#Jupyter notebook tutorial pdf code#

Within digital humanities literature, one can find references to Jupyter notebooks (split off from iPython, or interactive Python, notebooks in 2014) dating to 2015.

Jupyter notebooks have seen enthusiastic adoption in the data science community, to an extent where they are increasingly replacing Microsoft Word as the default authoring environment for research.

#Jupyter notebook tutorial pdf code#

However, if you have the necessary rights and permissions to republish the text of your scholarship in another format, Jupyter notebooks provide an environment where code and prose can be juxtaposed and presented with equal weight and value. Currently, code is typically published separately on GitHub or in another repository, where readers have to look up a footnote in the text to find out what scripts are being referenced, find the URL of the repository, go to the URL, look for the scripts, download them and associated data files, then run them. What if you could publish your scholarship in a format that gave equal weight to the prose and the code? The reality of current academic publication guidelines means that the forcible separation of your code and written argumentation may be a necessity, and their reunification may be impossible without navigating numerous obstacles. While publishers are increasingly open to the inclusion of links to supplementary code and other materials, such an arrangement inherently relegates them to secondary status relative to the written text.

When computation is an intrinsic part of your scholarship, how do you publish a scholarly argument in a way that makes the code as accessible and readable as the prose that accompanies it? In the humanities, the publication of scholarship primarily takes the form of written prose, in article or monograph form. Scaling up computation with Jupyter notebooks.Jupyter Notebooks for other programming languages.Saving, exporting, and publishing Jupyter notebooks.

Navigating the Jupyter Notebook interface.