Getting-and-cleaning-data-project

Getting and Cleaning Data Course Project

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This repository contains the R code and documentation files for the Data Science's track course "Getting and Cleaning data", available in coursera. The relevant files are as follows:

1. README.md, this file, which provides an overview of the data set and how it was created.
2. tidy_data.txt, which contains the data set.
3. CodeBook.md, the code book, which describes the contents of the data set (data, variables and transformations used to generate the data).
4. run_analysis.R, the R script that was used to create the data set (see the Creating the data set section below)

Creating the data set

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The R script run_analysis.R aims to create the data set and tidy.txt file contains the outcome after runnung this script. The steps in the document are as follows:

Step 0A- Download and unzip source data if it doesn't exist.

Step 0B- Read data.

Step 1- Merge the training and the test sets to create one data set.

Step 2- Extract only the measurements on the mean and standard deviation for each measurement.

Step 3- Use descriptive activity names to name the activities in the data set.

Step 4- Appropriately label the data set with descriptive variable names.

Step 5- Create a second, independent tidy set with the average of each variable for each activity and each subject.

Step6- Write the data set to the tidy_data.txt file.

So, the tidy_data.txt is created by running the run_analysis.R script using R version 3.4.1 on Windows 8.1 64-bit edition.