codebook.md

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CodeBook

This codebook describes the variables found in the tidy dataset generated by running run_analysis.R does the following.

    1. Merges the training and the test sets to create one data set.
    2. Extracts only the measurements on the mean and standard deviation for each measurement.
    3. Uses descriptive activity names to name the activities in the data set.
    4. Appropriately labels the data set with descriptive variable names.
    5. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

Original Data

Data Collection Description

The original data set was obtained from [http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones]

It is described as a "Human Activity Recognition database built from the recordings of 30 subjects performing activities of daily living while carrying a waist-mounted smartphone with embedded inertial sensors."

The experiments involved 30 subjects. Each subject performed six activities (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING) with a sensor-equipped smartphone attached to their waist. The smartphone's accelerometer and gyroscope they used to capture 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.

See the above website for further details on sensor signal pre-processing if you are interested.

Required files

• train/subject_train.txt, test/subject_test.txt: Each row identifies the subject who performed the activity for each window sample. Its range is from 1 to 30.

    train [1 3 5 6 7 8 11 14 15 16 17 19 21 22 23 25 26 27 28 29 30]
    test  [2 4 9 10 12 13 18 20 24]
  

• activity_labels.txt: Links the class labels with their activity name.

WALKING	WALKING_UPSTAIRS	WALKING_DOWNSTAIRS	SITTING	STANDING	LAYING
1	2	3	4	5	6

• train/y_train.txt, test/y_test.txt: Each row identifies the class label of an activity. Its range is from 1 to 6.

• features.txt: List of all features. And the tidy data includes only the measurements on the mean and standard deviation for each measurement

• train/X_train.txt, test/X_test.txt: Training and test set. Each row is a 561-feature vector with time and frequency domain variables.

Tidy Data

This picture comes from Course Discussion Forums. It illustrates the relationship between the original data and the tidy data. And in this project, subject.id and activity are moved to the first and second colums.

Complete list of variables by column number

Note that I have cleaned the original variable names for better readability/understanding. See the 'Style' section in README for more info if necessary.

Column No.	Variable Name	Values
1	subject.id	1-30
2	activity	WALKING
		WALKING_UPSTAIRS
		WALKING_DOWNSTAIRS
		SITTING
		STANDING
		LAYING
3	time.body.acceleration.mean.x.averaged
4	time.body.acceleration.mean.y.averaged
5	time.body.acceleration.mean.z.averaged
6	time.body.acceleration.std.x.averaged
7	time.body.acceleration.std.y.averaged
8	time.body.acceleration.std.z.averaged
9	time.gravity.acceleration.mean.x.averaged
10	time.gravity.acceleration.mean.y.averaged
11	time.gravity.acceleration.mean.z.averaged
12	time.gravity.acceleration.std.x.averaged
13	time.gravity.acceleration.std.y.averaged
14	time.gravity.acceleration.std.z.averaged
15	time.body.acceleration.jerk.mean.x.averaged
16	time.body.acceleration.jerk.mean.y.averaged
17	time.body.acceleration.jerk.mean.z.averaged
18	time.body.acceleration.jerk.std.x.averaged
19	time.body.acceleration.jerk.std.y.averaged
20	time.body.acceleration.jerk.std.z.averaged
21	time.body.gyro.mean.x.averaged
22	time.body.gyro.mean.y.averaged
23	time.body.gyro.mean.z.averaged
24	time.body.gyro.std.x.averaged
25	time.body.gyro.std.y.averaged
26	time.body.gyro.std.z.averaged
27	time.body.gyro.jerk.mean.x.averaged
28	time.body.gyro.jerk.mean.y.averaged
29	time.body.gyro.jerk.mean.z.averaged
30	time.body.gyro.jerk.std.x.averaged
31	time.body.gyro.jerk.std.y.averaged
32	time.body.gyro.jerk.std.z.averaged
33	time.body.acceleration.magnitude.mean.averaged
34	time.body.acceleration.magnitude.std.averaged
35	time.gravity.acceleration.magnitude.mean.averaged
36	time.gravity.acceleration.magnitude.std.averaged
37	time.body.acceleration.jerk.magnitude.mean.averaged
38	time.body.acceleration.jerk.magnitude.std.averaged
39	time.body.gyro.magnitude.mean.averaged
40	time.body.gyro.magnitude.std.averaged
41	time.body.gyro.jerk.magnitude.mean.averaged
42	time.body.gyro.jerk.magnitude.std.averaged
43	freq.body.acceleration.mean.x.averaged
44	freq.body.acceleration.mean.y.averaged
45	freq.body.acceleration.mean.z.averaged
46	freq.body.acceleration.std.x.averaged
47	freq.body.acceleration.std.y.averaged
48	freq.body.acceleration.std.z.averaged
49	freq.body.acceleration.jerk.mean.x.averaged
50	freq.body.acceleration.jerk.mean.y.averaged
51	freq.body.acceleration.jerk.mean.z.averaged
52	freq.body.acceleration.jerk.std.x.averaged
53	freq.body.acceleration.jerk.std.y.averaged
54	freq.body.acceleration.jerk.std.z.averaged
55	freq.body.gyro.mean.x.averaged
56	freq.body.gyro.mean.y.averaged
57	freq.body.gyro.mean.z.averaged
58	freq.body.gyro.std.x.averaged
59	freq.body.gyro.std.y.averaged
60	freq.body.gyro.std.z.averaged
61	freq.body.acceleration.magnitude.mean.averaged
62	freq.body.acceleration.magnitude.std.averaged
63	freq.body.body.acceleration.jerk.magnitude.mean.averaged
64	freq.body.body.acceleration.jerk.magnitude.std.averaged
65	freq.body.body.gyro.magnitude.mean.averaged
66	freq.body.body.gyro.magnitude.std.averaged
67	freq.body.body.gyro.jerk.magnitude.mean.averaged
68	freq.body.body.gyro.jerk.magnitude.std.averaged