June 16, 18, 23 & 25, 2020
9:00 am - 12:00 pm
Instructors: Trisha Adamus, Clare Michaud, Sarah Stevens, Tobin Magle
Helpers: Erin Jonaitis, Mary Murphy
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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 (Post-docs, University Staff, Undergraduate Students, Faculty, etc.). You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: Online. Get directions with OpenStreetMap or Google Maps.
When: June 16, 18, 23 & 25, 2020. 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).
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 facilitator@datascience.wisc.edu for more information.
Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Please be sure to complete these surveys before and after the workshop.
| Before starting | Pre-workshop survey |
| June 16 | Data Organization in Spreadsheets |
| June 16 | OpenRefine for Data Cleaning |
| June 18 | Introduction to R: dplyr |
| June 23 | Continuation of R: ggplot and Rmd |
| June 25 | Data Management with SQL |
| Post-workshop survey | |
| END |
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.
For this workshop we will be using the [ADNI Dataset](http://adni.loni.usc.edu/). Upon registration you will need to read and accept the data use agreement. A link to download the data will be given during the workshop as this is a sensitive dataset.
For the spreadsheets lessons you will need to have a spreadsheet program, such as Microsoft Excel or the Calc program in OpenOffice . If you do not already have one of these programs installed, please follow the links above to install.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
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.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
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.
SQL is a specialized programming language used with databases. We use a simple database manager called SQLite in our lessons.
curl https://uw-madison-datascience.github.io/2020-06-16-uwmadison-dc/getsql.sh | bash3.27.2 2019-02-25 16:06:06 ...If you want to do this manually, download sqlite3, make a bin directory in the user's home directory, unzip sqlite3, move it into the bin directory, and then add the bin directory to the path.
SQLite comes pre-installed on macOS.
SQLite comes pre-installed on Linux.
$ bashIf you installed Anaconda, it also has a copy of SQLite
without support to readline.
Instructors will provide a workaround for it if needed.
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.
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.
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.
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.