All assignments are a piece of work, that explains a story (almost). Therefore it needs to be clear, descriptive and preferably interactive as well for the viewer.
There are multiple ways to create an output in which the results/figures can be emphasized and not the code itself, that generated it as it is in a notebook.
jupyter offers an easy way to convert a notebook into a (semi)static HTML file:
jupyter nbconvert HowToSubmitAnAssignment.ipynb
This Tutorialspoint site will give you more tips about conversions.
One can also define the styling, colors or use a template
- --execute: executes all cells, it might be needed, to create the right image for the fiven file format
- --no-input: exclude input cells (code cells)
Same as before but one can set the --to
parameter to pdf, latex, slides etc...
There are several modules that is intended for nicely formatted output and offers a structured layout
-
Holoviews a higher level wrapper for many modules
-
Pyviz a collection of modules using various engines (matplotlib, bokeh, plotly)
-
Plotly for both python and R users
or
- R shiny for R users (but python code can be included as well)
As we will see on the Interactive Visualization lecture, all visualizations that can be revealed in a browser is a mixture of HTML, CSS, JS etc. codes. When using the jupyter notebook we are working in an environment that is defined by these coding languages.
There is always a way to directly change these codes and change the outlook of the enviroment or the output. In the presentationtricks folder there is collection of codes, that showcase how can one modify the default environment.