🦸 🦹
Use of GitHub
🐍 Use of Jupyter Notebooks
🔡 Accessing tabular data
📈 Data visualization
🌡️Become familiar with data on global climate change
💻 Assignment template
💯 Assignment rubric
This module will focus on examining a crucial global issue and important scientific debate about the state of global fisheries. In this module we will seek to reproduce some of the most widely cited examples of species collapse ever, and examine the evidence behind an influential and widely cited paper on global fisheries, Worm et al 2006. However, rather than use the limited data available to Boris Worm and colleagues in 2006, we will be drawing from the best and most recent stock asssement data available today to see how those patterns have faired.
In this module we will also begin to master one of the most important concepts in data science: manipulation of tabular data using relational database concepts. Instead of working with independent data.frames, we will be working with a large relational database which contains many different tables of different sizes and shapes, but that all all related to each other through a series of different ids.
We will use data from the RAM Legacy Stock Assessment Database. In order to better introduce some important emerging technologies, we will be accessing these data directly from a relatively new platform that is now playing a key role in data sharing in machine learning communities, with the memorable name, HuggingFace. We will be streaming data from https://huggingface.co/datasets/cboettig/ram_fisheries/tree/main/v4.65. We will have more to say about this approach as we progress.
Background abbreviated documentary, features many of the leading authors on both sides https://vimeo.com/44104959