Wright State University

Feb 28-Mar 1, 2019

9:00 am - 4:30 pm

Instructors: Sarah Supp, Robert Flight

Helpers: Molly Simonis, Michaela Woods, Leon Katona

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General Information

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. 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 "Good Enough Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers who may be interested. You don't need to be from Wright State University to attend! However, this workshop is being organized and promoted to Wright State students and researchers, so do register quickly if you want to attend. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Wright State University, 3640 Col. Glenn Hwy, Dayton, OH 45435. Get directions with OpenStreetMap or Google Maps.

When: Feb 28-Mar 1, 2019. Add to your Google Calendar.

Food: Sponsored by University of Dayton Department of Biology, breakfast food, coffee and snacks will be provided to workshop participants on both days. Lunch will not be provided, but there are many food options nearby, or there is refrigeration and microwaves available for those who want to pack a lunch.

Parking: There are campus parking lots near the buildings being used. If you are not from Wright State University and need parking information, please contact molly.simonis@gmail.com.

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 organizers 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 molly.simonis@gmail.com for more information.


Surveys

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

Pre-workshop Survey

Post-workshop Survey


Schedule

Thursday, Feb 28

Before starting Pre-workshop survey
Morning Data organization in spreadsheets
OpenRefine for data cleaning
NoonLunch on your own
AfternoonData management with SQL
Evening END

Friday, Mar 1

Morning Introduction to R
NoonLunch on your own
AfternoonData analysis and visualization with R
Evening Post-workshop survey
END

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


Syllabus

Data Organization

  • Why spreadsheets?
  • Formatting data tables in Spreadsheets
  • Formatting problems
  • Dates as data
  • Quality control
  • Exporting data
  • Reference...

Open Refine

  • Introduction to OpenRefine
  • Working with OpenRefine
  • Filtering and Sorting
  • Examining Numbers
  • Scripts from OpenRefine
  • Exporting and Saving Data
  • Reference

SQL for Data Management

  • Why are relational databases useful?
  • Create a database from text files
  • SQLite data types
  • Database operations
  • Combining data
  • Reference

Introduction to R

  • Working with objects
  • Using scripts
  • Calling functions
  • Subsetting vectors
  • Loading external data
  • Indexing data
  • Working with characters and factors
  • Reference

Data Analysis and Visualization Using R

  • Using dplyr to slice and dice data
  • Piping data from one function to another
  • Adding new columns to your data
  • Reshaping your data for different purposes
  • Producing different types of plots with ggplot2
  • Changing plot settings
  • Facetting plots
  • Building complex and customized plots
  • 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.

In addition to the software below, each lesson will require data to be downloaded and / or packages to install. If you are concerned about download and installation times, please click on each of the headings in the syllabus to go to that lesson page to see what data need to be downloaded.

Installation Assistance

We strongly encourage you to install and check the software before the workshop. If you have trouble installing the required software, there will be helpers available at 8:30am on both workshop days to help you install the software.

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.

macOS

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 dnf 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.

macOS

SQLite comes pre-installed on macOS.

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.

DB Browser for SQLite

To be able to interact with the SQLite databases, we will use the DB Browser for SQLite software. Please download and install it before the workshop. It is available for Windows, Mac, and Linux.

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 openrefine.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.

Git

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com. You will need a supported web browser.

You will need an account at github.com for parts of the Git lesson. Basic GitHub accounts are free. We encourage you to create a GitHub account if you don't have one already. Please consider what personal information you'd like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.

Video Tutorial
  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select “Use the nano editor by default” and 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. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  3. 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]
Video Tutorial

For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent "mavericks" installer from this list. Because this installer is not signed by the developer, you may have to right click (control click) on the .pkg file, click Open, and click Open on the pop up window. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.8) use the most recent available installer labelled "snow-leopard" available here.

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo dnf install git.