This project was inspired by my interest in Indian washrooms. I came across a very interesting business model where people setup small kiosks for washing clothes. It seemed genius and transferable to my part of the world where we have lots of poverty and people cannot afford to own washing machines. In looking for data to describe all the locations of similar washroom business clusters within Delhi, India; i found that there was no free open source tool to visualize this appropriately. That was the motivation for this project.

What it does

GeoVisor is a visualization tool which can be utilized to identify and analyze industry clusters across large cities using HereData location data.The dashboard provides regular individuals, investors, policymakers and city committees with a tool which helps better understand regional economies.

How I built it

I used HereData's rest api to pull up relevant feature data which i populated on a mapbox object plugged into a plotly graph on dash.

Challenges I ran into

Finding relevant economic data to populate my panel showing data across cities. It is shocking how poorly constructed free city datasets are. Free city related economic datasets are unicorns and i wasn't able to find a single one to populate my key metrics data panel.

Accomplishments that I'm proud of

I worked on this project with a heavy heart due to a Covid-19 related issue in my family. My uncle is struggling with this and it broke my heart and made me feel guilty being healthy enough to write meaningless code while he was battling for his life in an ICU.

What I learned

I am strong and i will overcome. Free datasets need to be made more readily available and i hope we can convince bankrupted or failed companies to publish internal metrics, that way we can move forward with more labeled sets of quality data across cities.

What's next for GeoVisor

I will probably expand its scope to being able to track singular and multiple global businesses across major cities in the world.

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posted an update

Extended map box dimensions on plotly graph, cleaned up population data. Some data points returned by the api to the map need to be assessed by a QC or QA team. I hope y'all contact me cause i've noticed some things i'd like to bring up but do not really know how to. Overall, nice hackathon. This has been really fun tbh!

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posted an update

Added a bit more verbosity to the map hovertext. You can now see the distance of each object from the center of a given industry cluster.

This is all related to giving investors a chance to identify the most impactful locations in terms of population density but with the least influence of a given industry.

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