Summary

Recommendations for longer notebooks

Create a table of contents on top

You can do that using Markdown. This produces a nice overview for longer notebooks. Example: https://stackoverflow.com/a/39817243

Jupyter Book

https://jupyterbook.org
You can cite and cross-reference
You can toggle cell visibility
… and a lot more

Discussion points

Use cases and reproducibility

If you are already using Jupyter, what tasks do you use it for?
If you are new to Jupyter, do you see any possible use cases?
Do you think Jupyter Notebooks can help tackle the problem of irreproducible results?

Are Jupyter notebooks “workflows”?

A reproducible workflow documents a “pipeline”
Also a Jupyter notebook can be a data processing and visualization pipeline
Are Jupyter notebooks “workflows”?

Interesting blog posts and articles

Similar tools for other languages

R: R Shiny, R Markdown
JavaScript: Observable
Julia: Pluto

Avoiding repetitive code

It all started with a short and simple notebook but how to organize as projects and notebooks grow?

Let’s imagine we wrote this function fancy_plot for a hexagonal 2D histogram plot (please try it in your notebook):

import seaborn as sns

# to get some random numbers
from numpy.random import default_rng


# this one is simple but let us imagine something very lengthy
def fancy_plot(x_values, y_values, color):
    """
    Fancy function creating fancy plots.
    """
    sns.jointplot(x=x_values, y=y_values, kind="hex", color=color)


rng = default_rng()

x_values = rng.standard_normal(500)
y_values = rng.standard_normal(500)

# call our function
fancy_plot(x_values, y_values, "#4cb391")


other_x_values = rng.standard_normal(500)
other_y_values = rng.standard_normal(500)

# call our function again, this time with other data
fancy_plot(other_x_values, other_y_values, "#fc9272")

Now we would like to use this function in 5 other notebooks without duplicating it over all of the notebooks (imagine the function is very lengthy).

It can be useful to create a Python file myplotfunctions.py in the same folder as the notebooks (you can change the name) and place this code into myplotfunctions.py:

import seaborn as sns


# this one is simple but let us imagine something very lengthy
def fancy_plot(x_values, y_values, color):
    """
    Fancy function creating fancy plots.
    """
    sns.jointplot(x=x_values, y=y_values, kind="hex", color=color)

Now we can simplify our notebook:

# to get some random numbers
from numpy.random import default_rng

from myplotfunctions import fancy_plot


rng = default_rng()

x_values = rng.standard_normal(500)
y_values = rng.standard_normal(500)

# call our function
fancy_plot(x_values, y_values, "#4cb391")


other_x_values = rng.standard_normal(500)
other_y_values = rng.standard_normal(500)

# call our function again, this time with other data
fancy_plot(other_x_values, other_y_values, "#fc9272")