title | author | date | output | ||||
---|---|---|---|---|---|---|---|
README |
Jason M. Netherland |
2015-06-13 |
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The goal of the project is to create a tidy dataset from a collection of sensor data that contains on the means and standard deviation observations.
##Study design and data processing
###Collection of the raw data The data was downloaded from: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
A full description is available at the site where the data was obtained: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
###Notes on the original (raw) data The original data is split into a test and train partition.
##Creating the tidy datafile
###Guide to create the tidy data file
- download the data
- unzip the data
- import data into R
- merge labels with y record
- create column names
- determine which rows are means or standard deviation rows
- combine x, y, and subject data
- add Partition Group column for test or train data
- combine test and train data into a single data frame
- melt data to create a thin tidy dataset
- use ddply to group and calculate means