Which NY City Precinct Has the Most 2018 Homeless Shelter Arrests So Far?

[zle2105]

Pitch

The NYPD posted a small database of all the homeless shelter arrests from 1/1/18 to 3/1/18. I am going to compare the locations of the NYPD Precincts making the arrests to the distribution of homeless shelters in the city to determine whether the arrests are distributed equally or if there are outliers.

Summary

So far, I have information on whether these arrests are for felonies, misdemeanors, or violations. I will be comparing the distribution of this data between the precincts as well.

My inspiration is this chart from Five Thirty Eight with depicts annual fluctuations in homicides. While I will not be graphing an event over time, I do like how it portrays three different aspects of a crime stat on one image. My only concern is that it may look too busy.

Details

Right now, I am looking for NYPD precinct statistics to supplement my research with.

Possible headline(s): (See Above) Which NY City Precinct Has the Most 2018 Homeless Shelter Arrests So Far?

Data set(s): https://www1.nyc.gov/site/nypd/stats/reports-analysis/homeless-shelter-arrests.page

Code repository:

Possible problems/fears/questions: I am worried that the data pool may be too small and give an exaggerated result. I would like to find stats from either NYC or another comparable city. It may be easier for me to compare arrests in a three month period from a previous year as opposed to extrapolating these stats over a year long period.

Work so far

Compiling df with the csv info.

Checklist

• [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 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

[zle2105]

I completed my data sets and have created a few preliminary charts.

My main concerns now are:

1. How to honestly portray the missing Precinct data on the charts?

2. How to compare the results to the amount of shelters in each Borough?

3. Do both without cluttering the chart in annotations

The First is a graph of the Total Number of Arrests for Each Borough

The Second Graph is for the Total Number of Felonies for Each Borough

The Third Graph is for the Total Number of Misdemeanors for Each Borough

The Fourth Graph is for the Total Number of Violations for Each Borough

Lastly, I have a graph for the Top Five Precincts for Arrests (I am going to label them with each Borough Name). The name of the Precinct is the Y-Axis (this label needs to be clearer).

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[Palarisk]

Hi, really interesting story idea! Your question number 2: How to compare the results to the amount of shelters in each Borough?

Do you have data on the number of people living in these shelters? If so, you could compare the results as an arrest/people ratio. If you don't have that, you could also calculate the arrest/shelter ratio, which would still be meaningful info eg for people living nearby

[nickospi]

• very interesting idea and set.
• I wonder if you could compare this to let's say last year or some years ago. maybe you could find an interesting trend here.
• I think you could do a stacked graph with all the arrests broken down by felonies, misdemeanors, violations.

[dz2383]

Interesting topic! Here are my suggestions:

• Are you able to have the percentage of arrest in each borough? Because it could be that Brooklyn has the largest number of people.
• I'm a little confused about the first graph and the last one. Since they are all about the arrest, what's the difference? -Agreed that using a stacked graph would be more clear!

[sarahslo]

so good that you have taken these steps and charted the data. thing is here, part of what we are seeing is a reflection of the population. that's why the charts look the same. these data need to be divided by the number of people per borough.

it's like saying, china has a lot of people who ride bicycles but hawaii has less...so next step is to normalize it by population.