#Getting and Cleaning Data

###Introduction The purpose of this project is to demonstrate ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis.

###Course Requirements

1. a tidy data set
2. a link to a Github repository with script for performing the analysis
3. a code book that describes the variables, the data, and any transformations or work performed to clean up the data called CodeBook.md

###Data Raw data used in this project can be obtained from the following link:

https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

The zip file will extract to a number of data and meta data text files.

###The R Script

An R script reads data files and applies of transformations to obtain tidy data. Operations applied to the data include:

1. Reading Training, Test and Features Data
2. Merging of Training and Test Data
3. Attaching Activity and Subjects Data to Merged Data
4. Removal of Special Characters from Variable Names
5. Calculation of avaerages of Activities per Subject
6. Attaching Labels to Activity Values
7. Writing the Tidy Data to file

###Tidy Data

The tidy data text file (tidy_data.txt) is the result of applying tidy data principles to the raw data. It contains Subjects grouped by all possible activities performed measuring the mean and standard deviations of a number of factors.

###Code Book A codeblock detailing the data, variables and code scripts used is also attached. It lists the input and output data, variables used as well as sequence of transformations applied to the data.