Peer-graded Assignment: Getting and Cleaning Data Course

• Dataset:Human Activity Recognition Using Smartphones Dataset - Version 1.0

  The experiments have been carried out with a group of 30 volunteers within an age bracket of 19-48 years. Each person performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) wearing a smartphone (Samsung Galaxy S II) on the waist. Using its embedded accelerometer and gyroscope, we captured 3-axial linear acceleration and 3-axial angular velocity at a constant rate of 50Hz. The experiments have been video-recorded to label the data manually. The obtained dataset has been randomly partitioned into two sets, where 70% of the volunteers was selected for generating the training data and 30% the test data.

• It has the instructions on how to run analysis on Human Activity recognition dataset.

run_analysis.R performs the data preparation and then followed by the steps required as described in the course project’s instructions:

• Downloaded the Dataset zip file.Unzipped the Dataset
• Loaded datasets from text files.
  • features_info.txt
  • features.txt
  • activity_labels.txt
  • train/X_train.txt
  • train/y_train.txt
  • test/X_test.txt
  • test/y_test.txt
  • train/subject_train.txt
  • train/Inertial Signals/total_acc_x_train.txt
  • train/Inertial Signals/body_acc_x_train.txt
  • train/Inertial Signals/body_gyro_x_train.txt
• Merged the training and the test sets to create one data set.
• Binded Activity name and subject code to merged data set
• Used descriptive activity names to name the activities in the data set
• Extracted only the measurements on the mean and standard deviation for each measurement.
• Appropriately labeled the data set with descriptive variable names.
• Created a second, independent tidy data set with the average of each variable for each activity and each subject.
• Final_tidydataset.txt is the exported final data after going through all the sequences described above.

Files

CodeBook.md a code book that describes the variables, the data, and any transformations or work that I performed to get and clean up the data