This is a dashboard of eBird data for Maharashtra. The original version (divided into seasons) was analysed first. Then the automated (monthly & seasonal) workflow was devised based on that. Data for all of 2025 & January 2026 were generated initially, and after this, the dashboard will be updated every month.
ABOUT eBird DATA:
I will be using the knowledge gained through this project to create a dashboard to present the results of an SDM, and also utilizing it in some other projects with spatial dashboards. This about page will be updated accordingly, to link to those projects.
I may improve this dashboard, but it was mostly a prototype so I could figure out a template for displaying a map and some extra data on the side, and also so I could learn CI/CD stuff, and get a grasp of Leaflet and JavaScript+CSS in general, etc etc. JavaScript & CSS can be very versatile and that's why I elected to use it. One of my inspirations for this was, strangely enough, a browser game called corru.observer. The creator didn't use WebGL for graphics, just CSS, and it runs quite nicely on the browser, utilizing the format of a web page in an interesting way to convey information. Why would a game be inspiration for data analytics? Because both things involve storytelling, and storytelling involves conveying information, and I got some ideas from the way corru.observer conveys information and the fact that it's doing so much while still running pretty smoothly (which is important; I want the dashboards to be accessible regardless of the quality of your device or network WHILE ALSO making them interesting/dynamic/interactive!). Also, games are a medium BUILT on interactivity, and I would like to make cool interactive dashboards, which allow you to REALLY get an intuitive grasp of the data. This dashboard isn't even halfway to what I'm imagining, partly due to its simplicity (which IS a strength but again, not what I'm imagining), but I'll figure it out as I go along!
AI disclosure: I did the entirety of the original analysis by myself, and used ChatGPT for some parts of the automation process (along with cleaning up my newbie attempts at webdev).
Also: You'll notice that the Monthly (automated) and Seasonal (automated) views have more sparse analysis, and that's because their main purpose was to delve into CI/CD with GitHub Actions & YAML workflows, so I was focused on learning THAT and encountered some difficulty in automating some parts of my original process. For example, Habitat specializations, Migratory patterns, and Common behaviours were taken from stateofindiasbirds.in/. I could've done some stuff with the Python scripts to repeat the process of adding that data to the monthly data, but frankly I got tired and wanted to just move onto the new skill stuff.
Find the repo here
Find my GitHub profile here
Find my LinkedIn here
Personal website will be created & added here later (will include links to all my data projects)
MORE DATA! Let's take a look at the data for 2025. We'll be looking a little bit at data from previous years too, but please note that the data used for the 'original' maps is different from the data obtained in the automated process (API calls result in a need to be mindful of rate-limiting, didn't include 'protocol type' & 'observation type' as a result, refer to the About section).
The eBird database consists of data inputted by users whose expertise may vary substantially. There is some spatial and temporal bias as well but https://www.sciencedaily.com/releases/2018/03/180312085117.htm
[ This section of the site is INCOMPLETE as of 24 February 2026. Currently focusing on SDM project, but this part will be built soon. ]