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Assignment Name: Programming Assignment 3
Course: Getting and Cleaning Data
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Student Name: Rebecca Love
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This is the programming assignment for Week 4 of the
Getting and Cleaning Data course required for the
Data Science Specialty on Coursera. The instructions for the
assignment are in the course online.
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This repository contains the following files:
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- 'README.txt': (this document)
- 'run_analysis.R': An R script
- 'CodeBook.md': Modifies and updates the available codebooks with the data to
indicate all the variables and summaries calculated, along with
units, and any other relevant information.
- 'UCI HAR Dataset': Contains the data that will be processed by run_analysis.R
To execute the script:
1. Set the working directory of R to the directory that contains the UCI HAR Dataset folder.
The result of the script is an text file called tidy_data.txt saved in the working directory.
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The steps taken to produce the final output are as follows:
## read 2 data files
## 1. UCI HAR Dataset\test\X_test
## 2. UCI HAR Dataset\train\X_train
## The features file contains the column names for the 561 variables
## Read the features file and put into a vector
## rename the columns in the test and train data sets
## create a new data frame for test and train data
## that conatins only the
## mean and std columns in the data set
## create a vector with the column indexes
## (remove)subcols <- c(grep("mean", names(testdat2)), grep("std", names(testdat2)))
## read 2 label files that contain the activity codes
## 1. UCI HAR Dataset\test\y_test
## 2. UCI HAR Dataset\train\y_train
## Add a column to the test and train data set for the activity codes
## named 'activitycode' to each data table using the activity codes data
## Add a column to the test and train activity sets for the activity label
## Add a column that conatins the subject id
## Extract the subject data
## merge the test and train data sets
## Group on subjectcode and activitylabel and average the data on the groups
## clean up column names
## Update subject and activity columns
## remove extraneous characters from measures column names
## output the final results to a text file in the working directory
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