This repository relates to the programming assignment of the Getting and Cleaning Data MOOC that is part of the Data Science Specialization offered by Johns Hopkins University and delivered on Coursera.
download_data.R This R script downloads the Human Activity Recognition Using Smartphones (HARUS) data set, which is the source data used in the programming assignment. The R working directory that's defined when the script is run is to be shared by all R scripts. The script creates a directory called 'data' within the working directory and stores the downloaded .zip file in that directory. Once downloaded, unzip the .zip file within the 'data' directory. Do not alter the unzipped directory structure or directory or file names in any way.
run_analysis.R This R script runs the analysis that constitutes the bulk of the programming assignment. This script must be run after download_data.R and before run_analysis_2.R. It reads the HARUS data set files and combines, transforms and subsets them to produce a data set called tidy_data_1.txt. See the file CodeBook.md for more details on the processing performed. This script also produces a file called codebook_features.txt which is data used to create the file CodeBook.md.
run_analysis_2.R This R script runs a secondary analysis, taking tidy_data_1.txt as input and producing a summary called tidy_data_2.txt. The summary gives the mean of each feature for each combination of Subject and Activity (see CodeBook.md). This script depends on and must be run after run_analysis.R.
codebook_features.txt An ancillary output of run_analysis.R containing a mapping between feature column IDs and feature names.
tidy_data_1.txt The primary output produced by run_analysis.R. (See the file CodeBook.md for a description).
tidy_data_2.txt The output produced by run_analysis_2.R
Assignment_description.txt A description of the programming assignment which motivated the development of the repository and its contents.
README.md This file.
CodeBook.md A description of tidy_data_1.txt