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Getting and Cleaning Data - Project

run_analysis.R

Forms and stores a tidy summary of the given data. This script performs the following steps:

  • Forms a data frame containing features and results for each subject in the training set.
  • Forms a data frame containing features and results for each subject in the test set
  • Combines these two into a single data frame.
  • Sets column names and activity labels.
  • Extracts from it a data frame containing mean and standard deviation features for each subject.
  • Cleans up column names to be more readable.
  • Forms a tidy summary from the new data frame containing averages of mean and standard deviation features for each subject during each activity.

###Results

  • data - Contains the combined data of the training and test sets.
  • meansDevs - Contains only mean and standard deviation columns for each subject.
  • dataSummary - Contains averages of mean and standard deviation values for each combination of activity and subject. It is written to data_summary.txt in the given data folder.

###Assumptions

  • The provided data must be unzipped into the working directory before running this script. That is, UCI HAR Dataset must be a subdirectory of the current directory.
  • Library reshape2 is required.
  • When extracting mean and standard deviation measurements, only columns with names containing -mean() and -std() are used. Those containing -meanFreq() are ignored.
  • The tidy data set is created from means/deviations data set and not from the overall data set.
  • The final result contains average values for each subject while performing each activity.

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