Introduction¶

Notebook is a python based Jupyter notebook embedded in Corridor Platform. Notebook users on corridor can access python libraries and other functionalities as they normally would in a Jupyter Notebook.

Additionally, they can access all the information available on Platform through corridor python package. For instance, all registered objects and their simulations can be accessed using corridor library. Users can then do any analysis on these objects using standard python functionalities.

Note that a user's ability to access information on platform is managed based on permissibility of their login credentials.

How is this used?
Users with programming skills can directly access the data within the platform and perform analyses including data exploration, reporting, and modeling without having to leave the platform.

In the default installation, the embedded notebook supports Python - and it is pre-loaded with Pandas and PySpark for analytics.

In this tutorial on Notebook, we will illustrate common capabilites which will come handy for a notebook user on corridor. We will divide the tutorial in following six sections:

1. Introduction
2. Accessing Information Through the Corridor Integrated Notebook
3. Sharing Objects With Other Users Via Integrated Notebook
4. Running Jobs Through the Integrated Notebook
5. Doing Exploratory Analysis Using the Corridor Integrated Notebook
6. Model Building and Result Analysis using the Integrated Notebook
7. Tips and Best Practices

Introduction to key notebook capabilities will be covered in following sections:

- Corridor Integrated Notebooks
- Corridor Package