Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

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Rattle Startup

After starting R (perhaps via RStudio) we can start up rattle, a graphical user interface for the data scientist, from the R Console prompt. Simply load the rattle package then invoke the rattle() command, as in:

library(rattle)
rattle()

The above Rattle window will display, ready to load data, explore and test the data, transform the data, and then begin building models from the data.

The interface aims to be simple and easy to use. The row of buttons support the basic operations, particularly the Execute button which we click so that the particular tab setting take effect or its associated operation is performed. Below the buttons are a series of tabs that represent the major steps of a data science project. In general we work through the tabs from the left to right, loading some data, exploring and testing the data, performing some transformations on the data, doing a cluster and/or association analysis, building a predictive model, and evaluating the performance of the model.

After setting up the requirements and settings for a particular tab, be sure to click the Execute button to have the settings within tab take effect, or else perform the task associated with the tab.