CleanDataAssignment/run_analysis.R at master · Jathinewong/CleanDataAssignment · GitHub

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## Date: August 18 2014
## run_analysis: This function read in datasets, extract the required columns and return the aggregate average of each of the column.
## read_data: This function read in 2 datasets and rbind them.
##
## run_analysis: This function read in datasets, extract the required columns and return the aggregate average of each of the column

run_analysis <- function() {

			features=read.table("UCI HAR Dataset/features.txt", stringsAsFactor=FALSE)

			measurement = read_data("UCI HAR Dataset/train/X_train.txt",
									"UCI HAR Dataset/test/X_test.txt",
									features$V2)

			subject = read_data("UCI HAR Dataset/train/Subject_train.txt",
								"UCI HAR Dataset/test/subject_test.txt",
								"subject")

			activity = read_data("UCI HAR Dataset/train/Y_train.txt",
								"UCI HAR Dataset/test/Y_test.txt",
								"activity")

			## update activity codes to activity labels
			activity = lapply(activity, factor,
								labels=c("WALKING", "WALKING_UPSTAIRS", "WALKING_DOWNSTAIRS",
										"SITTING", "STANDING", "LAYING"))

			## extract the column names of the mean and standard deviation columns from the measurement
			vector_mean = grep("mean\\(\\)", features$V2)
			vector_std = grep("std\\(\\)", features$V2)
			vector_mean_std = c(vector_mean, vector_std)
			names_mean_std = names(measurement)[vector_mean_std]

			attach(measurement)
			attach(subject)
			attach(activity)

			## extract the mean and standard deviation from the measurement data.frame
			measurement_mean_std = subset(measurement, select=names_mean_std)

			## combine the subject, activity and measurement of the mean and std
			subject_activity_mean_std = cbind(subject, activity, measurement_mean_std)

			## aggregate of the average of each mean and std for each subject and each activity
			subject_activity_average = aggregate(as.matrix(subject_activity_mean_std[,3:68]) ~
										subject + activity, data=subject_activity_mean_std, mean)

			## change column names with "avg" for average
			colnames(subject_activity_average) =
					c("subject", "activity", paste("avg_", colnames(measurement)[3:68], sep=""))

			attach(subject_activity_average)

			## check for file exists
			if ( file.exists("subject_activity_average.txt") ) {
					print("Failed to write to file \"subject_activity_average.txt\", file already exists",
							quote=FALSE)
			}
			else {
					write.table(subject_activity_average, "./subject_activity_average.txt",
						row.name=FALSE, quote=FALSE)
			}

			print("Wrote subject_activity_average.txt file to current directory")

}

## read_data: This function read in two files and combine them by rows
read_data <- function(file_str1, file_str2, column_name) {

			file1 = read.table(file_str1)
			file2 = read.table(file_str2)
			combine_files = rbind(file1, file2)

			## set column names
			colnames(combine_files) = column_name

			return(combine_files)
}