To run, download the script, load it into R, and type run_analysis(). The script will do the rest and the tidy_data.txt will appear in your data folder in the working directory.
This repository contains a R Script, final data set, code book, and README for the Getting and Cleaning Data course project through Coursera and Johns Hopkins University.
The run_analysis.R script downloads and unzips (if it doesn't already exist in your working directory) a data set collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained:
http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
The run_analysis.R script creates a tidy, well labeled data set consisting of all thirty subjects, the six types of activities that were tracked by the accelerometers, and only the variables that contains mean or standard deviation observations. Lastly, the run_analysis.R script calculates the average for each variable based for each subject for each activity.
- Its subject label.
- Its activity label.
- A 79-feature vector with average mean and standard deviation variables.
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'README.md'
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'run_analysis.R': script for processing the accelerometer data into a clean data set.
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'tidy_data.txt': The final data set produced by the run_analysis.R script.
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'code_book.txt': Shows information about the variables used in the run_analysis.R script.
- The run_analysis.R script takes a few minutes to run because it was written with effectiveness and not efficiency in mind.
For more information about this dataset contact: [email protected]