Tips and trics with Jupyter Notebooks - Data to Decision

Table of contents¶

Create internal links using the same heading as the one linked to.
Autofill happens automagically after writing the hashtag in the parenthesis, but this may miss out on capital letters.

[Including Markdown content from](#Including-Markdown-content-from-file)

Example:

Including Markdown content from
Create filling text on the fly
Exporting to PDF
Interactive graphics
HTML

Including Markdown content from file¶

# Use IPython.display.Markdown to display the text in ../../data/lorem.txt
from IPython.display import Markdown
with open('../../data/lorem.txt') as f:
    text = f.read()
Markdown(text)

Create filling text on the fly¶

# Use the lorem package to generate a paragraph.
import lorem as lo
from IPython.display import Markdown
Markdown(lo.paragraph())

Exporting to PDF¶

If not installed:

pip install 'nbconvert[webpdf]'

First time usage to install Chromium for conversion via HTML instead of LaTeX:

jupyter nbconvert --to webpdf --allow-chromium-download your-notebook-file.ipynb

Normal usage:

jupyter nbconvert --to webpdf your-notebook-file.ipynb

For general hiding of code in code cells:

jupyter nbconvert --to webpdf --no-input your-notebook-file.ipynb

Other export options (may need additional packages installed to work): ‘asciidoc’, ‘custom’, ‘html’, ‘html_ch’, ‘html_embed’, ‘html_toc’, ‘latex’, ‘markdown’, ‘notebook’, ‘pdf’, ‘python’, ‘qtpdf’, ‘qtpng’, ‘rst’, ‘script’, ‘selectLanguage’, ‘slides’, ‘webpdf’.
There are also a lot of other customisations available through other parameters, e.g., various templates and themes.
- Installing the python package nbconvert-theme-pale-sand-navy and using --template pale-sand-navy is an example.

Interactive graphics¶

Basic interactivity is possible directly in Plotly when exporting to HTML.
Advanced interactivity needs live running in some Jupyter environment or converting to a dynamic web page using Voilá, Mercury or similar.
Plotly’s renderer may need setting for correct compatibility and inclusion of JavaScript.

# The following renders plotly graphs in Jupyter Notebook Jupyter Lab and VS Code formats (first one helps HTML export)
import plotly.io as pio
pio.renderers.default = "notebook+plotly_mimetype+vscode"
# If you set it to some static output like "png", you can export to PDF (requires the kaleido package)
# pio.renderers.default = "png"

# Gapminder dataset of health and wealth stats for different countries
import plotly.express as px
df = px.data.gapminder()

# Animate all years
px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",
           size="pop", color="continent", hover_name="country",
           log_x=True, size_max=55, range_x=[100,100000], range_y=[25,90], 
           width=600, height=400) 
# Make sure to set width and height to avoid scaling issues with PDF export

HTML¶

Markdown supports some HTML, but Markdown commands have no effect inside HTML tags.
Basic HTML is preserved also when converting to PDF.

$\mu = 1$

Some text over here

Content	More content
Even more content	Last content $\mu = 1$