anurag313 / Getting-and-Cleaning-Data

Repository for "Getting and Cleaning Data" course project.

gettingcleaningdata

"Getting and Cleaning Data" Course Project

Data Source

data description: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones data url: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip

Original Data Description

Data Set Characteristics: Multivariate, Time-Series

Number of Instances: 10299

Area: Computer

Attribute Characteristics: N/A

Number of Attributes: 561

Date Donated: 2012-12-10

Associated Tasks: Classification, Clustering

Missing Values?: N/A

Number of Web Hits: 95106

Source:

Jorge L. Reyes-Ortiz, Davide Anguita, Alessandro Ghio, Luca Oneto.

Smartlab - Non Linear Complex Systems Laboratory

DITEN - Università degli Studi di Genova, Genoa I-16145, Italy.

activityrecognition '@' smartlab.ws

www.smartlab.ws

Process for running "run_analysis.R" script:

1. Unzip the dataset to the R working directory. Unzipping the dataset create a directory named "UCI HAR Dataset" into the working directory.
2. Install the following packages: "reshape2" and "plyr".
3. From the R environment and with the target directory present in the working directory, execute the command: source("run_analysis.R")
4. Output of the execution of code is generation of the tab-delimited text file "tidydata.txt" in the working directory.

Additional information about the "run_analysis.R" script:

Variables in the script

• activity - read and store info from file "activity_labels.txt".
• testactivity and trainactivity - read and store info about activity codes from files in each train and test groups, namely "Y-train.txt" and "Y-test.txt" respectively.
• test and train - read and store info about the measurements that were collected for test and train groups.
• features - read and store info about the feature names which are labeled V1 through V561 in the test and train data files. Features are used to decode the measurement names.

Tidy dataset

• The generated tidydata set is stored in a tab-delimited text file "tidydata.txt" in the working directory.
• The file tidydata.txt has 180 rows (30 subjects * 6 activities).
• The file tidydata.txt has 68 columns. Column 1 is "subject", column 2 is "activity" and the remaining 66 columns are the selected variables (mean and std).