matthew-alexander/data_cleaning

hopkins course on data cleaning

Hopkins Data Cleaning Course Project

hopkins course on data cleaning

This project was to download and aorganize the Human Activity Recognition Using Spartphones data from the UCI Machine Learning repository.

The data cleaning process entailed:

1. Merging the training and the test sets to create one data set.
2. Extracting only the measurements on the mean and standard deviation for each measurement.
3. Using descriptive activity names to name the activities in the data set
4. Labeling the data set with descriptive variable names.
5. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

Final data sets

The final data sets are:

• data_tidy.csv, which is the data produced from step 4
• data_tidy_means.txt, which is the second, independent data set that aggregates the means by subject and activities