How we built it
We started solving this problem by uploading all of our relevant data into postgres so that we could perform complex joins and other necessary queries with ease. Most of the data modeling was done in Python using the matplotlib, pandas, and numpy libraries. We also used ArcGIS Pro to help with some of the spatial modeling and figures.
Challenges we ran into
The biggest challenges we ran into this weekend was being able to join data across different datasets for our needs. There were a lot of slight differences in how the data was presented in the different datasets that required some manipulation on our end. It also took some time to be able to look between datasets and find which columns we needed and then think about how we were going to merge all of the necessary information together.
Accomplishments that we're proud of
We were able to get our database successfully running and loaded with the HDMA data, which took awhile due to the size of it.
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