SF Fire Call Logistics by Boom-Graph R&D: Incident Call Type by Location

Samuel Escapa & Sameer Isaq

Prototype 2

Visualization 2

Filter by year
2014
2015
2016
2017
2018
Transform

Interpretation

The 27 listed zip codes correspond to the 27 neighborhoods that we were given in the dataset. Continuing on with seemingly unexplicable delays in response times, we figured analyzing the types of calls that are reported would give insight. The stacked bars represent the different types of calls in a certain zip code.
Even with adding the ability to see statistics through the years you can see that there hasn't been much change in almost half a decade. Nearly all neighborhoods have remained consistent with their crime rates, so the question still remains as to why there seems to be such a delay in certain areas.

Discussion

Using this data, we can analyze what types of incidents happen in which areas more often than others. This can give us insight in terms of why some areas simply demand a faster response time (i.e. due to more serious calls) or even display a potential existence of prejudice due to certain areas seemingly being neglected.

Credit

Data from: SF Fire Department Calls for Service.


About the Team

Sameer Isaq
I am a third-year Computer Science student from the Bay Area.
I primarily have experience with backend work, but photography is a large hobby of mine and I am trying to transfer some of the artistic skills gained through photography to the world of frontend development.
Hope you enjoy!
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Samuel Escapa
Passionate learner and coder, explorer of the world! USF Class of 2020, Computer science.
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