TidyDataProject Introduction

The purpose of this project is to effectively collect, work with, and clean a dataset.

Data from the accelerometers from the Samsung Galaxy S smartphone are used. A complete description of accelerometer data is available at: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones;

The associated R script, run_analysis.R, does the following:

setwd(choose.dir()) SELECTS A DIRECTORY

Step 1 Merge training and test data sets combine train and test data combine train and test labels combine train and test subjects
Step 2 Extract only the data on mean and standard deviation l looks for mean() or std() in column V2 grabs the names where a match was found subsets the data with only the needed columns remove "()" capitalize M capitalize S
Step3. Uses descriptive activity names to name the activities in the data set update values with correct activity names correct column name
Step 4 Appropriately label the data set with descriptive variable names correct column name bind all the data in a single data set write out the 1st dataset
Step5. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

A code book that describes the data fields in tidy_dataset.txt can be be found in CodeBook.md.

Everymans-ai/TidyDataProject