Getting and Cleaning Data Course Project

It uses Human Activity Recognition Using Smartphones Dataset Version 1.0

• the data for the project [data]https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

• A full description is available at the site where the data was obtained:[description]http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

• First download the data set from the link and then set a working directory to UCI HAR Dataset

• needs dplyr , data.table , and tidyverse packages

• uses read.table() to import the data sets.

To Uses descriptive activity names to name the activities in the data set

• uses names() to describe the activity names of variables feature, activities

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

  • uses rbind() to merge Y_test and X_test, and store in **merged_activity **
  • it uses merge() and cbind() to create total_Merged_Data.

  To Extracts only the measurements on the mean and standard deviation for each measurement

  • uses grep("mean\(\)|std\(\)", features$feature_Label) to extract variables with mean and std on the column names
  • gsub("\(|\)", "", names(Merged_with_Mean_Std)) removes () from variable names

  To create independent tidy data set from the merged data set with mean and std variables

  • uses tbl_df function from dplyr package

  • uses group_by function to group the data set by activity_Label, subject_Id

  • Then, for each separted data set it summarizes all variables using mean

  • Finally, exports and save a data set with a name tidy_mean_std.txt