Notebooks
A Jupyter notebook is a web-based environment for interactive computing. You can run small pieces of code that process your data, and you can immediately view the results of your computation.
Notebooks include all of the building blocks you need to work with data:
- The data
- The code computations that process the data
- Visualizations of the results
- Text and rich media to enhance understanding
Code computations can build upon each other to quickly unlock key insights from your data. Notebooks record how you worked with data, so you can understand exactly what was done, reproduce computations reliably, and share your findings with others.
With Watson Studio, you can create Python, Scala, and R notebooks to analyze your data. You can collaborate with others on your notebooks, add comments, and view a history of your notebooks.
Reconnect to a running Jupyter notebook
Data scientists can reconnect to their running Jupyter notebook and view the progress and cell output after navigating away from the running notebook or after being signed out due to inactivity. When a data scientist reopens the notebook, it connects to the running kernel to restore notebook execution progress after reloading notebook page. This functionality is available only for notebooks running with Jupyter with Python 3.5 or GPU environments.