Mafikeng Campus, North-West University Building A4 Old Science Building Undergaduate Lab Phase 2

Nov 1 - 3, 2017

9:00 - 16:00

Instructors: Caroline F Ajilogba, Bennett Kankuzi, Amy Hodge, Martin Dreyer

Helpers: TBC

General Information

Data Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

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.

Where: Old Science Building A4, Undergraduate Lab Phase 2, Mafikeng. Get directions with OpenStreetMap or Google Maps.

When: Nov 1 - 3, 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:

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 carolfadeke@gmail.com for more information.

Registration: Please register by completing the form at https://goo.gl/forms/nOk5uPjkUGHDyDjh2.


Schedule

Surveys

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

Pre-workshop Survey

Post-workshop Survey

Day 1

08:30-09:30 Installation of software
Data organization in spreadsheets
10:00-10:15 Introduction
10:15-11:00 Formatting data tables in Spreadsheets
11:00-11:20 Formatting problems
11:20-11:40 Tea Break
11:40-11:50 Dates as data
11:50-12:00 Quality control
12:00-12:15 Exporting data
12:15-13:00 Lunch Break
OpenRefine for data cleaning
13:00-13:10 Introduction
13:10-13:55 Working with OpenRefine
13:55-14:15 Filtering and Sorting with OpenRefine
14:15-14:35 Examining Numbers in OpenRefine
14:35-14:50 Scripts from OpenRefine
14:50:15:10 Exporting and Saving Data from OpenRefine
15:10-15:30 Other Resources in OpenRefine
15:30-16:00 Introduction to R

Day 3

08:30-09:00 Morning Tea
09:00-10:00 Databases using SQL
10:00-10:40 Basic Queries
10:40-11:30 SQL Aggregation
11:30-12:15 Joins and aliases

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


Syllabus

Programming in R

  • Working with vectors and data frames
  • Reading and plotting data
  • Creating and using functions
  • Loops and conditionals
  • Using R from the command line
  • Reference...

Managing Data with SQL

  • Reading and sorting data
  • Filtering with where
  • Calculating new values on the fly
  • Handling missing values
  • Combining values using aggregation
  • Combining information from multiple tables using join
  • Creating, modifying, and deleting data
  • Programming with databases
  • Reference...

Open Refine

  • Introduction to OpenRefine
  • Importing data
  • Basic functions
  • Advanced Functions
  • 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.

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.

SQLite

SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.

Windows

The Data Carpentry Windows Installer installs SQLite for Windows. If you used the installer to configure nano, you don't need to run it again.

Mac OS X

SQLite comes pre-installed on Mac OS X.

Linux

SQLite comes pre-installed on Linux.

If you installed Anaconda, it also has a copy of SQLite without support to readline. Instructors will provide a workaround for it if needed.

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.