Getting and Cleaning Data Course Project

Project of Getting and Cleaning Data course on Coursera - September 2015.

Project Description

The purpose of this project is to demonstrate your ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. You will be graded by your peers on a series of yes/no questions related to the project.

You will be required to submit:

1. a tidy data set as described below
2. a link to a Github repository with your script for performing the analysis, and
3. a code book that describes the variables, the data, and any transformations or work that you performed to clean up the data called CodeBook.md. You should also include a README.md in the repo with your scripts. This file explains how all of the scripts work and how they are connected.

What you find in this repository

• CodeBook.md: information about raw and tidy data set and elaboration made to transform them
• LICENSE: license terms for text and code
• README.md: this file
• run_analysis.R: R script to transform raw data set in a tidy one

How to create the tidy data set

1. clone this repository: git clone https://github.com/pedroa2silva/coursera-gettingandcleaningdata-project.git
2. open a R console and set the working directory to the repository root (use setwd())
3. source run_analisys.R script (it requires the plyr package): source('run_analysis.R'). The code will download the file to a data folder under the working directory you selected. Note: If you're running on a Mac machine uncomment the line download.file(fileUrl,destfile=destFileNameAndPath, method = "curl") and comment the previous line download.file(fileUrl,destfile=destFileNameAndPath)

When the code finishes running you will find in the repository root directory the file tidydata.txt with the tidy data set.