Getting and Cleaning Data - Project

run_analysis.R

Forms and stores a tidy summary of the given data. This script performs the following steps:

• Forms a data frame containing features and results for each subject in the training set.
• Forms a data frame containing features and results for each subject in the test set
• Combines these two into a single data frame.
• Sets column names and activity labels.
• Extracts from it a data frame containing mean and standard deviation features for each subject.
• Cleans up column names to be more readable.
• Forms a tidy summary from the new data frame containing averages of mean and standard deviation features for each subject during each activity.

###Results

• data - Contains the combined data of the training and test sets.
• meansDevs - Contains only mean and standard deviation columns for each subject.
• dataSummary - Contains averages of mean and standard deviation values for each combination of activity and subject. It is written to data_summary.txt in the given data folder.

###Assumptions

• The provided data must be unzipped into the working directory before running this script. That is, UCI HAR Dataset must be a subdirectory of the current directory.
• Library reshape2 is required.
• When extracting mean and standard deviation measurements, only columns with names containing -mean() and -std() are used. Those containing -meanFreq() are ignored.
• The tidy data set is created from means/deviations data set and not from the overall data set.
• The final result contains average values for each subject while performing each activity.