Getting and Cleaning Data - Project

This repository contains the work done for Coursera's Getting and Cleaning Data project.

The run_analysis.R script contains the R code for creating a tidy data set from the raw data downloaded from https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip. The data contains measurements values from subjects performing various activities namely walking, walking upstairs, walking downstairs, sitting, standing and laying, while wearning the computing devices.

Pre-requisite

The raw data must be available for the script to create the tidy data set.

Script Details

• The train sets are read and the data contained in the subject_train.txt, X_train.txt & y_train.txt are read and merged into a single data frame. The colums are labeled appropriately.
• The test sets are read and the data contained in the subject_test.txt, X_test.txt & y_test.txt are read and merged into a single data frame. The colums are labeled appropriately.
• The train and the test data sets are merged together to create a single data set named tidy.
• Next the activity lables are applied to the dataset named labled_tidy
• A seperate data set containing the standard deviation and mean values is created and named as std_mean_tidy
• Another dataset is created with the average values of the variables on a per-subject basis and named mean_df
• For all the above data sets, the top three rows are displayed after the data set is created.
• Finally, the data sets are dumped into csv files named tidy_data.csv, std_mean.csv and mean_subject.csv

Steps to execute

1. Download the data set from https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
2. Extract the downloaded data set in the directory containing the run_analysis.R script.
3. After extraction, you should have a directory named UCI HAR Dataset in the same directory as the script.
4. Execute the script either from the R console or R-studio.