Skip to content

djsnowsill/GettingAndCleaningDataAssignment

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Getting And Cleaning Data Assignment

Repository for Coursera: https://class.coursera.org/getdata-015

run_analysis.R should do the following:

  1. Merges the training and the test sets to create one data set.
  1. Extracts only the measurements on the mean and standard deviation for each measurement.
  1. Uses descriptive activity names to name the activities in the data set
  1. Appropriately labels the data set with descriptive variable names.
  1. From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.
Please upload the tidy data set created in step 5 of the instructions. 
Please upload your data set as a txt file created with write.table() using row.names=FALSE 
(do not cut and paste a dataset directly into the text box, as this may cause errors 
saving your submission).

Repository structure

-README.md, this file.

-codebook.md, contains the description of variables produced by run_analysis.R

-run_analysis.R, is the R script that produces the tidyData.txt file

-DatasetHumanActivityRecognitionUsingSmartphones.txt, is the file generated by run_analysis.R, which contains the tidy data set generate from supplied data set

Running the run_analysis.R script

  1. create a directory on your local machine where you would like to clone the repository
  1. change directory into what you created in #1
  1. clone this repository : git clone https://github.com/djsnowsill/GettingAndCleaningDataAssignment
  1. change directory into the GettingAndCleaningDataAssignment directory
  1. start R from the command line
  1. source("run_analysis.R")

How the run_analysis.R script works

Review the run_analysis.R script in the root of the cloned repository.

The script contains extensive comments which explains what the script is doing

Please note that this script relies on dplyr which is installed by the script if it is not available

This script downloads the necessary raw data files so they are not required to be downloaded by the user

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages