The beetlehangers project in the Haelewaters Lab is a research project that I’m currently working on with Ghent University. The project focuses on mapping the distribution of a newly discovered fungi called Hesperomyces harmoniae. The project involves cleaning, manipulating, and visualizing samples using Python and Excel. The team and I are working with a database of Hesperomyces samples that have been collected from a variety of sources, via web-scraping, data requests, and on-site collection.
One of my main tasks on the project has been to verify the data using Python to pull coordinate locations of the entire database for plotting purposes. This involves using Python’s geocoding library to translate the locality information of each beetle specimen into geographic coordinates.
Another important aspect of the project has been developing web-scraping techniques for automated online data collection for Hesperomyces samples from Flickr. We’re using Python to scrape Flickr for images of Hesperomyces, a type of fungus that grows on beetles. These images will be used for further analysis and study of the fungus. As part of my work on the project, I’ve also created and embedded HTML visualizations for user use using WordPress. This involved using Python and Excel to clean and manipulate the data and then using WordPress to create interactive visualizations that users can explore.
The beetlehangers project has been a fascinating and challenging project to work on. It has given me the opportunity to work with scientists from all over the world and has allowed me to further develop my skills in Python, data cleaning and manipulation, and web development.
A new development in my involvement in this project is the creation of an image classifier using CNN image classification. Given a large dataset of images, the classifier is trained to predict whether or not the image contains Hesperomyces samples within it.
To take a quick look at our research, check out this link.
Skills: Python, Excel, and WordPress