Overview

The councilcount package allows easy access to population data for over 100 demographic groups across various NYC geographic boundaries. This data was pulled from the 5-Year American Community Survey. For geographic boundaries that are not included in the ACS, like council districts, estimates were generated.

Installation

You can install the released version of councilcount from GitHub

remotes::install_github("newyorkcitycouncil/councilcount")

Load Package

library(tidyverse)
# load last
library(councilcount)

Vignette

For demos of the functions included in councilcount, please visit vignettes/councilverse.Rmd.

Quick Start

First load the councilcount package as above.

Functions

R

councilcount includes 3 functions:

• get_bbl_estimates() – Generates a dataframe that provides population estimates at the BBL level (there are also columns for various other geographies, like council district, which can be used for geographic aggregation)
• get_geo_estimates() – Creates a dataframe that provides population estimates for selected demographic variables along chosen geographic boundaries (e.g. council district, borough, etc.) for a chosen ACS 5-Year survey
• get_ACS_variables() – Provides information on all of the available ACS demographic variables that can be accessed via get_geo_estimates() for a specified survey year

get_bbl_estimates() has 1 parameter:

• year – The desired year for BBL estimates. The years currently available are 2011, 2016, 2021, and 2022.

get_ACS_variables() has 1 parameter:

• acs_year – The end-year of the desired 5-Year ACS. The surveys currently available are 2007-2011, 2012-2016, 2017-2021, and 2018-2022.

get_geo_estimates() has 4 parameters:

• acs_year - The end-year of the desired 5-Year ACS. The surveys currently available are 2007-2011, 2012-2016, 2017-2021, and 2018-2022.
• geo – The desired geographic region. Please select from the following list:
  • Council Distrist: “councildist”
  • Community Distrist: “communitydist”
  • School District: “schooldist”
  • Police Precinct: “policeprct”
  • Neighborhood Tabulation Area: “nta”
  • Borough: “borough”
  • New York City: "city"
• var_codes – The desired demographic group(s), as represented by the ACS variable code. To access the list of available demographic variables and their codes, please run get_ACS_variables()
• boundary_year – If “councildist” is selected, the boundary year must be specified as 2013 or 2023. The default is 2023.

Here is an example, in which codes for “Female” and “Adults with Bachelor’s degree or higher” are used. The data is requested along 2023 Council District boundaries for the 2018-2022 ACS.

vars <- c('DP05_0003E', 'DP02_0068E')
get_geo_estimates(acs_year = "2022", geo = "councildist", var_codes = vars, boundary_year = "2023") 

Python

The equivalent functions are also available in Python. To access them, use the following code (Note: you must have the councilcount package downloaded on your computer):

import sys
my_path = 'INSERT PATH' # set absolute path to /councilcount/inst/python location (example: '/Users/jsmith/Desktop)
sys.path.insert(0, my_path + "/councilcount/inst/python/")
from retrieve_estimates import get_bbl_estimates, get_census_variables, get_geo_estimates

Data Sources

• The Five Year American Community Survey (ACS)
  • 2006-2011
  • 2012-2016
  • 2017-2021
  • 2018-2022
• Primary Land Use Tax Lot Output (PLUTO) datasets
  • 2011
  • 2016
  • 2021
  • 2022

Methodology

Estimates for over 100 ACS demographic variables were generated for the dashboard. Estimates are available at Council District, Community District, School District, Police Precinct, Neighborhood Tabulation Area, Borough, and New York City levels. CouncilCount utilizes the 5-Year ACS, meaning the data points presented on the dashboard represent 5-year averages for the listed demographic variables. Using the multiyear estimates increases the statistical reliability of the data, especially for small population subgroups and regions with low populations.

These estimates were generated using the 2007-2011, 2012-2016, 2017-2021, and 2018-2022 ACS 5-Year Estimates Data Profiles, which provide demographic estimates by census tract. Estimates for some geographies, like neighborhood tabulation areas, which are built from census tracts, were generated by directly aggregating census-tract-level data. However, this method does not work for geographies that have no relation to census tracts, like council districts and police precincts. In order to generate estimates for such geographies, ACS demographic data was synthesized with building data from the 2011, 2016, 2021, and 2022 PLUTO datasets to approximate the distribution of subpopulations around the city for each time period. Estimates for all geographies (except for council districts, for which a boundary year must be specified) are available along boundary lines as they were drawn in 2020, regardless of the period chosen, in order to make comparisons possible across time. For more information on the method used to generate the demographic estimates presented on CouncilCount, please contact [email protected].