The datasets were downloaded from UCI Machine Learning Repository: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
You should create one R script called run_analysis.R that does the following.
- Merges the training and the test sets to create one data set.
- Extracts only the measurements on the mean and standard deviation for each measurement.
- Uses descriptive activity names to name the activities in the data set
- Appropriately labels the data set with descriptive variable names.
- From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.
This project includes the following files and folders:
- README.md
- run_analysis.R - script used for data cleaning
- CodeBook.md - a code book that describes the variables, the data, and any transformations or work that you performed to clean up the data.
- data - downloaded copy of data
- tidydata1.csv
- tidydata2.csv
- a tidy data set as described above (see Instructions)
- a link to a Github repository with your script for performing the analysis
- a code book that describes the variables, the data, and any transformations or work that you performed to clean up the data called CodeBook.md.
- You should also include a README.md in the repo with your scripts. This repo explains how all of the scripts work and how they are connected.