Inspiration
The PowerPoint presentation and my past experiences of maps inspired me to create this project.
What it does
The map uses CSV files and ESA imagery to help predict Mosquitoes. The predictions use a white point or dot to display the prediction. There is a legend for the ESA imagery and the points and polygons have labels.
How we built it
I found a website full of CSV data that I took and added into the map so that it would display the data. I then used some of the files to code bar charts that displayed the average temperature and based on that, I used the data to make my predictions and found that Georgia, Alabama, and Florida would have more Mosquitoes based on all of the data. So, to show the prediction, I made a polygon that displays the predicted area.
Challenges we ran into
I've ran into problems where codes didn't make charts that I tried to program as the code kept on showing other countries, but I then used I used the pandas, matplotlib.pyplot, and seaborn libraries to create the charts.
Accomplishments that we're proud of
I'm proud of making a map that could help save people.
What we learned
I learned how to use large CSV files to generate a map.
What's next for Mosquito Predicting with Globe Observer Data
I might try to go on and add more datasets to my Mosquito Predicting map.
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