Getting and Cleaning Data

##Overview

This is a repository for project 2 of the Getting and Cleaning Data Coursera course (Johns Hopkins University).

Setting Up

1. Download the following file and save it to your computer (eg. your Desktop):

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

2. Extract it using a decompression program like 7zip. Remember this directory, you'll need it later. During the extraction, a folder named "./UCI HAR Dataset" will be created containing some data which is for information purposes only along with the following 8 essential files without which the script will fail:

3. ./test/x_train.txt

4. ./test/y_train.txt

5. ./test/subject_train.txt

6. ./train/x_train.txt

7. ./train/subject_train.txt

8. ./train/y_train.txt

9. ./features.txt

10. ./activity_labels.txt

11. Download and save run_analysis.R to your computer and source it using the source() command. (type ?source in the RStudio console if you don't know how to do this)

Running the script

1. In RStudio at the r console, you can do one of the following to run the script: 1. Use the setwd() command to navigate to the "./UCI HAR Dataset" path you created in step 2 of the setting up section. You can then run analyze() to run the script (For help using the setwd() command, type ?setwd in the RStudio at the r console)

2. Pass the path as a parameter to the analyze() function (eg. analyze("./UCI HAR Dataset"))

3. The script will now run, tellling you what it's doing as it does it. In a nutshell it performs the following actions:

4. Merges the training and the test sets to create one data set.

5. Extracts only the measurements on the mean and standard deviation for each measurement.

6. Uses descriptive activity names to name the activities in the data set

7. Appropriately labels the data set with descriptive variable names.

8. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

9. After successful completion of the script, 2 files will be created:

10. ./data-cleaned.txt (Contains the merged data from the training and test sets, as well as the corresponding tidy labels.)

11. ./data-averages.txt (Contains all the averaged data from the cleaned data table created in the other file. It should contain 180 rows and 68 columns as there are 30 subjects and 6 activities (30*6), so for each activity and each subject we calculated means 30 * 6 = 180 rows.)