One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained:
http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
This repository has the R code and relevant documentation for project for "Getting and Cleaning data", Coursera.
The dataset being used is: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
Files used:
I have used all the files afer unzipping the dataset.
CodeBook.md: Description of variables declared and the datasets used.
run_analysis.R: This repo explains how all of the scripts work and how they are connected. The entire code starts right from downloading and unzipping the data to creation of final tidy dataset.
The final output is called tidy.txt, and uploaded in the course project's form.