Ruv7
commented
8 years ago Published on 8/31, Trending notebooks moved to consideration of topics for next iteration.
Closed Ruv7 closed 8 years ago
Ruv7
commented
8 years ago Published on 8/31, Trending notebooks moved to consideration of topics for next iteration.
Altair: Altair is a new Python package implementing a declarative API for fast and efficient data exploration and visualization. Altair's goal is not to add another plot rendering tool to Python's current visualization milieu, but rather to allow Python users to easily generate JSON-formatted visualization specifications following the well-defined Vega-Lite visualization grammar. The resulting visualizations can be seamlessly rendered in the Jupyter notebook via the ipyvega package. This declarative, grammar-based approach means that Altair, via Vega-Lite, could someday serve as a means for various visualization libraries to work together, communicating via the lingua franca of the Vega-Lite grammar. Attaining this goal would require other visualization libraries to input and output Vega-Lite specifications of their plots: a daunting task, but one in which developers of Matplotlib, Bokeh, Plotly, and other libraries have expressed interest. (written by: Jake VanderPlas, Senior Data Science Fellow, Director of Research in Physical Sciences, University of Washington eScience Institute)
Find trending notebooks on Github. Github is now indexing notebooks (below is from draft of blog post on Ghost written by Brian Granger)
Earlier this year, GitHub started to render Jupyter Notebooks on their website (see our blog post about that here). This feature has been very popular with our users, many of whom are storing their notebooks in git repositories on GitHub. As the following screenshot shows, this feature allows anyone in the world to view notebooks on GitHub. This opens the door for the broad sharing of computational narratives that combine code with equations, visualizations and narrative text.
The community of Jupyter and GitHub users have embraced this new feature! Since the release of this feature, we've seen an increase in the total number of notebooks hosted on GitHub from approximately 200,000 to over half a million.
A common question we get from users is "how do we find interesting and popular notebooks?" We have also struggled ourselves to keep track of all the amazing things that users are doing with the Jupyter Notebook. Today, we are excited to announce a new feature in GitHub that addresses some of these issues.
For the past few months, GitHub has been indexing Jupyter Notebooks in their search. As part of this, they created a Jupyter Notebook category on the trending page here:
https://github.com/trending?l=jupyter-notebook&since=weekly http://blog.jupyter.org/2015/05/07/rendering-notebooks-on-github/
Recent events + video links to talks (JupyterDay ATL, PyBay, PyData)