##Getting and Cleaning Data: Course Final Project ###Human activity recognition data collected with a waist-mounted smartphone

To reproduce the accompanying data sets (found in the repository as Tidy.csv and means-stds.csv), follow these steps:

• Download and unzip the raw source data from here
  • A description of the original data collection procedure can be found here
• Download the run_analysis.R file and place it in the same folder as the unzipped data.
  • The file should be at the same level as features.txt, features_info.txt etc. from the raw data.
  • The test/ and train/ subfolders should also exist alongside these files.
• Change the working directory to wherever you have placed the file, and run source("run_analysis.R") from within R. This should locally create the files Tidy.csv and means-stds.csv. The contents of these two files are described in the codebook.
  • The code also creates two data frames in memory, named Tidy and X containing the corresponding data.
• The code does not require loading any additional libraries.
• The code begins by cleaning the environment through rm(list=ls()to prevent potential conflicts. Make sure you store any unsaved objects prior to running the code!