The files relate to the Coursera "Getting and Cleaning Data" course project and application of instructions by Devon Ly

• README.md - This awesome text file
• CodeBook.md - A descriptive text describe the data used and procedures to transform and clean data
• run_analysis.R - The R code to perform transformation and cleaning
• tidy_data.txt - An output of the above script with relabelled variables and data aggregate as a mean by subject and activity

The instructions for the project were as follows

You should create one R script called run_analysis.R that does the following.

• Merges the training and the test sets to create one data set.
• Extracts only the measurements on the mean and standard deviation for each measurement.
• Uses descriptive activity names to name the activities in the data set
• Appropriately labels the data set with descriptive activity names.
• Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

• If you do not already have the reshape2 package, you will need to install it with the command
  • install.packages("reshape2")
• Download the datasets from https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
• Unzip the file into your working directory
  • The files should be placed into a sub folder called UCI HAR Dataset
• Copy run_analysis.R into your working directory
• Run the R script
  • source("./run_analysis.R")

• Place tidy_data.txt file into your working directory
• Load the data with following command
  • TIDY_DATA <- read.table('./tidy_data.txt')