This repo contains the R scripts that can be used to analysis the UCI HAR Dataset and convert it into a tidy data set.
This was done as the course project for the "Getting and Cleaning Data" course in Coursera which is part of the "Data Science" specialization track.
Create a R script 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.
The R code that is used for analysis is available in the run_analysis.R file.
Source the file in R using the following command and it will automatically download the dataset, perform the transformation, tidy the data and save it in the file tidy_data.txt.
source("run_analysis.R")The tidy data set can be loaded back into R using the following command
tidy_data <- read.table("tidy_data.txt")The codebook available in this repo describes the variables, the data, the transformations that are done and the clean up that was performed on the data.