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Course Project for Getting and Cleaning Data Coursera/JHU May 2014

Repo contents

  • run_analysis.R : R script that reads all data and creates 2 output files of clean data
  • readme.md : informational document
  • codebook : descriptions of features

Instructions for use:

  • create a project folder on your local machine
  • in R (or RStudio) set that to your "working directory" [setwd()]
  • save the script run_analysis.R (found here) to that project directory
  • run the script
  • 2 result files will be written to a subfolder /output/

Raw Data / Data Source

The raw data is in a zip file. There is no need to save the data via link as the script run_analysis.R will download and unpack the data. Source link is provied here in case there is any problem running the script. Script was written on a Linux OS and should be compatible with all distros and Mac OS. Script has not been tested on Windows or any other OS.

Script

When the script run_analysis.R is run it will do the following

  • download the source data zip file and unpack the data to a subfolder named "UCI HAR dataset"
  • Merges the training and the test sets to create one data set.
  • Extracts only the measurements on the mean and standard deviation for each measurement.
  • Replaces the activity codes in the dataset with decriptive names from /UCI HAR Dataset
  • Expands dataset feature names
  • writes this cleaned up dataset to /output/tidydata.txt
  • Creates a second, independent tidy data set with the average of each variable for each activity and each subject and writes it to /output/tidyDataGrouped.txt

Code Book

Will describe names of features

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repo containing course project for class "Getting and Cleaning Data" Coursera/JHU May 2014

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