Skip to content

README.md

Latest commit

 

History

History
38 lines (31 loc) · 1.8 KB

README.md

File metadata and controls

38 lines (31 loc) · 1.8 KB

Getting-and-Cleaning-Data-Course-Project

Human Activity Recognition Using Smartphones Dataset

overview

This script is mean to process data collected from the accelerometers from the Samsung Galaxy S smartphone according to the requirement of Course Project.

struncture of the original data

If you want to run the script, make sure that the data is in your R workspace. The structure of directory should be like this:

\UCI HAR Dataset\activity_labels.txt"
\UCI HAR Dataset\features.txt"
\UCI HAR Dataset\test\subject_test.txt"
\UCI HAR Dataset\test\X_test.txt"
\UCI HAR Dataset\test\y_test.txt"
\UCI HAR Dataset\train\subject_train.txt"
\UCI HAR Dataset\train\X_train.txt"
\UCI HAR Dataset\train\y_train.txt"

where to get the original data

you can get the data from: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
here is the codebook of this data: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

what the "run_analysis.R" do

  • 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 variable names.
  • 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.

understand the output

the output has been saved in file "result.txt". A full description is available in the CodeBook

The dataset includes the following files

README.md
codebook.txt:show information about the result.txt
result.txt:a independent tidy data set with the average of each variable for each activity and each subject.