Getting and Cleaning Data Course Project This is the course project for the Getting and Cleaning Data Coursera course. The included R script, run_analysis.R, conducts the following: 1 - Download the dataset from web if it does not already exist in the working directory. 2 - Read both the train and test datasets and merge them into x(measurements), y(activity) and subject, respectively. 3 - Load the data(x's) feature, activity info and extract columns named 'mean'(-mean) and 'standard'(-std). Also, modify column names to descriptive. (-mean to Mean, -std to Std, and remove symbols like -, (, )) 4 - Extract data by selected columns(from step 3), and merge x, y(activity) and subject data. Also, replace y(activity) column to it's name by refering activity label (loaded step 3). 5 - Generate 'Tidy Dataset' that consists of the average (mean) of each variable for each subject and each activity. The result is shown in the file tidy_dataset.txt.
This course project is to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis.
The data for this project can be downloaded through the following link: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
Full description of the data can be found here: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
CodeBook.md. describes the variables, the data, and any work that are performed to clean up the data.
run_analysis.R contains all the coding for doing the course project, that includes downloading and unzipping the dataset that is used for this project.
averagedata.txt is a written out text file from run_analysis.R, which is the average features of each subject and each activity. Please refer to CodeBook.md. for more explicit information.