Class project for Coursera JHU Getting and Tidying Data 2015-02-22
This project consists of an R script that reads a specific dataset and tidies it according to the class instructions.
The files here are:
README.md - this file
run_analysis.R - the R script that tidies the data
CodeBook.md - a codebook describing the output data file
Not included here:
The input and output files. They are described below, though.
In order to run the R script, you will need a suitable version of R and the dplyr library, and the input data set.
Tested on R version: 3.1.2.
Tested on Mac OSX 10.9.5 (64-bit),
using RStudio Version 0.98.507
Tested on dplyr package version: 0.4.1.
Note, to check if you have dplyr installed, do this at an R prompt:
> installed.packages()["dplyr",c("Package","Version")]
Package Version
"dplyr" "0.4.1"
If, instead of the above response, you get a "subscript out of bounds" error, then you will need to install the dplyr package like this:
> install.packages("dplyr")
Download the following zip file (about 63 MB) and expand it:
https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
That will create the "UCI HAR Dataset" directory (about 270 MB).
The tested version of this dataset was downloaded on Fri Feb 20 14:29:04 2015.
Note, if the dataset is not available at that location, it is possible you can get it
from
http://archive.ics.uci.edu/ml/machine-learning-databases/00240/UCI%20HAR%20Dataset.zip
However, I did not verify that the contents were identical.
See the comments at the top of run_analysis.R for detailed information on how to run the script.
In most cases, just cd to the "UCI HAR Dataset" directory and run the script.
The script will generate an output dataset in whitespace-delimited text form.
The dataset is written to the file tidy_activity_recog_data.txt
in the "UCI HAR Dataset" directory.
See the file CodeBook.md (in the same directory as this README.md file)
for details on the output dataset.