Stanford University

Jul 10-11, 2019

9:00 am - 4:30 pm

Instructors: Claudia Engel, Lori Ling, Linnea Shieh, João Rodrigues

Helpers: Ashley Jester, Zac Painter

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 pre-docs affiliated with SIEPR at Stanford University. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Stanford Institute for Economic Policy Research (SIEPR), 366 Galvez Street, Stanford, CA. Get directions with OpenStreetMap or Google Maps.

When: Jul 10-11, 2019. 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).

Code of Conduct: 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.

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 sgembala@stanford.edu for more information.


Surveys

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

Pre-workshop Survey

Post-workshop Survey


Schedule

Day 1

Before Pre-workshop survey
8:30 Help with setup (optional)
9:00 Introduction to R
10:30 Morning Break
12:00 Lunch Break
13:00Data analysis & Visualization in R
14:30 Afternoon Break
16:00 Wrap Up
16:30 END

Day 2

8:30 Help with setup (optional)
9:00 Introduction to Python
10:30 Morning Break
12:00 Lunch Break
13:00Data analysis & Visualization in Python
14:30 Afternoon Break
16:00 Wrap Up
16:30 Post-workshop survey
16:40 END

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


Syllabus


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.

R

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

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.

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.

Python

Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

  1. Open https://www.anaconda.com/download/#linux with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type
    bash Anaconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
    cd Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

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 macOS and Linux is usually set to Vim, which is not famous for being intuitive. If you accidentally find yourself stuck in it, hit the Esc key, followed by :+Q+! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

nano is a basic editor and the default that instructors use in the workshop. It is installed along with Git.

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.

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 BBEdit or Sublime Text.

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.