Getting and Cleaning Data - Course Project
This repo contains the code that accomplishes the final project of the Getting and Cleaning Data, part of the Data Science Specialization and available at Coursera.
Introduction
The purpose of the project is to demonstrate the skills acquired in the course to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. The original data were collected from the accelerometers from the Samsung Galaxy S smartphone and available at:
https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
The dataset is the result of experiments carried out with a group of 30 volunteers within an age bracket of 19-48 years. Each person performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) wearing a smartphone (Samsung Galaxy S II) on the waist. 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
Project Structure
There are two main files in the project:
- CodeBook.md
- describes the variables, the data and all transformations performed to clean up the data
- run_analysis.R
- executes the cleaning process and output a file called tidyData.txt. More information can be found at the CodeBook.
Installation
The script requires the plyr and dplyr packages, you may need to install them.
install.packages('plyr')
install.packages('dplyr')Usage
Simply run the script called run_analysis.R. If the dataset folder isn't in the current working directory, the script will download and unzip the data. This process may take a while, since the dataset has 60 MB.
The script will produce the tidyData.txt file previously described.