tidy-data

Summary

Course project for Coursera Getting and Cleaning Data online course

The run_analysis.R script processes data set available for download from (https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip)

as it is required by course project requirements:

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.

Script

dependencies

The script will require data.table and reshape2 packages

executing

Unzip downloaded data archive into script's directory, there should be new sub-folder named UCI HAR Dataset where the script will read the data from. Main script to run is run_analysis.R. It expects a parameter with name of the folder where tthe raw data had been unpacked to. If input parameter is omitted, the script will try to look for UCI HAR Dataset folder in its source directory.

Script could be run by issuing

source('./run_analysis.R')
data <- tidy_set()

or to explicitly specify data folder

data <- tidy_set('/tmp/data/UCI HAR Dataset')

output

Returned object is of data.table class, it contains 11880 rows and 4 columns described in details in CodeBook.md Resulting data could be saved into tidy_data.txt file by the following command

write.table(data, file="tidy_data.txt", row.names=FALSE)