Week 4 project - Getting and Cleaning Data in R
Author – Benedict Neo
This is the final project from the Coursera course Getting and Cleaning Data by John Hopkins. The purpose of this project is to demonstrate my ability to collect, work with, and clean a data set.
Repository contents
This repository includes 4 files, the R script named run_analysis.R, this read_me file you’re reading now, the codebook file which explains more about the data set and the methodology, and the final tidy data set.
| Goal | Item | Link to Item |
|---|---|---|
| R Script | run_analysis.R | Link |
| Read_me file | README.md | Link |
| CodeBook file | CodeBook.md | Link |
| Tidy Data file | Clean Data Set | Link |
Review criteria of project
- The submitted data set is tidy.
- The Github repo contains the required scripts.
- GitHub contains a code book that modifies and updates the available codebooks with the data to indicate all the variables and summaries calculated, along with units, and any other relevant information.
- The README that explains the analysis files is clear and understandable.
- The work submitted for this project is the work of the student who submitted it. Getting and Cleaning Data Course Project
Project theme
Getting and Cleaning Wearables Computing Data
One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone.
The Data
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Data Zip File: UCI Machine Learning Repo
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Data Description: link