CodeBook for run_analysis R script
This CodeBook describes the variables, the data, and any transformations or work that is performed to clean up the data for the "Getting and Cleaning Data" course assignment.
The run_analysis.R script performs the data preparation followed by the 5 steps according to course project desxription.
i. Load appropriate libraries (data.table and dplyr libraries)
ii. Download the dataset Dataset downloaded in ./data directory and unzipped under the folder called UCI HAR Dataset of the working directory
iii. Assign each data to variables features <- features.txt : 561 rows, 2 columns The features selected for this database come from the accelerometer and gyroscope 3-axial raw signals tAcc-XYZ and tGyro-XYZ. activities <- activity_labels.txt : 6 rows, 2 columns List of activities performed when the corresponding measurements were taken and its codes (labels) subject_test <- test/subject_test.txt : 2947 rows, 1 column contains test data of 9/30 volunteer test subjects being observed x_test <- test/X_test.txt : 2947 rows, 561 columns contains recorded features test data y_test <- test/y_test.txt : 2947 rows, 1 columns contains test data of activities’code labels subject_train <- test/subject_train.txt : 7352 rows, 1 column contains train data of 21/30 volunteer subjects being observed x_train <- test/X_train.txt : 7352 rows, 561 columns contains recorded features train data y_train <- test/y_train.txt : 7352 rows, 1 columns contains train data of activities’code labels
iv. Merges the training and the test sets to create one data set X (10299 rows, 561 columns) is created by merging x_train and x_test using rbind() function Y (10299 rows, 1 column) is created by merging y_train and y_test using rbind() function Subject (10299 rows, 1 column) is created by merging subject_train and subject_test using rbind() function Merged_Data (10299 rows, 563 column) is created by merging Subject, Y and X using cbind() function
v. Extracts only the measurements on the mean and standard deviation for each measurement TidyData (10299 rows, 88 columns) is created by subsetting Merged_Data, selecting only columns: subject, code and the measurements on the mean and standard deviation (std) for each measurement
vi. Uses descriptive activity names to name the activities in the data set Entire numbers in code column of the TidyData replaced with corresponding activity taken from second column of the activities variable
vi. Appropriately labels the data set with descriptive variable names code column in TidyData renamed into activities All Acc in column’s name replaced by Accelerometer All Gyro in column’s name replaced by Gyroscope All BodyBody in column’s name replaced by Body All Mag in column’s name replaced by Magnitude All start with character f in column’s name replaced by Frequency All start with character t in column’s name replaced by Time
vii. 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 Finaltidydata (180 rows, 88 columns) is created by sumarizing TidyData taking the means of each variable for each activity and each subject, after groupped by subject and activity. Export Finaltidydata into Finaltidydata.txt file.
viii. Show, as a test, the first three lines of the Finaltidydata