Joe’s Seaside Plotting Python Project

seaside-pass-lat-long-plot.neherdata.com

Goal: Using the latitude and longitude pairs from the ‘location’ key in the pass.json file, accomplish the following:

• Create a dataframe using the python library Pandas and load the latitude and longitude data pairs into columns labeled latitude and longitude, respectively.
• Using a reverse geocoding api like positionstack (there are tons of them out there, most require an api key which you sign up for), create columns in your dataframe labeled address, city, state, and country and populate each latitude and longitude with its respective address, city, state, and country data.
• Using either the python library Folium, GeoPandas, or (preferred) Plotly, render a map that plots each of the latitude and longitude data pairs.
• Export the rendered map as both a PNG image file named map.png and as a HTML file named index.html - commit and push both files to the repository on GitHub.
• Using GitHub Actions, publish the index.html file to GitHub Pages as a static HTML site.
• Enable the setting to secure the GitHub Pages site with HTTPS.
• Have the GitHub Pages site resolve to the custom domain seaside-pass-lat-long-plot.neherdata.com from the GitHub Pages settings panel. I’ve already configured the DNS on the registrar side to work with the domain, you just need to enable it.
• THEN YOU’RE DONE!

• Pro Tip # 1 - create a conda environment to work inside of and install your python libraries in.
• Pro Tip # 2 - use a Jupyter notebook. You’ll install it as a python library after you’ve created and activated your Conda environment.