justinjwlee / cleaning-data-assignment

Data sci specialisation. Getting & cleaning data

Getting and Cleaning Data Peer Assessment

What is included in this repo?

• run_analysis.R stand-alone script with no other dependencies
• README.md includes instructions on how to use script & CodeBook

How to use the script?

1. Download the UCI Dataset here
2. Download this script
3. Save it in the directory of your unzipped UCI HAR Dataset folder
4. Open R Studio
5. Type the following into the prompt:

> setwd("./<your UCI HAR Dataset dir>")
> library(reshape2)
> source("./<your UCI HAR Dataset dir>/run_analysis.R")
> run_analysis()

The tidy dataset named 'tidyDataset.txt' will be saved in the UCI Dataset folder

Code Book

Assumptions

1. Only variables with mean() & std() in their names are extracted. Other variables with names like meanFreq() are ignored
2. The independent tidy data set is created by grouping individual then activity and taking average of those readings
3. Resulting tidy data set dimension: 180 (30 subjects * 6 activities) x 69 (66 variables + subject + activity_id + activity_label)

Pseudocode

Operating System: OSX Mavericks

• Step 1: merge test data and training data into 1 set
• Step 2: extract only mean() & std() for each measurement

Get the indices of mean() & std() in features.txt file Regex to select all features containing mean() & std()
Matches returns a vector of indices of features containing mean() & std() MatchesNames returns a vector of features names containing mean() & std() Subsets the data frame on column indices

• Step 3: merge test and training activity labels into 1 set
• Step 4: joins data frame of activity names with data frame of sensor data
• Step 5: group by subject and then by each activity by taking avg of each variable

Variables

• subject
• activity_id
• activity_label
• tBodyAcc-mean()-X
• tBodyAcc-mean()-Y
• tBodyAcc-mean()-Z
• tBodyAcc-std()-X
• tBodyAcc-std()-Y
• tBodyAcc-std()-Z
• tGravityAcc-mean()-X
• tGravityAcc-mean()-Y
• tGravityAcc-mean()-Z
• tGravityAcc-std()-X
• tGravityAcc-std()-Y
• tGravityAcc-std()-Z
• tBodyAccJerk-mean()-X
• tBodyAccJerk-mean()-Y
• tBodyAccJerk-mean()-Z
• tBodyAccJerk-std()-X
• tBodyAccJerk-std()-Y
• tBodyAccJerk-std()-Z
• tBodyGyro-mean()-X
• tBodyGyro-mean()-Y
• tBodyGyro-mean()-Z
• tBodyGyro-std()-X
• tBodyGyro-std()-Y
• tBodyGyro-std()-Z
• tBodyGyroJerk-mean()-X
• tBodyGyroJerk-mean()-Y
• tBodyGyroJerk-mean()-Z
• tBodyGyroJerk-std()-X
• tBodyGyroJerk-std()-Y
• tBodyGyroJerk-std()-Z
• tBodyAccMag-mean()
• tBodyAccMag-std()
• tGravityAccMag-mean()
• tGravityAccMag-std()
• tBodyAccJerkMag-mean()
• tBodyAccJerkMag-std()
• tBodyGyroMag-mean()
• tBodyGyroMag-std()
• tBodyGyroJerkMag-mean()
• tBodyGyroJerkMag-std()
• fBodyAcc-mean()-X
• fBodyAcc-mean()-Y
• fBodyAcc-mean()-Z
• fBodyAcc-std()-X
• fBodyAcc-std()-Y
• fBodyAcc-std()-Z
• fBodyAccJerk-mean()-X
• fBodyAccJerk-mean()-Y
• fBodyAccJerk-mean()-Z
• fBodyAccJerk-std()-X
• fBodyAccJerk-std()-Y
• fBodyAccJerk-std()-Z
• fBodyGyro-mean()-X
• fBodyGyro-mean()-Y
• fBodyGyro-mean()-Z
• fBodyGyro-std()-X
• fBodyGyro-std()-Y
• fBodyGyro-std()-Z
• fBodyAccMag-mean()
• fBodyAccMag-std()
• fBodyBodyAccJerkMag-mean()
• fBodyBodyAccJerkMag-std()
• fBodyBodyGyroMag-mean()
• fBodyBodyGyroMag-std()
• fBodyBodyGyroJerkMag-mean()
• fBodyBodyGyroJerkMag-std()