This project is the part of "Getting and cleaning data" Coursera course.

We download the wearable computing data from here about movement patterns using accelerometers from the Samsung Galaxy S smartphone.

We:

• Merge the training and the test sets to create one data set.
• Extract only the measurements on the mean and standard deviation for each measurement.
• Use descriptive activity names to name the activities in the data set
• Appropriately label the data set with descriptive activity names.
• Create a second, independent tidy data set with the average of each variable for each activity and each subject.

The resulting dataset is saved into the file "tidy.txt".

The included materials in this project are:

• README.md i.e. this file
• R Scripts - described below
• CodeBook.md - a code book file
• tidy.txt - a tidy dataset
• features_info.txt - meanings of variables in the original dataset

Two scripts are used and both of them should be in the working directory.

Fetches the data from internet and extracts it in the current directory

Does the cleaning and tidying up the dataset. It uses the dataFetching.R to get the data ready for analysis so at least dataFetching.R has to be in the working directory.