Getting And Cleaning Data @Coursera

Course Project

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.

Dataset Description

The project taps into an exciting area of wearable computing, where a number of big brands compete to develop clever algorithms. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. 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

Here are the data for the project:

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

Requirements

Create an R script called run_analysis.R that does the following:

1. Merges the training and the test sets to create one data set.
2. Extracts only the measurements on the mean and standard deviation for each measurement.
3. Uses descriptive activity names to name the activities in the data set
4. Appropriately labels the data set with descriptive variable names.
5. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

Project Outcome

In sync with the requirements this project comprises:

1. a tidy data set based on the original data set: tidy_data.txt and tidy_data.csv (nicely formatted on GitHub)
2. an R script called run_analysis.R for performing the analysis
3. a code book called CodeBook.md that describes variables, data and any transformations or work performed to clean up the data

Other Resources

• Human Activity Recognition Using Smartphones Data Set
• Data Science & Wearable Computing Battle