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Getting & Cleaning Data Course Project CookBook

This document describes the variables, the data, and any transformations or work that was performed to clean up a dataset into a tidy one in the context of the course project. The original dataset relates to Human Activity Recognition Using Smartphones. This reference also provides the background information necessary to understand this document and the transformations applied to the original dataset.

Transformed Dataset

The following are the variables resulting from transforming the original dataset into the tidy dataset as found in the out.txt result file:

  • activity
  • subject
  • tBodyAcc.[mean,std].[X,Y,Z]
  • tGravityAcc.[mean,std].[X,Y,Z]
  • tBodyAccJerk.[mean,std].[X,Y,Z]
  • tBodyGyro.[mean,std].[X,Y,Z]
  • tBodyGyroJerk.[mean,std].[X,Y,Z]
  • tBodyAccMag.[mean,std]
  • tGravityAccMag.[mean,std]
  • tBodyAccJerkMag.[mean,std]
  • tBodyGyroMag.[mean,std]
  • tBodyGyroJerkMag.[mean,std]
  • fBodyAcc.[mean,std].[X,Y,Z]
  • fBodyAcc.meanFreq.[X,Y,Z]
  • fBodyAccJerk.[mean,std].[X,Y,Z]
  • fBodyAccJerk.meanFreq.[X,Y,Z]
  • fBodyGyro.[mean,std].[X,Y,Z]
  • fBodyGyro.meanFreq.[X,Y,Z]
  • fBodyAccMag.[mean,std]
  • fBodyAccMag.meanFreq
  • fBodyBodyAccJerkMag.[mean,std]
  • fBodyBodyAccJerkMag.meanFreq
  • fBodyBodyGyroMag.[mean,std]
  • fBodyBodyGyroMag.meanFreq
  • fBodyBodyGyroJerkMag.[mean,std]
  • fBodyBodyGyroJerkMag.meanFreq
  • angletBodyAccMean.gravity
  • angletBodyAccJerkMean.gravityMean
  • angletBodyGyroMean.gravityMean
  • angletBodyGyroJerkMean.gravityMean
  • angle[X,Y,Z].gravityMean

where [mean,std] denotes that a variable has both 'mean' and 'std' versions, and [X,Y,Z] implies distinct X, Y and Z values. For instance, tBodyAcc.[mean,std].[X,Y,Z] expands to:

  • tBodyAcc.mean.X
  • tBodyAcc.mean.Y
  • tBodyAcc.mean.Z
  • tBodyAcc.std.X
  • tBodyAcc.std.Y
  • tBodyAcc.std.Z

activity represents the activity performed by the test subject and is one of WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, or LAYING.

subject represents the unique identity of the person who performed the activity and is an integer in the range [1, 30].

The full description and units of the other variables is available here. This basically covers mean and standard deviation values (i.e. std) of various accelerations and angular velocities.

Transformations

The following steps have been carried out over the original dataset resulting in the output file out.txt:

  • Download and unzip the dataset
  • Merge the training and the test sets to create one dataset
  • Extract only the measurements on the mean and standard deviation for each measurement
  • Use descriptive activity names to name the activities in the dataset
  • Appropriately label the dataset with descriptive variable names
  • Create an independent tidy dataset with the average of each variable for each activity and each subject

These transformations are implemented in the run_analysis.R file which contains further details on each one of these steps.

References