Ambulance response times in NYC

[adrianblanco]

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Pitch

Summary

The black spots to have an emergency in NYC.

My data come from Emergency Medical Services (EMS) hosted on NYC Open Data.

I was inspired by this project:

Details

Possible headline(s):

• Which are the worst communicated areas to have an emergency?
• Which is the Ambulance Response Times for different areas in NYC?
• How long does it take for an ambulance to arrive to the emergency scene?
• Which are the average response times for eack kind of emergencies?

Data set(s): https://data.cityofnewyork.us/Public-Safety/EMS-Incident-Dispatch-Data/76xm-jjuj

Code repository: https://github.com/adrianblanco/data-studio/tree/master/code/01-ems

Possible problems/fears/questions:

• Filter 7M rows

Work so far

Checklist

This checklist must be completed before you submit your draft.

• [x] I have already spent time with my data set, opening it, exploring it, etc
• [ ] I have created a "DIARY.md" file to save links and list all of the terrible, no good problems I come across
• [ ] My issue issue has [Project] in the title
• [x] My issue links to my data set(s)
• [ ] My issue links to my code repository
• [ ] My issue explains what I'd like to explore in the data set
• [ ] My issue includes images - either inspiration or what I've done so far
• [ ] I have received two comments of peer feedback on my pitch issue

[maxarvid]

Cool, make sure to get those zipcodes to make sure the data is nice and granular. Maybe also consider taking means of wait times to make the data more manageable?

[cfelke]

Nice, I think the most important thing right now is to keep your data as compressed as possible to proceed with your analysis. Basically, what Max just wrote. Excited to see all of our animated maps \o/

[adrianblanco]

Status update:

• I have refined the code and solved some issues to deal with and filter 7M rows that's the reason the styles are not finished yet
• Respiratory and cardiac conditions analyzed

• New charts plotted without styling

  avg response time per zipcode, respiratory problems

  

  number of respiratory incidents per zip code, respiratory problems

  
• Filter to pull the data from the API created

TODOs:

• Working on styles for the new charts
• Create a dataframe to collect all the data analyzed
• Get the main incidents per zipcode
• Plot the info in a map
• Frame the final story

[maxarvid]

Clearly a project that demands a map as zipcodes by themselves are difficult to interpret. Let's reconvene when the map is presentable?

[cfelke]

Showing your findings in a map would be great, if you manage to pull this off - go for it! Regarding the style of your bar charts I'd play a little with matplotilb, customize it aso.

[playfairbot]

Howdy! I'm a little robot, here for a surprise inspection.

You need some feedback, let me summon @kevinlitman-navarro, @Katerinavts, @SimoneLuc for you

It looks like we need to fix up your your update a little bit! Edit it by clicking the pencil in the top right-hand corner. It requires:

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Maybe you just didn't use the template? If not, edit your comment, cut and paste the template in, and then fill it out.

[kevinlitman-navarro]

• Short of a zipcode map as mentioned above, I'd like to see per borough analysis. Maybe this could be combined with other demographic data so you could see how the makeup of an area might correlate with the ambulance data
• Also certainly needs a lot of styling work, but it seems as if you just haven't gotten around to it yet
• Seems like you could pretty easily turn this into something any news org would want to publish, since you've already found the data. I hope to see it on the Upshot soon!

[adrianblanco]

Visuals improved:

Moving to a map soon!

[sarahslo]

i think, yes, move to a map! i want to know where these place are and not ever be there. can you do the opposite and give us the places with the shortest response times? or include other types of emergencies? i am interested!

also, change the seconds into minutes and seconds. no one will ever say, 'it took the ambulance more than 2500 seconds to arrive.' this measure should be reader-friendly.