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

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

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• Host: GitHub
• URL: https://github.com/gsahonero/getting-and-cleaning-data---course-project
• Owner: gsahonero
• Created: 2015-01-25T23:21:28.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2015-02-02T01:17:17.000Z (almost 10 years ago)
• Last Synced: 2023-02-27T02:18:10.885Z (almost 2 years ago)
• Language: R
• Size: 340 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Getting and Cleaning Data - Course Project

## About the Script

The `run_analysis.R` performs the following procedures:

1. Verifies existence of the Data folder. If such folder does not exist, R will download it. The URL of the data is the following link: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip 

2. The data files (X,Y files of the train and test data sets) are loaded as CSV files. 

3. Data frames are merged by using `rbind`and `cbind` combining **Subject, Activity and Measurements** observations.

4. Columns' names are given by extracting them from **features.txt** file, which is included in the data set.

5. Columns that contain *mean* or *std* are found by using `grepl`.

6. IDs and names of activities are read from the **activity_labels.txt** file. The factor function is used to convert the activity IDs into descriptive names.

7. Using `ddply` a second data set is created. This data set includes the average of each variable given each activity and subject. 

8. Finally, `write.csv` is used to create the tidy data set in the same folder as `run_analysis.R` script.