igivis7/cleaning_and_getting_data_programming_assignment

Cleaning and Getting Data Course Programming Assignment

Cleaning and Getting Data Course Programming Assignment

The task of the course programming assignment is an analysis of sensors (accelerometer and gyroscope) data generated from experiments with Samsung Galaxy S II smartphones. The experiment details can be found in references 1, 2 and 3.

Within this course programming assignment there was an R script 'run_analysis.R' created that does the following:

• Part I: Merges the training and the test sets to create one data set.
• Part II: Extracts only the measurements on the mean and standard deviation for each measurement.
• Part III: Uses descriptive activity names to name the activities in the data set.
• Part IV: Appropriately labels the data set with descriptive variable names.
• Part V: From the data set in step IV, creates a second, independent tidy data set with the average of each variable for each activity and each subject.

The last data set is saved to the 'run_analysis_output.txt' file.

The Programming Assignment includes the following files

• 'README.md' - this file with course programming assignment description.
• 'run_analysis.R' - R script that does data manipulating.
• 'CodeBook.md' - Describes the experiment data variables and the steps taken to obtain final result.
• 'run_analysis_output.txt' - Output file generated by the run_analysis.R script.

Structure of the data files

The path to the data from smartphone sensors (folder 'UCI HAR Dataset') must be defined in the variable 'data_Location' in the script 'run_analysis.R'. The current version of the script must be placed at the same location as 'UCI HAR Dataset' folder

The folder 'UCI HAR Dataset' structure is meant to be following:
 |-- activity_labels.txt
 |-- features_info.txt
 |-- features.txt
 |-- README.txt
 |-- test
 |   |-- Inertial Signals
 |   |   |-- body_acc_x_test.txt
 |   |   |-- body_acc_y_test.txt
 |   |   |-- body_acc_z_test.txt
 |   |   |-- body_gyro_x_test.txt
 |   |   |-- body_gyro_y_test.txt
 |   |   |-- body_gyro_z_test.txt
 |   |   |-- total_acc_x_test.txt
 |   |   |-- total_acc_y_test.txt
 |   |   |-- total_acc_z_test.txt
 |   |-- subject_test.txt
 |   |-- X_test.txt
 |   |-- y_test.txt
 |-- train
     |-- Inertial Signals
     |   |-- body_acc_x_train.txt
     |   |-- body_acc_y_train.txt
     |   |-- body_acc_z_train.txt
     |   |-- body_gyro_x_train.txt
     |   |-- body_gyro_y_train.txt
     |   |-- body_gyro_z_train.txt
     |   |-- total_acc_x_train.txt
     |   |-- total_acc_y_train.txt
     |   |-- total_acc_z_train.txt
     |-- subject_train.txt
     |-- X_train.txt
     |-- y_train.txt

References

• [1] Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. International Workshop of Ambient Assisted Living (IWAAL 2012). Vitoria-Gasteiz, Spain. Dec 2012
• [2] http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
• [3] README.txt of the dataset: http://archive.ics.uci.edu/ml/machine-learning-databases/00240/UCI%20HAR%20Dataset.zip