nycomplaints 
by many NYC Council district offices to enter and track constituent cases that can range from issues around affordable housing, to potholes and pedestrian safety. This dataset aggregates the information that individual staff have input. However, district staffs handle a wide range of complex issues. Each offices uses the program differently, and thus records cases, differently and so comparisons between accounts may be difficult. Not all offices use the program. For more info - http://labs.council.nyc/districts/data/
This is a teaching package; the data are not clean—in particular there are spurious zip codes in the complaints data, as well as other issues.
Data sourced from NYC Open Data
The package also includes nyzip_demog and census_vars. The former is
a table of five-year ACS estimates of some demographic features by ZCTA.
The latter is a table showing the specific Census Bureau variables used
to construct the demographic table.
Installation
You can install nycomplaints from GitHub with:
remotes::install_github("kjhealy/nycomplaints@main")Loading the Data
library(tidyverse) # Optional but strongly recommended
library(nycomplaints)
nycomplaints
#> # A tibble: 240,027 × 11
#> unique_key account opendate closedate complaint_type descriptor zip
#> <chr> <chr> <date> <date> <chr> <chr> <chr>
#> 1 NYCC01506329 NYCC01 2015-01-02 2015-01-14 Aging Senior Ce… 11220
#> 2 NYCC01506331 NYCC01 2015-01-04 2016-03-25 Aging <NA> 11373
#> 3 NYCC01506332 NYCC01 2015-01-04 2016-03-25 Aging <NA> 11373
#> 4 NYCC01506333 NYCC01 2015-01-04 2017-02-23 Health Rats/Rode… 10006
#> 5 NYCC01506334 NYCC01 2015-01-05 2015-01-15 Land Use and Zon… <NA> 10003
#> 6 NYCC01506335 NYCC01 2015-01-06 2016-02-09 Transportation Pot Holes 10002
#> 7 NYCC01506338 NYCC01 2015-01-06 2015-03-17 Transportation Parking P… 10002
#> 8 NYCC01506342 NYCC01 2015-01-08 2015-01-08 Economy/Jobs Business … 11355
#> 9 NYCC01506343 NYCC01 2015-01-08 2015-01-08 Immigration Visas 10002
#> 10 NYCC01506345 NYCC01 2015-01-08 2015-01-08 Housing and Buil… Seeking a… 10013
#> # ℹ 240,017 more rows
#> # ℹ 4 more variables: borough <chr>, city <chr>, council_dist <chr>,
#> # community_board <chr>
nyzip_demog
#> # A tibble: 68 × 10
#> zip population white_alone black_alone asian_alone two_or_more_races
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 10001 26966 16963 2117 4527 2178
#> 2 10002 76807 24687 6453 30288 5880
#> 3 10003 54447 38481 2823 9110 2967
#> 4 10004 4795 2758 162 1593 262
#> 5 10005 8637 6496 147 1180 535
#> 6 10006 3894 2526 255 895 150
#> 7 10007 8194 6173 736 1064 78
#> 8 10009 60000 34924 4577 7995 5469
#> 9 10010 33193 22952 2952 4955 1491
#> 10 10011 51867 38919 2322 4854 3795
#> # ℹ 58 more rows
#> # ℹ 4 more variables: hispanic <dbl>, nonhispanic_white <dbl>,
#> # nonhispanic_black <dbl>, med_hhinc <dbl>
census_vars
#> # A tibble: 9 × 2
#> variable varname
#> <chr> <chr>
#> 1 B01001_001 population
#> 2 B02001_002 white_alone
#> 3 B02001_003 black_alone
#> 4 B02001_005 asian_alone
#> 5 B02001_008 two_or_more_races
#> 6 B03003_001 hispanic
#> 7 B03002_003 nonhispanic_white
#> 8 B03002_004 nonhispanic_black
#> 9 B19013_001 med_hhinc