https://github.com/stevewyl/getting-and-cleaning-data-project

Task for Getting andCleaning Data cousrse for Cousera
https://github.com/stevewyl/getting-and-cleaning-data-project

Last synced: about 1 month ago
JSON representation

Task for Getting andCleaning Data cousrse for Cousera

• Host: GitHub
• URL: https://github.com/stevewyl/getting-and-cleaning-data-project
• Owner: stevewyl
• Created: 2016-02-01T08:09:38.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2016-02-01T08:54:25.000Z (almost 9 years ago)
• Last Synced: 2024-11-19T04:06:27.298Z (about 1 month ago)
• Language: R
• Homepage:
• Size: 59.8 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd

Awesome Lists containing this project

README

        
---

title: "README"

author: "Steve.Wang"

date: "2016年2月1日"

output: html_document

---

# Getting and Cleaning Data Project

Getting and Cleaning Data Course Project February 2016

This is a repository for any and all code written for the Getting and Cleaning Data Coursera course through Johns Hopkins University.

# Course Project

(find all project-related materials in the UCI HAR Dataset directory, however, copies of the important files have been put into this main directory to fulfill the submission requirement)

* Unzip the source (https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip) into a folder on your local drive, say C:\\Users\\Desktop\\Documents\\Coursera\\Getting and Cleaning Data\\Getting and Cleaning Data Course Project\\Getting and Cleaning Data Course Project\\UCI HAR Dataset

* Put run_analysis.R into C:\\Users\Desktop\\Documents\\Coursera\\Getting and Cleaning Data\\Getting and Cleaning Data Course Project\\UCI HAR Dataset

* In RStudio: setwd("C:\\Users\\Desktop\\Documents\\Coursera\\Getting and Cleaning Data\\Getting and Cleaning Data Course Project\\UCI HAR Dataset"), followed by: source("run_analysis.R")

* Use data <- read.table("data_set_with_the_averages.txt") to read the data. It is 180x68 because there are 30 subjects and 6 activities, thus "for each activity and each subject" means 30 * 6 = 180 rows. Note that the provided R script has no assumptions on numbers of records, only on locations of files.