One of the particularities of scientific computing is the need for experiments, explorations, and collaborations. This need is addressed by notebooks.
Notebooks are collaborative web-based environments for data exploration and visualization — the perfect toolbox for data science. They help create reproducible, shareable, collaborative computational narratives.
There are alternatives to the well known Jupyter / iPython notebook. Multilinguism, Big data are among several traits addressed by new entrants such as Beaker or the Apache Zeppelin notebooks while Matlab, SageMath have existed for years.
In Jupyter, Zeppelin, Beaker: The Rise of the Notebooks, I explore the different Notebook platforms that are available to the Data Scientist. This article was contributed to the Open Data Science blog.
If you liked this post, please share it on twitter And leave me your feedback, questions, comments, suggestions below. Much appreciated :)