Sharing NYC Police Precinct Data

Note: This post was originally published April 29, 2011, and updated in June 2020. In February 2022, I updated it again using 2020 Census data. 

Anyone doing population analysis by NYC police precinct might find this post helpful, especially if you're interested in race and/or ethnicity analysis by precinct.

Back in 2011, I wanted to compare the racial and ethnic breakdown of low-level marijuana arrests — reported by police precinct — with that of the general population. The population data, of course, is available from the US Census, but it's not provided by police precincts, which also don't follow any major census boundaries like census tracts. Instead, they generally follow streets and shorelines. Fortunately, census blocks (which in New York, are often just city blocks) also follow streets and shorelines.

So I used US Census block maps and precinct maps from the city to figure out which blocks are in which precincts. Since population data is available at the block level, that data can then be aggregated into precincts.

In this, the third version of this post, I've updated the counts now that the 2020 population data is available.

The 2020 data

• nyc_precinct_2020pop.csv is the 2020 Census population, race, and ethnicity (Hispanic/non-Hispanic) data by NYPD police precinct. The column headers from the US Census are a little cryptic, but you can translate them using the P1 table metadata file and the P2 table metadata file.

• nyc_block_precinct_2020pop.csv — every populated block in NYC is identified by its ID (called "GEOID20"), is matched to the police precinct it sits within, and contains the block's race/ethnicity information. Use the same metadata tables to translate the column headers. Also be sure to read about the caveats below.

• nyc_precincts.geojson depicts the geographic boundaries of the NYPD precincts I used for the files above, as they existed in February 2022. As of this post, the information on the NYC Open Data portal indicates it was last updated on Nov 24, 2021.

Caveats for the 2020 data

The biggest caveat is that the US Census has introduced data fuzziness, or "noise," to make it difficult to identify individuals based on census data. This fuzziness is more pronounced at smaller geographies — the smallest being census blocks, which I've used for these calculations. Hansi Lo Wang did a great primer on these data protections for NPR, and the US Census Bureau has put out a lot of material on how it uses "differential privacy."

Read more »

17 responses
John, great work as always. When you aggregated the block data to precincts, did you compute intersections or use a centroid approach? I find that the centroid approach is much cleaner, easier, and -- except for the "straddlers" as you point out above -- more consistent in terms of allocating small-area population to larger spatial units. (I've been meaning to post something about this, your blog gives me more impetus to do so -- we've been dealing with this extensively at our shop at the CUNY Graduate Center as well.)

Cheers,
Steve

— SR_spatial
Yes! I tried both methods and experienced the same thing. I actually used the "internal point" latitude and longitude provided by the Census Bureau, which should be even better than a simple centroid. Since the precincts seem to have been drawn around the blocks for the most part, it worked really nicely -- and the "straddlers" were easy to spot.
— John Keefe
Hey John,

Cool stuff - it's great to see you share the data and methodology for this stuff.

You could make the (possibly incorrect, especially in rural areas) assumption that people are evenly spaced within the census blocks, and then assign the appropriate numbers to each arbitrary polygon by using the block shapes rather than centroids. The general methodology for this would be to:
- Calculate the percentage intersection of each census block to each polygon
- Multiply the total block population by that percentage
- Sum these partial populations of each block to get the total polygon population [or other attribute]

Assuming your data is unprojected (e.g. epsg:4326) and you want more easily readable areas to look at, then in PostGIS land your query might look something like:
SELECT b.population,
area(b.the_geom) * 100000000 as area,
area(st_intersection(b.the_geom, p.the_geom) *
100000000 as intersected_area
FROM precincts p, blocks b
WHERE st_intersects(b.the_geom, p.the_geom)
--and p.gid = 1234 -- [for some specific precinct]
GROUP by p.gid, b.population, intersected_area, area

Note that all we care about is relative area, not actual area (area calculations don't really make sense in unprojected reference systems; I just multiplied by a big number to make the result more easily readable).

