Earth Data Analytics Coding Challenge 2: Veery Migration

The Veery thrush (Catharus fuscescens) migrates each year between nesting sites in the U.S. and Canada, and South America. Veeries are small birds, and encountering a hurricane during their migration would be disasterous. However, Ornithologist Christopher Hechscher has found in tracking their migration that their breeding patterns and migration timing can predicting the severity of hurricane season as accurately as meterological models!

You can find demo videos and further reading online in the ESIIL Learning Portal Earth Data Analytics Textbook

Getting started using GitHub Codespaces

To get started from the main repository page:

1. Click on the green Code dropdown in the upper right
2. Open the Codespaces tab
3. Click Create codespace on main

It can take a few minutes for the codespace to load for the first time. Be patient! It doesn't make it go faster to try again. You can find out more about all your codespaces at https://www.github.com/codespaces. If you are using this repository through GitHub Classroom, you shouldn't run out of codespace minutes, but you can run out of storage space if you have too many codespaces open or download too much data.

Challenge overview

There are 3 parts to this coding challenge:

1. Complete the analysis notebooks in this repository with the sample data

2. Complete the download notebook in this repository to practice accessing data

3. Write a portfolio post (optional, but this is an option for your final project!):

   a. Come up with your own scientific question you can answer or explore with similar data b. Create a new notebook in this repository b. Reproduce the analysis to help answer your question c. Write a portfolio post explaining your results d. Upload the post to your data science portfolio webpage to show off your work!

Do your best to finish at least the two required parts of the coding challenge by the due date for this challenge. We're here to help!

Portfolio tip

The following code may help you to export your analysis if you want to put it on your portfolio:

jupyter nbconvert <your-notebook-name>.ipynb --to markdown --no-input

You can run it within your notebook as a %%bash cell, or in the terminal.