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Getting and Cleaning Data - Course Project

The R script run_analysis.R was created to gather data, clean data, and created a tidy summary dataset of the UCI HAR Dataset. run_analysis.R contians the following functions:

  • ###runAnalysis This function is a wrapper to run all necessary functions start to finish and write the tidy summary dataset to uci-har-means-tidy.txt. To view the output run the following code:

    data <- read.table('uci-har-means-tidy.txt', header = TRUE)

    View(data)

  • ###getLibraries This script requires the dplyr library. This function will check for this library and download and/or load if necessary.

  • ###getData This function checks the working directory for the UCI HAR Dataset. If the folder does not exist the data is downloaded, unziped, and the zipped file is removed. The unziped folder location is reported to the user.

  • ###createCombinedDataset This function does the following:

  1. Reads all necessary tables into R.
  2. Makes a unique feature list to avoid duplicate label issues with dplyr select.
  3. Relabels the columns in both test and train data to the features.
  4. Adds the y for each test and train dataset and labels is activity.
  5. Adds the subject to each test and train dataset.
  6. Combines the test and train data into one dataset.
  7. Changes activity to a factor and resets the levels to the tidy activity labels.
  8. Returns the combined labeled dataset.
  • ###createSummaryDataset This functions takes the output of the createCombinedDataset function and does the following:
  1. Selects a subset of columns that contain: subject, activity, and any field containing the word mean or std in the label.
  2. Groups the data by subject and activity then summarizes all measurement fields by the mean.
  3. Creates tidy column labels by the following: a. removing hypens. b. removing parenthesis. c. applying camel case. d. changes BodyBody to Body.
  4. returns the tidy summary dataset.