Cheers,

-Josh

— Josh Livni
Josh, thanks so much for this! I was actually heading down this path when I switched back to the centroid method -- partly because I wasn't sure how to pull off this area calculation, and also because there were only three blocks that really came up as an issue -- and I could get a sense of them visually in Google Maps.

One REALLY BIG thing to consider is that you can have problems when much of the area in question falls over water -- which is common for Census *tracts* on shorelines. For example, in Manhattan, there are tracts that have slivers of densely populated areas along the water, and with the bulk of the tract in the Hudson River! That's because the tracts extend to the state line, which is in the water.

A way around that is to consider the tract's AREAWATR and AREALAND metadata values, provided by the Census Bureau, in the calculation.

Better yet, use blocks, which end at the shorelines. (Other, watery blocks -- with 0 AREALAND -- fill out the tracts to the state line.)

— John Keefe
Hi John. Thanks for sharing this tool with the public. I have a question: in doing this research, did you ever figure out how the NYPD precinct lines were actually drawn? I work for a non-profit that serves troubled youth, and we have several locations across the city. I'm trying to compare crime stats in each of the communities we serve, so it would be helpful for me to know how the our precinct llines were created (by population, by census, by geography). I've made several calls to the NYPD, and the answer has been "they've been like that forever." Just wondering if you might have come across the answer in the course of your work. Best, Denise
— denise cante
Hi John, I'm working on a mental health disparities project comparing neighborhood characteristics and I was wondering where/how you accessed precinct level crime data for NYC. I've been scouring NYC OpenData as well as the NYPD website and can't seem to find anything at the precinct level, much less anything broken down by specific crimes. Any advice or sources would be greatly appreciated.
— Gabriel
Hi John, I've been trying to download the dataset but not been successful.... and the aggregate function seems to be not working,,, i've tried on a number of computers... but can't figure out how I can make it work... any thoughts? or suggestions?
— lee
john -- having worked so hard to compile pop by census block and precinct by census block, couldn't you have written a pretty basic summation program to get pop by precinct, without the magic of google? that aside, why not add a table of the 124 totals, for the use of peons lacking the time to emulate your google mastery? such people do matter, and giving them access would make your labors exponentially more worthwhile.
— howard arneson
brother...you just saved me. thank you for this gem!
— Stuart
What is the population of the Sixth Precinct? Erich Goode
— Erich Goode
John: Thanks so much for supplying statistics on the racial composition for the Sixth Precinct as a whole; this is very useful. Is it possible to designate an area within a certain ambit of Washington Square Park (say, 10 blocks) & find out the racial characteristics that area? I realize this would be a very custom-made statistic, but is it a simple matter to figure this out? Erich Goode
— Erich Goode
Hi John, these statistics are amazing and invaluable to doing public policy research. I am doing a project on gun crime that takes into account population density, but I am having a hard time getting data on the size of the precincts. Can you tell me what the GIS data is in for the precinct sizes? GIS Area is usually just supplied in whatever form someone makes it in, but doesn't display. Do you have any idea what units the GIS data is in?
— Dylan
Cohesive and correct. Thank you so much for the time saver.
— Zach
Hi John. I'm having trouble accessing the precinct_block_key.csv file that you linked to above. Is this still available for download? Thanks for building this great tool!
— Claudia
Hi John, This looks amazing! I am currently working on a project that needs to aggregate census tracts to precinct levels. However, when i downloaded the data from the American Community Survey, my tracts were labeled as "Census Tract 556, Kings County, New York" not the longer numerical names, as outlined in your files. Did i do something incorrectly? Is there a way to figure out which tracts belong into which precinct, or is this something that I will have to do manually with maps?
— Amanda D'Souza
Thanks so much John, this key was a big help!
— Joe
Great work. I didn't notice if there was there income data included...
— Walter Kulakowski