llvdl / datascientist-getting-and-cleaning-data Goto Github PK

The goals for the clean up script are:

• 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 activity names.
• Creates a second, independent tidy data set with the average of each variable for each activity and each subject.

The steps to clean up the UCI HAR dataset are:

1. clone this repository to your local system
2. you should see the run_analysis.R script in the folder you extracted the repository to
3. extract the UCI HAR data set to the folder where you cloned this repository
   • The data set can be downloaded from https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip and must be unzipped
   • Note: After extracting the data set, you should have a subdirectory called UCI HAR Dataset in the folder the repository is cloned in
4. open R or RStudio
5. make sure the current working directory is the folder you extracted the repository to
   • use getwd() to check the current working directory and setwd() to set the current working directory
6. start the script with source("run_analysis.R")

After the script has ran, you should see a newly created set with the filename tidy_data_set.txt in the folder. Please note that the script will overwrite the file if it already exists before running.

You can load the clean data set using the read.table function, e.g.

data <- read.table("tidy_data_set.txt")

View(data)