Course project for Coursera course Getting and Cleaning Data.
The aim of the project is to extract a tidy data set from the provided raw data set. The linked data represents data collected from accelerometers from a smartphone that may presumably be used to predict a subjects activity, e.g. walking or runing.
- run_analysis.R
An R script for producing the tidy data set (see instructions below). - CodeBook.md
A code book with explanations of the variables in the resulting tidy data set.
The R script has comments to make it clear where all the five steps outlined in the assignment take place. More importantly, R variable names are quite detailed.
- It is assumed that the raw data has been extracted to a directory called "UCI HAR Dataset" that must be located in the working directory.
- To generate the tidy data, run the script run_analysis.R, e.g. as follows:
source("run_analysis.R")
* This will generate the tidy data as an R data frame variable activity.subject.averages and write it to disk in a file another_tidy_dataset.txt
* (The script also "pollutes" the environment with variables used along the way to create the tidy data set.)