Codebook.md

Coursera Getting and cleaning data project Code book:

This is a Code book to describe the tidy_data.txt and how it was transformed from the given data

1. Original data:

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The original data and how it was colleced can be found in: Click here

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The original data file is provided as a zip folder which contains:

• UCI HAR Dataset (Folder) contains:

  • README.txt
  • activity_labels.txt
  • features.txt
  • features_info.txt
  • test (folder)
    • X_test.txt
    • subject_test.txt
    • y_test.txt
    • Inertial Signals (folder)
      • 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
  • train (folder)
    • X_train.txt
    • subject_train.txt
    • y_train.txt
    • Inertial Signals (folder)
      • 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

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2. Tidy data:

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The transformed final data is represented in the tidy_data.csv file which is formed of 81 columns that contains the means of mean values and standard deviation values of each variable per human subject and activity type. Total 180 reading of 2 identifiers (subject and activity) and 79 variables. the total number of subjects who performed the test is 30. they are:

• Identifiers:
  1. subjects
  2. activity
• Variables:
  1. timebodyacc_mean_x
  2. timebodyacc_mean_y
  3. timebodyacc_mean_z
  4. timebodyacc_std_x
  5. timebodyacc_std_y
  6. timebodyacc_std_z
  7. timegravityacc_mean_x
  8. timegravityacc_mean_y
  9. timegravityacc_mean_z
  10. timegravityacc_std_x
  11. timegravityacc_std_y
  12. timegravityacc_std_z
  13. timebodyaccjerk_mean_x
  14. timebodyaccjerk_mean_y
  15. timebodyaccjerk_mean_z
  16. timebodyaccjerk_std_x
  17. timebodyaccjerk_std_y
  18. timebodyaccjerk_std_z
  19. timebodygyro_mean_x
  20. timebodygyro_mean_y
  21. timebodygyro_mean_z
  22. timebodygyro_std_x
  23. timebodygyro_std_y
  24. timebodygyro_std_z
  25. timebodygyrojerk_mean_x
  26. timebodygyrojerk_mean_y
  27. timebodygyrojerk_mean_z
  28. timebodygyrojerk_std_x
  29. timebodygyrojerk_std_y
  30. timebodygyrojerk_std_z
  31. timebodyaccmag_mean
  32. timebodyaccmag_std
  33. timegravityaccmag_mean
  34. timegravityaccmag_std
  35. timebodyaccjerkmag_mean
  36. timebodyaccjerkmag_std
  37. timebodygyromag_mean
  38. timebodygyromag_std
  39. timebodygyrojerkmag_mean
  40. timebodygyrojerkmag_std
  41. frequencybodyacc_mean_x
  42. frequencybodyacc_mean_y
  43. frequencybodyacc_mean_z
  44. frequencybodyacc_std_x
  45. frequencybodyacc_std_y
  46. frequencybodyacc_std_z
  47. frequencybodyacc_meanfreq_x
  48. frequencybodyacc_meanfreq_y
  49. frequencybodyacc_meanfreq_z
  50. frequencybodyaccjerk_mean_x
  51. frequencybodyaccjerk_mean_y
  52. frequencybodyaccjerk_mean_z
  53. frequencybodyaccjerk_std_x
  54. frequencybodyaccjerk_std_y
  55. frequencybodyaccjerk_std_z
  56. frequencybodyaccjerk_meanfreq_x
  57. frequencybodyaccjerk_meanfreq_y
  58. frequencybodyaccjerk_meanfreq_z
  59. frequencybodygyro_mean_x
  60. frequencybodygyro_mean_y
  61. frequencybodygyro_mean_z
  62. frequencybodygyro_std_x
  63. frequencybodygyro_std_y
  64. frequencybodygyro_std_z
  65. frequencybodygyro_meanfreq_x
  66. frequencybodygyro_meanfreq_y
  67. frequencybodygyro_meanfreq_z
  68. frequencybodyaccmag_mean
  69. frequencybodyaccmag_std
  70. frequencybodyaccmag_meanfreq
  71. frequencybodybodyaccjerkmag_mean
  72. frequencybodybodyaccjerkmag_std
  73. frequencybodybodyaccjerkmag_meanfreq
  74. frequencybodybodygyromag_mean
  75. frequencybodybodygyromag_std
  76. frequencybodybodygyromag_meanfreq
  77. frequencybodybodygyrojerkmag_mean
  78. frequencybodybodygyrojerkmag_std
  79. frequencybodybodygyrojerkmag_meanfreq

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3. Transformation:

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• Downloaded the dataset zip file.

• Unzipped the file

• Read the Readme.md file with provided with the data.

• Read the activity and features file of the study.

• Filered the features to contains only columns names that has ( mean and std).

• Read the tables for both training and test folders.

• Changed the activity values from y_test.txt and y.train.txt to the activity names.

• Selected the required columns with the help of features table.

• Cleaned the columns names from features file

   Getting the names of the columns fixed properly (replaced "t" with "time"
  , "f" with "frequency" , "-" with blank repalced typos , removed "\\()"
  ,changed all letters to lower case letters and replaced all blansk with "_")
  

• Created two tables for test and train with subjects and activity names.

• Combined the tables for training and testing.

• Grouped the resulting table by subject first then activity.

• Calculated means of all variables.