Getting and Cleaning Data Project

This repo contains a single R-file run_analysis.R, which contains 4 functions that together make up the project.
The aim of this project is to take the UCI HAR Dataset and tidy the dataset. The project has 5 objectives:

1. Merge all data into a single dataset and this dataset contains 1 variable per column and 1 observation per row
2. Extract only the means and standard deviations of measurements
3. Give activities descriptive names
4. Give variables (columns) descriptive names

In addition:
5. Create a summary from this tidy dataset, with the means per subject per activity

Quick Start

load run_analysis.R and call the runProject()-function This uses the default settings with the datafiles expected in the working directory. Optionally a directory for the dataset and a filename for the summary can be specified.

The Dataset

Information on the background, raw data files and processing can be found in codebook.md

Functions

Here the functions in run_analysis.R are described that make up the project

Function 1: getTidyData

This is the main workhorse for this project. The function accepts a directory where the dataset is stored creates a tidy dataset. In overview (with numbers matching the steps marked in the R code):

1. • 2. A check is performed to verify all above listed files are present and if so, they are all read into memory.
2. The activity codes and subjects - which are stored in separate files, are merged into their respective datasets.
3. • 5. The columns are given descriptive names based on features.txt.
        6.1 The test and train dataset are merged. This completes objective 1 and 4.
        6.2 From this dataset, only the columns that have 'mean' or 'std' in their name are selected, finising objective 2.
        6.3 - 6.4 The activity codes are translated into descriptive activity names.
4. This finalizes objective 3 and results in a tidy dataset which is returned.

Function 2: createSummary

This function takes the dataset from getTidyData as input, together with a filename and creates a summary. This summary is the average per subject per activity for all the columns, meeting objective 5. This summary is then written to a file in the working directory.

Function 3: readSummary

This function is not necessary for the project, but is a little helper-function to read to generated summary back into R.

Function 4: runProject

This function is the only one the end-user needs to call, which in turn calls getTidyData and createSummary to fulfill the entire project with a single call.