Lab 10, Maths Building, First Floor, University of Limpopo: Sept 18

Lab 10, Maths Building, First Floor, University of Limpopo

Sept 18 - 20, 2017

18 & 19 Sept: 9:00 - 16:30, 20 Sept: 9:00 - 13:00

Instructors: Ivo Agbor Arrey, Anelda van der Walt, Katrin Tirok, Jacqui Muller

Helpers: Martin Mafunda, TBC

General Information

Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.

We will cover Software installation, Data organization in spreadsheets, Data cleaning with OpenRefine, Introduction to R, Data Analysis and Visualisation in R and Developing post-workshop learning communities. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

This workshop is specifically aimed at researchers and postgraduate students affiliated with the University of Limpopo and the University of Venda who are interested to join the NEPTTP Master's in eScience degree in 2018. Please note that no prior programming experience is expected. Learners will be introduced to foundational concepts of data handling and programming in R. The curriculum do not include statistics or mathematics.

The workshop is jointly organised and funded by the DHET through the Rural Campus Connectivity Project II , Talarify, and the University of Limpopo

Where: TBC. Get directions with OpenStreetMap or Google Maps.

When: Sept 18 - 20, 2017. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organisers have checked that:

The room is wheelchair / scooter accessible.
Accessible restrooms are available.

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email anelda.vdwalt@gmail.com for more information.

Registration:Please register for the workshop by completing the form available at https://goo.gl/forms/IvRRQoleuB9G74Dp2.

Schedule

Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey

Day 1 - Monday 18 Sept		Day 2 - Tuesday 19 Sept		Day 3 - Wednesday 20 Sept
09:00	Installations/Ice Breaker/Introductions	09:00	Data Cleaning with OpenRefine	09:00	Data visualisation in R
09:30	Introduction to Linux Shell	09:30	OpenRefine Continues	09:30	Visualisation continues
10:30	Break	10:30	Break	10:00	Break
11:00	Linux Shell continues	11:00	Intro to R	10:20	Visualisation continues
12:30	Lunch	12:30	Break	11:30	Wrap up
13:15	Linux shell continues	13:15	R Continues	12:30	Finish
15:00	Break	15:00	Break
15:20	Better use of Spreadsheets	15:20	R Continues
16:30	Wrap up	16:30	Wrap up
16:45	Finish	16:45	Finish

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.

Syllabus

The Unix Shell

Files and directories
History and tab completion
Pipes and redirection
Looping over files
Creating and running shell scripts
Finding things
Reference...

R for Data Analysis

Introduction to R
Starting with data
Aggregating and analyzing data
Data visualization
Reference...

Cleaning Data with OpenRefine

Working with OpenRefine
Filtering and Sorting Data
Examining numbers
Scripts from OpenRefine
Exporting and Saving Data
Reference...

Better Use of Spreadsheets

Formatting data tables in Spreadsheets
Formatting problems
Dates as data
Quality control
Exporting data
Reference...

Setup

To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Windows

Video Tutorial

Download the Git for Windows installer.
Run the installer and follow the steps bellow:
1. Click on "Next".
2. Click on "Next".
3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
4. Click on "Next".
5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
6. Keep "Use Windows' default console window" selected and click on "Next".
7. Click on "Install".
8. Click on "Finish".
If your "HOME" environment variable is not set (or you don't know what this is):
1. Open command prompt (Open Start Menu then type cmd and press [Enter])
2. Type the following line into the command prompt window exactly as shown:
  setx HOME "%USERPROFILE%"
3. Press [Enter], you should see SUCCESS: Specified value was saved.
4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

Mac OS X

The default shell in all versions of Mac OS X is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

Linux

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by :q! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

Windows

Video Tutorial

nano is a basic editor and the default that instructors use in the workshop. To install it, download the Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

Mac OS X

nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.

Others editors that you can use are Text Wrangler or Sublime Text.

Linux

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

Mac OS X

Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the RStudio IDE.

OpenRefine

For this lesson you will need OpenRefine and a web browser. Note: this is a Java program that runs on your machine (not in the cloud). It runs inside a web browser, but no web connection is needed.

Windows

Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It will not run correctly in Internet Explorer.

Download software from http://openrefine.org/

Create a new directory called OpenRefine.

Unzip the downloaded file into the OpenRefine directory by right-clicking and selecting "Extract ...".

Go to your newly created OpenRefine directory.

Launch OpenRefine by clicking google-refine.exe (this will launch a command prompt window, but you can ignore that - just wait for OpenRefine to open in the browser).

If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.

Mac

Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser. It may not run correctly in Safari.

Download software from http://openrefine.org/.

Create a new directory called OpenRefine.

Unzip the downloaded file into the OpenRefine directory by double-clicking it.

Go to your newly created OpenRefine directory.

Launch OpenRefine by dragging the icon into the Applications folder.

Use Ctrl-click/Open ... to launch it.

If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.

Linux

Check that you have either the Firefox or the Chrome browser installed and set as your default browser. OpenRefine runs in your default browser.

Download software from http://openrefine.org/.

Make a directory called OpenRefine.

Unzip the downloaded file into the OpenRefine directory.

Go to your newly created OpenRefine directory.

Launch OpenRefine by entering ./refine into the terminal within the OpenRefine directory.

If you are using a different browser, or if OpenRefine does not automatically open for you, point your browser at http://127.0.0.1:3333/ or http://localhost:3333 to use the program.