tabmashburn / getting-cleaning-data-project

Coursera Data Science Specialization Course

Getting-Cleaning-Data-Project

Coursera Data Science Specialization Course Course Project

Project Description

This project is an exercise in acquiring and cleaning data. The project uses data from the UCI Machine Learning Repository: Human Activity Recognition and Smart Phone Data site: Description here.. Data for the project can be downloaded here: Zip Archive Download.

Project Files

Data Processing Script: run_analysis.R

The R script run_analysis.R reads the data files and combines them into one full data file. Important variable values are renamed from numbers to meaningful names. The full set of variables is reduced to a subset that involve means and standard deviations. Variable names are changed to conform with R's legal variable names and to be descriptive.

Tidy Data Output: tidyDataset.txt

The data is then grouped by subject and activity, and summarized by each variable's mean. The end result is a tidy data set, conforming to Hadley Wickham's tidy data principles Tidy Data. The tidy data set is written to the file tidyDataset.txt.

Data Processing Description and Variable Names: CodeBook.md

The file CodeBook.md describes the processing steps and variables used in run_analysis.R and supplements the README.txt included in the original downloaded archive.