Python & Jupyter Notebook Guide

Jupyter Notebook is an open source Python package for creating, editing and sharing notebook files (file format .ipynb) which are widely used by Data Analysts and Data Scientists. These notebook files allow users to combine their Python code with text and images to create meaningful analyses and reports.

Jupyter Notebooks are used throughout relevant programmes, and Jupyter is, therefore, essential for learners to apply their Python learning within their role.

Learners will need access to a Python interpreter (Python 3.9.0 or above) with the Jupyter Notebook/JupyterLab package installed.

There is no particular requirement for how this is deployed to learners, but if your organisation already uses Python for existing data analysts and data scientists, we recommend that learners are given access to the same Python environment for consistency.

A simple but suitable set-up can be established by following the guidance below. No paid licence is required at any point for any of these items.

The first step is installation of the Python interpreter, which can be installed from the Python website or from the Microsoft store.

Learners will then require various packages used widely within the Data Analytics and Data Science communities, such as Jupyter Notebooks, Pandas, NumPy, Seaborn, and Matplotlib (see last page for the full list of packages used). Packages are bundles of additional Python functionality that can be added to the base Python installation.

Therefore learners need to have the ability to install Python packages. They need to be able to use the command line with pip (which comes as part of the Python installation) without requiring additional levels of authorisation. Pip downloads Python packages from PyPi, the Python package repository, so this may also need to be allowlisted in any firewalls or VPNs.

Alternatively learners can be given access to the packages required in the list at the end of this document as part of a managed Python installation if your organisation distributes these (Jupyter Notebook is included within this list).

In addition to the above, the Visual Studio Code editor can be installed along with the Visual Studio Code extensions for Python and Jupyter to provide a smoother and more impactful user experience. The desktop app can be installed for free from the VS Code website or Microsoft Store, and extensions can be installed for free from the VS Code Marketplace.

This is not strictly required as by default Jupyter Notebooks open in their own application within a standard web browser, but it does provide some helpful additional tools for apprentices to use within their coding projects.

Multiverse places a great deal of emphasis on data governance and ensures learners are taught how to responsibly work with sensitive and personal data before introducing them to Python. Since learners must apply their knowledge to actual business cases, it is crucial that they have access to internal datasets while following any organisational guidelines. You can help support the learner to derive maximum value from the programme by establishing clear guidelines for data management and documenting any internal data governance policies and processes.

No data is required to be uploaded to Multiverse systems as part of the learning process for Python. If apprentices wish to use Python and/or Jupyter Notebooks for their own work or for their portfolio projects in the workplace, then if Python and Jupyter are installed using the process described in this document they run entirely locally on the learner’s machine and do not require any data to be sent or uploaded elsewhere.

The following packages are used for relevant programmes: