Human-Activity-Recognition

This repository contains material for the course project of the Coursera course "Getting and Cleaning Data", part of the Data Science specialization. The overall aim of this project is to write an R script generating a tidy dataset from raw data, along with a CodeBook describing the variables, the data, and the transformations performed to clean up the data.

The data used for this project are data collected from the accelerometers from the Samsung Galaxy S smartphone. They are provided by the UCI machine learning repository, a full description is available here.

Content

• run_analysis.R: the main script performing the analysis
• Readme.md
• CodeBook.md: describes data transformation and content of the tidy dataset generated

Pre-requisite

The R script does not include code to download the source data. The latter are described and can be obtained here. They can also be downloaded directly from here.

For the run_analysis.R script to run properly, data have to be downloaded and extracted to a folder named "UCI HAR Dataset" within R's working directory.

Notes

• The script only uses the base R package
• After running run_analysis.R, the tidy dataset is written to a text file tidy.txt. To read and display the dataset, use the following commands :

data <- read.table("tidy.txt", header = TRUE, check.names = FALSE)
View(data)