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Getting and Cleaning Data Course Project

This project provides the required 'R' script to perform cleaning operations on a set of data obtained from a Human Activity Recognition test performed uses a Samsung Galaxy S smartphone.

The run_analysis.R script will read in the training and test data sets and perform the necessary operations to insure the data is 'Tidy'. Before cleaning, additional tests are performed on the input data to insure that the number of rows/columns match what is expected from each table. If a fatal error or flaw in the data is detected, an error message will be displayed indicating the error. Should you receive this error, you may need to download a clean set of data and attempt the analysis again. See Downloading the Original Data below for more information on how to obtain the original data.

Running the script

To run the script, start R, source the run_analysis.R script, and then run the run_analysis(). For example, from the directory containing the R Script enter:

prompt> R --quiet
> source("run_analysis.R")
> run_analysis()

This will read and tidy the data and create any output files in the output subdirectory by default. Upon successfull completion, the script will output Done and return you to the R prompt.

Downloading the Original Data

The oroginal data is available is included in this Github project in the origData (zip file) and data (expanded files) subdirectory. The link to the original data is provided below and you can use the supplied getData.R script to automatically download it for you. Simply use the getData() function after sourcing the getData.R script.

original data set

Version Information

The following version of R and R Libraries were used to read and clean the data.

  • R version 3.1.2 (2014-10-31) -- "Pumpkin Helmet"
  • data.table -- 1.9.5
  • plyr -- 1.8.1
  • stringr -- 0.6.2

The operating system was Ubuntu 14.04 on a 64-bit x86 platform

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R Scripts, READMEs, and data for the Coursera Getting and Cleaning Data course project

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