AE Analytics

Jupyter Notebooks

What are Jupyter Notebooks?

The Analytics Engine utilizes Jupyter notebooks to be the user-facing method to showcase the variety of applications built upon tools developed as part of the climakitae Python library. Each of these notebooks can be used in multiple applications focused on, but not limited to, the energy sector in California supporting ratepayers through reliable and renewable energy management.

How to Use the Notebooks

The Jupyter notebooks linked below contain example code to support the user-identified applications and showcase how to use climakitae for data retrieval, subsetting, and general analysis. Interactive notebooks are publically available on GitHub in the cae-notebooks repository, and available on the Analytics Engine Jupyter Hub for users with access. The notebooks provide step-by-step functionality to access, analyze, and plot climate data available through the Analytics Engine. The notebooks can be used as-is or serve as a starting point to adapt to a specific organization’s needs, workflows, or particular applications.

Python tools included in the notebooks provide examples for how to work with both the historical and projection data on the platform, and demonstrate how to move from the climate variables provided through the Analytics Engine to actionable information that can inform decision-making and risk assessments.

Notebook Types

Analytics Engine notebooks are organized into three categories to help users identify the right notebook for their needs and set expectations for how each is structured.

  • Tool notebooks are designed to execute a specific workflow and produce a concrete output, such as an analysis, data product, or visualization. These notebooks are action-oriented and intended to be run end-to-end with minimal modification, though they can be adapted to suit specific organizational needs.
  • Method notebooks walk through a methodology used in the Analytics Engine analyses. They explain the scientific or technical approach behind a particular technique and are useful for users who want to understand how a method works before applying it, or who need to document or reference the methodology in their own work.
  • Education notebooks are designed for learning. They introduce a climate science topic or concept and are a good starting point for users who are newer to climate data or want to build foundational knowledge before working with tool or methods notebooks.

Each notebook in the AE Notebooks GitHub repository includes a categorical assignment in the AE Navigation Guide, which provides a full index of available notebooks organized by type, topic, and application.

Actively Maintained Notebooks

This set of notebooks is actively maintained by the Cal Adapt team to highlight how to use climakitae, as well as showcase some scientific topics of high interest and value, such as Global Warming Levels.

  1. basic_data_access.ipynb: Access, subset, and export climate data using climakitae
  2. renewables_data_access.ipynb: Access and plot derived renewables data products
  3. weather_station_data_access.ipynb: Access quality controlled historical weather station data
  4. derived_variables_demo.ipynb: Define and use custom derived climate metrics with register_user_function
  5. warming_level_methods.ipynb: Compare SSP time-based and Global Warming Levels approaches
  6. custom_climate_profiles.ipynb: Generate annualized hourly climate profiles for energy system modeling and planning
  7. threshold_tools.ipynb: Define extreme events and analyze their likelihood using extreme value theory

Other notebooks

The Cal Adapt team has an additional repository of notebooks that are not actively maintained, but are saved as referenced for our users and developers. This includes notebooks developed with our partners for specific use-cases, notebooks used for one-off data or figure generation, among others. You can view and download these notebooks in the cae-archives repository on GitHub.