The purpose of this project is to demonstrate your ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis.
One R script called run_analysis.r should be created 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.
There is one main script performing all the required operations named, as per
objectives, run_analysis.r. The script expects the working directory to be
already set to its same location. If this is not the case, update the R working
directory issuing command:
setwd("<path-to-script's-directory/folder>")
All sourced and saved data is placed in the data sub-folder, where the
original dataset samsung-sensors-data.zip can be found. This file can safely
be removed as the script will try to re-download it if not available. The
script will save in the same folder the output of the analysis, namely:
tbl_tidy_1/Data set and CodeBook resulting from Step 4;tbl_tidy_2/Data set and CodeBook resulting from Step 5.
As an example, the script generates the plot presented in the following figure
to show how the data from tbl_tidy_1 can be exploited.
The CodeBooks are automatically generated by the script, still they are committed in this repository to ease their use (See ) CodeBook: TBL TIDY 1 and CodeBook: TBL TIDY 2