This is a repository for the Getting and Cleaning Data Coursera course through Johns Hopkins University.
- Merges the training and the test sets to create one data set.
- Extracts only the measurements on the mean and standard deviation for each measurement.
- Uses descriptive activity names to name the activities in the data set.
- Appropriately labels the data set with descriptive activity names.
- Creates a second, independent tidy data set with the average of each variable for each activity and each subject.
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Dependency: package dplyr is required and can be installed as follow in RStudio:
install.packages("dplyr") -
Download and unzip the data file into your local directory or folder, for example: "/Users/YourName/GettingAndCleaningData/Project/UCI HAR Dataset".
This can be done by either using utilities outside RStudio or inside RStudio as follows:
setwd("/Users/YourName/GettingAndCleaningData/Project") fileUrl = "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip" download.file(fileUrl, destfile="./UCI HAR Dataset.zip", method = "curl") unzip("./UCI HAR Dataset.zip") -
Then put "run_analysis.R" script in the repository into "/Users/YourName/GettingAndCleaningData/Project/UCI HAR Dataset".
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In RStudio, run the script:
source("run_analysis.R") -
The result file called "tidy_data_averages.txt" will be generated when the script is finished.
- The details of how the "run_analysis.R" does can be found in the script itself and CodeBook.md file.