uci_dataset_analysis

This repository contains the run_analyis.R script which takes raw data from "./UCI HAR Dataset" directory, perform 5 cleanup tasks to the raw data and return a tidy dataframe as a result. Below are the detailed descriptions of the expected input, cleanup tasks and the output:

##Expected input: "./UCI HAR Dataset" should be present in the working directory

1. activity_labels.txt - Text label for each activity id
2. features.txt - Text label for each sensor output

####./UCI HAR Dataset/test - test-group data-set

1. subject_test.txt - test-group subject-id linked to X_test.txt data
2. y_test.txt - test-group activity-id linked to X_test.txt data
3. X_test.txt - sensors data for test-group

####./UCI HAR Dataset/train - train-group data-set

1. subject_train.txt - train-group subject-id linked to X_train.txt data
2. y_train.txt - train-group activity-id linked to X_train.txt data
3. X_train.txt - sensors data for train-group

Cleanup tasks :

run_analysis() perform the following cleanup tasks to the raw dataset

1. Merges the training and the test sets to create one data set.
2. Extracts only the measurements on the mean and standard deviation for each measurement.
3. Uses descriptive activity names to name the activities in the data set
4. Appropriately labels the data set with descriptive variable names.
5. 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.

Output results :

1. return a tidy dataframe from step 5
2. it also writes this tidy dataframe to a file named "har_tidy.data.txt"

The result tidy dataframe has:

• 180 rows (observations) for each of the SUBJECT.ID (30) x ACTIVITY.ID (6) combination.
• 79 columns variables: Averages of the mean and standard deviation for each measurement