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Introduction

Dataset data_tidy.txt is created by running run_analysis.R.

  • Firstly, all the files needed are read into R. To merge the training and testing data, first, combine Xtrain, sub_train which contains subjectID, and ytrain by column to form training dataset. Do the same to form the testing dataset. Then combine those two sets by row.
  • To perform the 2nd step, only those columns with the mean and standard deviation measures should be selected.
  • According to the activity labels, match the ActivityID in the dataset from step 2. This will allow the activity has a decriptive name.
  • Some features with Body in the names repeated twice are corrected.
  • Finally, by averageing each variable for each activity and each subject, data_tidy.txt is created.

Data and Variables Descriptions

  • For the final dataset data_tidy.txt, there are 180 rows with 66 selected features as well as "ActivityName" and "SubjectID". The names of variables are listed below
names(data_tidy)
 [1] "ActivityName"            "SubjectID"               "tBodyAcc-mean()-X"      
 [4] "tBodyAcc-mean()-Y"       "tBodyAcc-mean()-Z"       "tBodyAcc-std()-X"       
 [7] "tBodyAcc-std()-Y"        "tBodyAcc-std()-Z"        "tGravityAcc-mean()-X"   
[10] "tGravityAcc-mean()-Y"    "tGravityAcc-mean()-Z"    "tGravityAcc-std()-X"    
[13] "tGravityAcc-std()-Y"     "tGravityAcc-std()-Z"     "tBodyAccJerk-mean()-X"  
[16] "tBodyAccJerk-mean()-Y"   "tBodyAccJerk-mean()-Z"   "tBodyAccJerk-std()-X"   
[19] "tBodyAccJerk-std()-Y"    "tBodyAccJerk-std()-Z"    "tBodyGyro-mean()-X"     
[22] "tBodyGyro-mean()-Y"      "tBodyGyro-mean()-Z"      "tBodyGyro-std()-X"      
[25] "tBodyGyro-std()-Y"       "tBodyGyro-std()-Z"       "tBodyGyroJerk-mean()-X" 
[28] "tBodyGyroJerk-mean()-Y"  "tBodyGyroJerk-mean()-Z"  "tBodyGyroJerk-std()-X"  
[31] "tBodyGyroJerk-std()-Y"   "tBodyGyroJerk-std()-Z"   "tBodyAccMag-mean()"     
[34] "tBodyAccMag-std()"       "tGravityAccMag-mean()"   "tGravityAccMag-std()"   
[37] "tBodyAccJerkMag-mean()"  "tBodyAccJerkMag-std()"   "tBodyGyroMag-mean()"    
[40] "tBodyGyroMag-std()"      "tBodyGyroJerkMag-mean()" "tBodyGyroJerkMag-std()" 
[43] "fBodyAcc-mean()-X"       "fBodyAcc-mean()-Y"       "fBodyAcc-mean()-Z"      
[46] "fBodyAcc-std()-X"        "fBodyAcc-std()-Y"        "fBodyAcc-std()-Z"       
[49] "fBodyAccJerk-mean()-X"   "fBodyAccJerk-mean()-Y"   "fBodyAccJerk-mean()-Z"  
[52] "fBodyAccJerk-std()-X"    "fBodyAccJerk-std()-Y"    "fBodyAccJerk-std()-Z"   
[55] "fBodyGyro-mean()-X"      "fBodyGyro-mean()-Y"      "fBodyGyro-mean()-Z"     
[58] "fBodyGyro-std()-X"       "fBodyGyro-std()-Y"       "fBodyGyro-std()-Z"      
[61] "fBodyAccMag-mean()"      "fBodyAccMag-std()"       "fBodyAccJerkMag-mean()" 
[64] "fBodyAccJerkMag-std()"   "fBodyGyroMag-mean()"     "fBodyGyroMag-std()"     
[67] "fBodyGyroJerkMag-mean()" "fBodyGyroJerkMag-std()"
Variable name Description
subjectID ID the subject who performed the activity for each window sample. Its range is from 1 to 30.
ActivityName Activity name

The description of other features can be found in features_info.txt