This repository contains the submission for the Getting and Cleaning Data Course Project peer-graded assignment.

run_analysis.R is a R script with the following functionality.

1. Download and unzips the data archive if the data directory UCI HAR Dataset is not found
2. Read the files subject_train.txt, subject_test.txt, X_train.txt, X_test.txt, y_train.txt, y_test.txt using read.table
3. Merging all data sets into a variable called activity and clearing unused variables
4. Applying the column names subject and label to first and second column and reading the remaining column names from the file 'features.txt'
5. Subsetting the data set to only include column that have mean(), std(), subject or label in their names using grepl
6. Using the factor function to replace the 'label' observations with the activity names from the file from activity_labels.txt
7. Remove the brackets form the variable names, and lowercase all label observations
8. Requiring the dplyr package, the script uses the group_by and summarize_at functions to generate a new tidy data set with the average of each variable for each activity and each subject
9. Writing out the resulting tidy data set into a file called activity_mean.csv and the data set features into a file named activity_mean-features.txt

The codebook for the resulting tidy data set in provided in a file named activity_mean-codebook.txt, in the same format and style as the codebook features_info.txt from the original data UCI HAR Dataset set.