OOI Data Python Notebooks

The Ocean Observatories Initiative and other Ocean Observing Systems provide a great opportunity to involve students in data analysis.

Online interactive widgets, like our Data Explorations and those supporting the OOI Lab Manual, offer students an accessible way to engage with and learn from data. However, to develop a deeper understanding of oceanographic processes and data analysis, it’s essential that students also work directly with real data using code, just as many of today’s oceanographers do.

To support this, we’ve compiled a collection of Python notebooks that provide hands-on opportunities to explore oceanographic data. One of the goals of our current project is to build a new collection of notebooks that include guided educational activities to help students develop coding skills while analyzing real-world datasets, reinforcing key oceanographic concepts along the way.

Educational Notebooks

The Ocean Data Labs project is working with the community to develop a new series of lessons and activities that use coding notebooks to engage students in data.  We hope to share more of these later in 2025.  We have also developed a set of prototype python ocean data activities, to demonstrate how to access OOI data using their new data system and to spur creativity and interest in developing programmatic data activities.

Pioneer MAB Storm and Python Quick Intro
Uses data from the new Pioneer Mid Atlantic Bight Array to demonstrate how to plot wind, waves and other datasets to show the impact of a passing storm. the passing
Blog post | Jupyter Notebook | Open in Colab

Pioneer MAB Profiler
An example showing how to plot a timeseries of profiler data, as well as an individual profile on a TS diagram.
Blog post | Jupyter Notebook | Open in Colab

Real-time Data from Axial Seamount
Current predictions suggest the Axial Seamount volcano will erupt again in 2025.  But we still don’t know exactly when.  This notebook demonstrates how to pull the latest seismic, seafloor pressure and other datasets into one graph so you can get a quick view of the current trends.
Blog post | Jupyter Notebook | Open in Colab

Hunga Tonga 2022 Tsunami
Shortly after the Hunga Tonga volcano erupted, the OOI Endurance Array detected both underwater and atmospheric pressure (taunami) waves from the eruption.  And it appears the OOI Pioneer NES Array in the Atlantic saw an atmospheric signal as well.  This notebook demonstrates how to plot all this data, and use that information to calculate phase speeds of the waves.
Jupyter Notebook | Open in Colab

2020 Data Labs REU

During the summer of 2020, we developed a series of notebooks as part of our Virtual REU program.  These activities introduced students to python programming and data analysis using the National Data Buoy Center (NDBC) dataset, which includes a lot of weather-related datasets which can be more initiative for students to start with as they build coding and data skills.

You can find more educational Python examples on our blog.

More OOI Data Processing Examples

While working our Data Explorations and training for other workshops, we developed a number of Python notebooks to demonstrate how to access, process, and visualization data from the OOI. We encourage you to check out these examples, and use them to develop your own lessons and activities to share with the community.