- ARCHIVE / Data science
- More Jupyter notebooks: pyvis and networkx
Lately I’ve been spending more time creating Jupyter notebooks that demonstrate how to use the Dimensions API for research analytics. In this post I’ll talk a little bit about two cool Python technologies I’ve discovered for working with graph data: pyvis and networkx. pyvis and networkx The networkx and pyvis libraries are used for generating and visualizing network […]
- Getting to grips with Google Colab
I’ve been using Google Colab on a regular basis during the last few months, as I was curious to see whether I could make the switch to it (from a more traditional Jupyter/Jupyterlab environment). As it turns out, Colab is pretty amazing in many respects but there are still situations where a local Jupyter notebook […]
- Calculating Industry Collaborations via GRID
A new tutorial demostrating how to extract and visualize data about industry collaborations, by combining the Dimensions data with GRID. Dimensions uses GRID (the Global Research Identifiers Database) to unambiguously identify research organizations. GRID includes a wealth of data, for example whether an organization has type ‘Education’ or ‘Industry’. So it’s pretty easy to take advantage of […]
- Introducing DimCli: a Python CLI for the Dimensions API
For the last couple of months I’ve been working on a new open source Python project. This is called DimCli and it’s a library aimed at making it simpler to work with the Dimensions Analytics API. The project is available on Github. In a nutshell, DimCli helps people becoming productive with the powerful scholarly analytics API […]
- Running interactive Jupyter demos with mybinder.org
The online tool mybinder.org allows to turn a Git repo into a collection of interactive notebooks with one click. I played with it a little today and was pretty impressed! A very useful tool e.g. if you have a repository of Jupyter notebooks and want to showcase them to someone with no access to a Jupyter […]
Parerga und Paralipomena / At the core of all well-founded belief lies belief that is unfounded – Wittgenstein
