This code book is part of the getting and cleaning data project
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##Data
- Triaxial acceleration from the accelerometer (total acceleration) and the estimated body acceleration.
- Triaxial Angular velocity from the gyroscope.
- A 561-feature vector with time and frequency domain variables.
- Its activity label.
- An identifier of the subject who carried out the experiment.
- mean(): Mean value
- std(): Standard deviation
- mad(): Median absolute deviation
- max(): Largest value in array
- min(): Smallest value in array
- sma(): Signal magnitude area
- energy(): Energy measure. Sum of the squares divided by the number of values.
- iqr(): Interquartile range
- entropy(): Signal entropy
- arCoeff(): Autorregresion coefficients with Burg order equal to 4
- correlation(): correlation coefficient between two signals
- maxInds(): index of the frequency component with largest magnitude
- meanFreq(): Weighted average of the frequency components to obtain a mean frequency
- skewness(): skewness of the frequency domain signal
- kurtosis(): kurtosis of the frequency domain signal
- bandsEnergy(): Energy of a frequency interval within the 64 bins of the FFT of each window.
- angle(): Angle between to vectors.
##Transformation
- Dwonload the file if it does not exist
- Unzip the file, if the file exists then overwrite
- Read the activity lables and features
- Read the train datasets and name the columns
- Read the test datasets and name the columns
- Merging the dataset
- Selecting only the needed variables
- Final dataset with only the needed variables
- Create a dataset from final dataset without the activity type
- Summarizing the finalDataNoActivityType table to include just the mean of each variable for each activity and each subject
- Merging the tidyData with activityType to include descriptive acitvity names
- Export the tidyData set