This repository produces a tidy dataset using accelerometer and gyroscope data derived from the Samsung Galaxy S smartphone. The data were obtained from the UCI Machine Learning Repository and were originally collected by Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz.
Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.
This repository contains one R script (run_analysis.R), which executes the following steps:
- Merges the training and the test sets to create one data set.
- Extracts only the measurements on the mean and standard deviation for each measurement.
- Uses descriptive activity names to name the activities in the data set
- Appropriately labels the data set with descriptive variable names.
- From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.
- Writes the tidy data set as a txt file created with write.table() using row.name=FALSE.
run_analysis.R requires the data.table and plyr packages in the R statistical environment.
The repository also contains:
- The complete raw data set, stored in the [UCI HAR Dataset](/UCI HAR Dataset/) folder.
- The tidy data set produced by the script, tidyds.txt.
For details on the variables in the data, please see CodeBook.md.