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variables_codebook.txt
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variables_codebook.txt
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#######################################################################################################################
Code book : description of the variables from the text file "avgMeasures.txt" created by the code of "run_analysis.R" file
#######################################################################################################################
The data was extract, transform and load from "Human Activity Recognition Using Smartphones Data Set Version 1.0" research. The source is :
Jorge L. Reyes-Ortiz, Davide Anguita, Alessandro Ghio, Luca Oneto.
Smartlab - Non Linear Complex Systems Laboratory
DITEN - Università degli Studi di Genova.
Via Opera Pia 11A, I-16145, Genoa, Italy.
activityrecognition@smartlab.ws
www.smartlab.ws
----------------------------------------------------------------------------------------------------------------------
The "avgMeasures.txt" file goal was to make a tidy data set with explicit variables names and no intermediate variables or data sets.
In that sense the "avgMeasures.txt" variables are :
[1] "feature"
Features measurements names which come from the original core features names but without any triaxial specicifaction if applied,
17 possibilities :
tBodyAcc
tGravityAcc
tBodyAccJerk
tBodyGyro
tBodyGyroJerk
tBodyAccMag
tGravityAccMag
tBodyAccJerkMag
tBodyGyroMag
tBodyGyroJerkMag
fBodyAcc
fBodyAccJerk
fBodyGyro
fBodyAccMag
fBodyAccJerkMag
fBodyGyroMag
fBodyGyroJerkMag
[2] "estimateparameter"
Axies specification from triaxial measurement for some concerned "feature". "feature" where axial measurement is out-of-context are fill with NAs values,
4 possibilities :
X
Y
Z
NA
[3] "estimate"
Mean and standard deviation of Samsung signals calculations made for each "feature" which come from the original source,
2 possibilities :
mean()
std()
[4] "activity"
Activity name perfomed by subject during "feature" measurements which come from the original source,
6 possibilities :
WALKING
WALKING_UPSTAIRS
WALKING_DOWNSTAIRS
SITTING
STANDING
LAYING
[5] "subjectid"
Number id for each of the 30 subject which come from the original source,
30 possibilities :
from 1 to 30 //not displayed since it's obsious and will waste space
[6] "mean(value)"
Average value of each "feature" for either each triaxial measurement or none triaxial specification, each "activity" and each "subjectid",
11 880 observations :
8 triaxial features
* 3 axes
+ (17-8) none-axial features
____________________________
33 features
* 2 estimates
* 6 activities
* 30 subject
____________________________
11 880 observations