The assignment is to form tidy data that is ready to analyse.
The data has been taken from accelerometers in Samsung Galaxy S smartphones and a full description is available at the site where the data was obtained:
http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
The data can be downloaded from the link below:
https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
The assignment work is captured in one R script called run_analysis.R that does the following:
- 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.
This document, README_run_analysis.md, describes run_analysis.R.
A separate file, run_analysis_code_book.md contains descriptions of the:
- variables
- data
- transformations or work that performed to clean up the data
Executing run_analysis.R (when loaded (source("run_analysis.R"))) will form a dity data set of the mean data values.
Note: the working directory must be first set to the parent folder containing the "UCI HAR Dataset".
- Read in all relevant data files for train and test.
- Combine datasets
- Select only the measurements on the mean and standard deviation measurements
- Produce the mean of means table
- Write data to .csv file in the parent directory