This repository is a submission by Suyash Mishra for the Getting and Cleaning Data course project. It contains the necessary instructions and code for performing analysis on the Human Activity Recognition dataset.
The analysis is conducted on the "Human Activity Recognition Using Smartphones" dataset.
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CodeBook.md: This code book provides a comprehensive description of the variables, data, and any data transformations or cleaning procedures that were applied. -
run_analysis.R: This script carries out the data preparation and follows the five steps mandated in the course project's definition:- Merging the training and test sets to create a single dataset.
- Extracting only the mean and standard deviation measurements for each feature.
- Assigning descriptive activity names to the activities in the dataset.
- Appropriately labeling the variables with descriptive names.
- Creating a second, independent tidy dataset with the average of each variable for each activity and subject.
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FinalData.txt: This exported file represents the final dataset obtained after executing all the aforementioned steps. It contains the summarized and tidy data, ready for further analysis.
Please refer to the CodeBook.md for detailed information about the dataset, variables, and the transformations applied.