This repo is used to submit a course project for "getting and cleaning data" course (part of the Johns Hopkins data science track). The following files can be found in the repo:
- run_analysis.R
- tidy_data.txt
The idea is that the dataset provided (link can be found below), is not in the format needed for analysis. Thus, a script (run_analysis.R) is provided to read the dataset and turn it into a tidy dataset that can be used for analysis. The first file (run_analysis.R) is the script file; whereas, the second file (tidy_data.txt) is an example of the dataset that you will get if you run the script.
The following analysis is done when you run the provided script:
- In step1, the training and testing dataset are read and loaded to R.
- In step2, the training and testing dataset are merged togther into one dataset along with the subject and activity data.
- In step3, the column names are changed into a more friendly names (from V1,V2,etc to activity, subject, BodyAcc-mean()-X). Also, the activity names are changed to something more friendly (from 1,2,3 to walking, sitting, etc).
- in step4, we extract only the measurements on the mean and standard deviation for each measurement.
- in step5, we create an independent tidy dataset with the average of each variable for each activity and each subject, and returning back the result.
The dataset used with this project can be found at: UCI Machine Learning Repository.
You will need R studio installed on your machine with the basic packages and the dplyr package as well.