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 repo explains how all of the scripts work and how they are connected.
One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. 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:
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
Download the zip file from the location and unzip to folder getdata-projectfiles-UCI HAR Dataset
getdata-projectfiles-UCI HAR Dataset will now contain the folder getdata-projectfiles-UCI HAR Dataset/UCI HAR Dataset
### Installing
Download the file run_analysis.R from the repository https://github.com/pruthvirajv/GettingAndCleaningData into the folder getdata-projectfiles-UCI HAR Dataset folder as described earlier
## Running the tests
Execute the following command on the command prompt of R.
Ensure current working directory is set to getdata-projectfiles-UCI HAR Dataset
GenerateTidyDateaSet()