The data used for this project came from FWCC Exotic Species Database, and iNaturalist website.
This project was built in separate jupyter files by three members of a team, and then consolidated as one main analysis. Click here to go directly to the consolidated file on Github, or click here to go to the project's Github repo.
"The only constant is change" - Heraclitus (535 BC - 475 BC)
Questions for Analysis
- Are sightings of Burmese pythons in the wild increasing? (Client wants an analysis with visualizations)
- Which three counties are most affected? (Analysis + visualization)
- Are there geographic hotspots? If so, can you estimate the likelihood that volunteers would find pythons if we sent patrols to those areas between today's date and Dec 31st? (Analysis + viz)
- When are people most likely to spot pythons, and why? (Analysis + viz)
- Are sightings cyclical? (Analysis + viz)
- How many python observations do you predict will be recorded for the full 2019 year? (time-series analysis)
- For purposes of developing a social media/citizen science campaign, the client would like to know:
- Should we be using iNaturalist to get the public more engaged? (Back your answer with data)
- Which iNaturalist users are most active in sighting pythons?
- Which iNaturalist users are most active in identifying pythons? Hint: iNaturalist observations must be confirmed by other users...
- Which iNaturalist users are most connected in the python-spotting community (i.e. who are the influencers)?
- Is there overlap between the observers in the two datasets (i.e., are any wildlife officials also using iNaturalist)? (Hint: yes. Visualize it.)
Description
This Project was created by Ray Echevarria, Eduardo Paez, and myself (Sahivy R. Gonzalez) as an assignment from Ironhack's Data Analytics Bootcamp.
Project Structure
First Step: Data Cleaning
This was done by Ray Echevarria, thus you can see his process in the jupyter file.
Second Step: Data Analysis and Visualization
Ray Echevarria and I were in charge of this part. I focused on time series analysis and visualization of population, mapping (visualizations) of the sightings, clustering of sightings by location density through KMeans, and prediction of population through regression modeling. Ray's focus was on probability analysis of sightings, and cyclical analysis of sightings.
Third Step: iNaturalist
This was done by Eduardo Paez, thus you can see his process in the jupyter file.
