• Be multi-lingual!
• Introduction to Python
• Introduction to Jupyter

• R
• HTML, CSS
• Shell scripting
• Python
• MATLAB

• Computer languages are similar, have strengths & weaknesses
• Comprehension before production (read code before you write it)

• Beautiful is better than ugly.
• Explicit is better than implicit.
• Simple is better than complex.
• Complex is better than complicated.
• Readability counts.

• Released in 1991
• Supports imperative, object-oriented, and functional programming paradigms
• Syntax makes extensive use of white space

Python:

def mult_by_two(x):
  x * 2

R:

mult_by_two <- function(x) {
  x * 2
}

• Uses = for assignment (vs. R’s <-)

• Scientific programming
• Web programming (Django)
  • Instagram, Disqus, Mozilla, Bitbucket, Open Science Framework (OSF)

• GitHub repo: https://github.com/psu-psychology/jupyter-resources
• How to: https://psu-psychology.github.io/psy-525-reproducible-research-2020/how_to/jupyter-notebooks-psu.html

• Literate programming documents (code + text + images + …) in your browser
• Began as interactive Python (iPython)

• Local machine
  • Installing Python, Jupyter
  • Launch from terminal or Command Prompt app via jupyter notebook
• Penn State’s Juptyer notebook hub: https://lxclusterapps.tlt.psu.edu:8000

• https://github.com/psu-psychology/jupyter-resources/blob/master/psy-525-jupyter-notebooks.ipynb

• Connect to PSU VPN via Cisco AnyConnect, then
  • https://lxclusterapps.tlt.psu.edu:8000
  • Create a Jupyter notebook on the TLT server
• Install Python on your local machine; install Jupyter & launch it.

• Tools for reproducible data-gathering