##Overview
This repo contains the code and instructions for the course project of the Coursera Getting and Cleaning Data module of the Data Science specialization.
##Requirements
This procedure executed on Windows 7 using R version 3.1.0 (2014-04-10)
The script requires the following libraries:
- plyr
- reshape2
##Instructions
- Create a directory to work in and set the R working directory to it.
- Obtain the raw dataset from https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
- Copy the zip file and the script run_analysis.R to the working directory.
- Extract the zip file to the working directory. The directory "UCI HAR Dataset" should now exist in the working directory containing the dataset described in the Codebook.
- Execute the script with the following command - source("run_analysis.R")
##Data
The source data and data transformations are described in the Codebook.
In summary, the script:
- Combines training and test data sets
- Extracts specific columns of mean and standard deviation data
- Joins measurement data to subject and activity
- Applies meaningful labels to columns
- Summarize the data to show the average mean and standard deviation measurements organized by subject and activity
- Output the summarized tidy data set
##Output
The tidy data file "tidy_data.txt" will be created in the working directory.