pepexavier / getting_data

My personal work to the Coursera- John Hopkins University course called "Getting and Cleaning Data"

The script run_analysis.R

0. Previus task

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Before start the scrip we dowload the zipfile from cloudfront.net and extrat it in the working directory, in a subdirectory called "UCI HAR Dataset"

1. Merges the training and the test sets to create one data set.

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We read the data from the "train" and "test" folders and we merge the similiar frames: Data come from x_t????.txt, Labels come from y_t????.txt, and sujets come from subject_t????.txt. 2. Extracts only the measurements on the mean and standard deviation for each measurement.

From the file features.txt we take the names of the frame Data and select the mean and standard deviation for each measurement, then we Extract those measurements from Data frame and the associated names, in the new Data frame. 3. Uses descriptive activity names to name the activities in the data sett

We take the names of each activity from file activity_labels.txt and them we substitute the numeric data in the Labels vector with the descriptive names adding "activity" as the name. 4. Appropriately labels the data set with descriptive variable names.

We add the name "subject" to the subject vector and after we join subject and Labels vectors with Data frame. 5. Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

With the use of for at two levels (one with the subjects and the second with activities) we calculate the average of each variable and the we build an data frame called TidyData. When this frame is complete we write a file called tidy_data_set.txt.

You can see The tidy_data_set.txt Code book.