title	author	date	output
README.md	J.S.	June 20, 2015	html_document

#Human Activity Recognition Using Smartphones - Tidy Data

The objective of this project is to gather data from a public database of the University of California and perform some cleaning and tidying.

The data collected contains information about different sensor readings of a Galaxy Samsung. The experiment used 30 test subjects performing 6 different types of activities: laying, sitting, standing, walking, walking downstairs, walking upstairs.

The original data can be obtained here.

To perform the analysis:

source("run_analysis.r")
run_analysis()

-Make sure you have an internet connection.

The following steps will be performed by the script:

1. Check if dplyr package is installed. If not it will be downloaded
2. Download the original data if it has not been downloaded previously. A folder named "UCI HAR Dataset" will be created
3. Load original variable names from the file features.txt
4. From the original variable names, extract the list of variable names and indices that contain the strings "mean()" or "std()".
5. Remove strange characters from variable names ("(",")","-",etc)
6. Load list of activities from activities.txt and convert them to lowercase
7. Load training and test data sets from /train and /test folders

• X_train.txt
• y_train.txt
• subject_train.txt
• X_test.txt
• y_test.txt
• subject_test.txt

8. Merge the data (concatenating columns from X, y, and subject, and merging rows from train and test data sets)
9. Group the data set by subject and activity
10. Calculate the mean for each additional variable and append the text "average_" to the beginning of each name
11. Save the new data set into a file called "tidy.txt"

Information of all the new variables in the data set can be found in the file CodeBook.md