Coursera: "Getting and Cleaning Data" Course Project

Week 3 Course Project for Coursera's Getting and Cleaning Data within the Data Analysis in R specialization.

run_analysis.R merges testing and training data sets and their associated subjects and labels from within a zip file. This is the primary file within the repo and requires the data to be downloaded separately. Data should be put in the ./data subdirectory for R script to work.

Location of data https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

Description of data: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

README_rawdata.txt provides information on the raw telemetry data.

Description of run_analysis.R

1. R script extracts the time-summarized data from the archive. This includes time-means, standard deviations, min, max, etc.
2. Pulls the subject and activity labels and merges them with the testing and training data sets.
3. Appends the testing data to the training data.
4. Relabels the data frame according to the archived "features.txt" list, and removes "()" from name.
5. Creates factor variable with informative labels for "activity".
6. Keeps columns corresponding to the mean and standard deviation.
7. Creates new ensemble mean for each subject (1 to 30) and each activity (1 to 6). Outputs this dataset.