
- Forest
- Boost
- Word Cloud
Console
Script

Building RattleNG from Source

Ensure you have R installed, as described in the installer README.

Install Flutter as describe in the Flutter Install Guide. In short, to install on Windows, download the flutter sdk, unzip it to your home folder, add C:\Users\<user>\flutter\bin to the PATH environment variable, and in a CMD console run flutter help.

Currently (20230918), on Azure Windows VM, flutter doctor just sits there!

Then clone the rattleng repository:

git clone https://github.com/gjwgit/rattleng
cd rattleng
flutter run

Choose your target platform when prompted.

After firing up the rattleng app, check in the Console tab to make sure R is running. You should see some R code and the console is waiting at the R prompt:

...
>

RattleNG will itself eventually check for these and prompt if they are not available.

Latest Code

RattleNG is currently under active development. To get the current app you can install flutter on your local computer, then clone the github repository, to your local disk, and from a command line change to the directory where you cloned the rattle repository (it should contain a lib sub-directory) and type the following command, changing <os> to be one of windows, macos, or linux.

flutter run -d <os>

How you can Help

RattleNG will remain an open source application, free for anyone to use in any way they like. Contributions are welcome and the simplest is to make them through pull requests on github. You can fork my repository, make your changes, and push them back as a pull request to my repository where I can review and merge into the main product.

There is plenty to do, and if you have a favourite feature of Rattle, consider either implementing the GUI in Flutter for that component, or else write a simple template R script that takes a dataset ds and any other template parameters (as <<PARAMETER>> in the script) to then do it's stuff! The <<PARAMETER>> strings are filled in by the Flutter interface. See the growing number of scripts in assets/scripts/

Suggested tasks can be found as github issues.

Rattle Resources

Bob Meunchen's review of Rattle: https://r4stats.com/articles/software-reviews/rattle/

Some RattleNG teasers

Rattle's 5 Click to Your First AI Model

The traditional Rattle Welcome screen provides an overview of Rattle. To build your first model, simply click the Dataset button to choose Demo, which will load the rattle::weather dataset. Then click the Model tab and the Tree feature to then Build your first decision tree (an AI model).

Click the Dataset button to have options to load the data from a file, from an R package, or the demo weather dataset.

After the data is loaded we are presented with a summary.

Exploring Data Visually

All of the popular Rattle visualisations are available, modernised using ggplot and the tidyverse.

The traditional missing data plots have been updated:

The correlation plot removes repeated information from the plot:

Summarising Through WordClouds

For a text file we can gain an insight into the document through a word cloud.

Wrangling the Data

A suite of transformation functions are available in Rattle to map variables in different ways. Each transformation will create a new variable from the old variable. Here we see min_temp being transformed using the RECENTER feature and each of the transform functions available. The new variables are prefixed with an indicator of the type of transformation performed.

Building Models

A decision tree model is one of the most widely built AI models.

Visualisations are now built and presented by default, compared to Rattle of Old.

The R Console

The R console is where everything in R happens. The user can review the contents of the console and even run R commands themselves. Click the Export button to have the history of R commands from the console saved to file. Compare this Export to that of the Script page where a documented and formatted script is saved to file.

Everything Captured as Scripts

And be assured, the most important of functionalities, the Script tab's capturing of your interactions, remains a key feature of Rattle. All of your interactions with R through Rattle are captured as a documented and nicely formatted script that you can save to file and replicate your whole project simply by asking R to run the script. It is also he starting point for modifying a script to do precisely what you want, beyond what Rattle supports. No lock-in.

gjwgit / rattleng

readme