In this posts I’m going to demonstrate how to get NYC census data at the tract level to estimate census data at the NYPD-precinct level. There are 77 NYPD precincts serving five boroughs of NYC and each precinct contains multiple census tracts. To get the census-level demographics on a per-precinct level, I’ll need a way to aggregate the tract data into precincts - let’s get started!

In today’s post I build upon the last post to demonstrate the use of the tmap package to make a choropleth map in R. I also include instructions on how to use the sf library to obtain the block-level census tract IDs included in the tidycensus ACS data for the State Plane coordinates within the NYC 311 data. If you’re new to making maps, it’s important that you recognize the differences between geographic coordinate and projected coordinate systems.

In this post I’ll be investigating equity between different census tracts in NYC based on economic measures and the open-to-close service request (SR) duration for 311 heat/hot water complaints. Census Tract Granularity If you’ve checked out my previous posts, you know I’ve done a bunch of work with NYC’s OpenData at the ZIP-code level. Today I’m going to go a step further and obtain NYC data with latitude and longitude coordinates and merge it with census data by census tract from the 5-year American Community Survey (ACS) from 2016.

This post is going to follow along and expand on a well-known tutorial for Mixed Effect Linear Models by Bodo Winters, a lecturer in Cognitive Linguistics at the University of Birmingham, Dept. of English Language and Applied Linguistics. While this tutorial will generally follow Winter’s, I have added additional detail for EDA, expanded the details re: code & errors that are encountered, and added notes from many other sources on Mixed Effect Models (see the Sources section at the end for links) - let’s get started!