NYC Affordable Housing Production Summary
Yuyan Lin
2026-09-13
This report analyzes affordable housing production data. The data are from NYC Open Data and are provided by the New York City Department of Housing Preservation and Development (HPD).
# Import the NYC affordable housing data from the CSV file.
housing <- readr::read_csv("affordable_housing.csv",show_col_types = FALSE)
# Display the first six rows of the dataset.
head(housing)## # A tibble: 6 × 41
## `Project ID` `Project Name` `Project Start Date` Project Completion D…¹
## <dbl> <chr> <chr> <chr>
## 1 75917 HOUSING PLUS. 729 VA… 03/31/2026 <NA>
## 2 76580 1692/1702/1706 UNION… 03/31/2026 03/31/2026
## 3 76580 1692/1702/1706 UNION… 03/31/2026 03/31/2026
## 4 77723 431 CONCORD AVENUE 03/31/2026 <NA>
## 5 78451 CONFIDENTIAL 03/31/2026 <NA>
## 6 77166 BERGEN WYCKOFF 03/30/2026 <NA>
## # ℹ abbreviated name: ¹`Project Completion Date`
## # ℹ 37 more variables: `Building ID` <dbl>, Number <chr>, Street <chr>,
## # Borough <chr>, Postcode <dbl>, BBL <dbl>, BIN <dbl>,
## # `Community Board` <chr>, `Council District` <dbl>, `Census Tract` <dbl>,
## # `NTA - Neighborhood Tabulation Area` <chr>, Latitude <dbl>,
## # Longitude <dbl>, `Latitude (Internal)` <dbl>, `Longitude (Internal)` <dbl>,
## # `Building Completion Date` <chr>, `Reporting Construction Type` <chr>, …# Check the number of rows and columns
dim(housing)## [1] 9250 41# Review the Column Names
names(housing)## [1] "Project ID" "Project Name"
## [3] "Project Start Date" "Project Completion Date"
## [5] "Building ID" "Number"
## [7] "Street" "Borough"
## [9] "Postcode" "BBL"
## [11] "BIN" "Community Board"
## [13] "Council District" "Census Tract"
## [15] "NTA - Neighborhood Tabulation Area" "Latitude"
## [17] "Longitude" "Latitude (Internal)"
## [19] "Longitude (Internal)" "Building Completion Date"
## [21] "Reporting Construction Type" "Extended Affordability Only"
## [23] "Prevailing Wage Status" "Extremely Low Income Units"
## [25] "Very Low Income Units" "Low Income Units"
## [27] "Moderate Income Units" "Middle Income Units"
## [29] "Other Income Units" "Studio Units"
## [31] "1-BR Units" "2-BR Units"
## [33] "3-BR Units" "4-BR Units"
## [35] "5-BR Units" "6-BR+ Units"
## [37] "Unknown-BR Units" "Counted Rental Units"
## [39] "Counted Homeownership Units" "All Counted Units"
## [41] "Total Units"# Summary Statistics for Total Units
# Calculate the mean Total Units
mean(housing$`Total Units`, na.rm = TRUE)## [1] 47.1213# Calculate the median Total Units
median(housing$`Total Units`, na.rm = TRUE)## [1] 12# Calculate the standard deviation of Total Units.
sd(housing$`Total Units`, na.rm = TRUE)## [1] 92.66828# Rental and Homeownership Units
# Counted Rental Units
summary(housing$`Counted Rental Units`)## Min. 1st Qu. Median Mean 3rd Qu. Max. NAs
## 1.00 5.00 13.00 37.55 41.00 917.00 2526# Counted Homeownership Units
summary(housing$`Counted Homeownership Units`)## Min. 1st Qu. Median Mean 3rd Qu. Max. NAs
## 1.00 1.00 1.00 22.87 2.00 489.00 6609# Bedroom Units
# Calculate summary statistics for One-Bedroom Units
summary(housing$`1-BR Units`)## Min. 1st Qu. Median Mean 3rd Qu. Max. NAs
## 1.00 2.00 6.00 19.13 21.00 312.00 3313# Calculate summary statistics for Two-Bedroom Units
summary(housing$`2-BR Units`)## Min. 1st Qu. Median Mean 3rd Qu. Max. NAs
## 1.00 2.00 7.00 17.65 18.00 305.00 3391# Calculate summary statistics for three-bedroom units
summary(housing$`3-BR Units`)## Min. 1st Qu. Median Mean 3rd Qu. Max. NAs
## 1.00 1.00 4.00 10.41 11.00 193.00 5917New York City has five boroughs: Bronx, Brooklyn, Manhattan, Queens, and Staten Island. # Housing Units by Borough
# Count the number of buildings in each borough
table(housing$Borough)##
## Bronx Brooklyn Manhattan Queens Staten Island
## 2502 3593 1449 1268 438# Calculate the average Total Units by Borough
borough_summary <- housing |> dplyr::group_by(Borough) |> dplyr::summarise( Average_Total_Units = mean(`Total Units`, na.rm = TRUE))
borough_summary## # A tibble: 5 × 2
## Borough Average_Total_Units
## <chr> <dbl>
## 1 Bronx 47.1
## 2 Brooklyn 39.5
## 3 Manhattan 73.1
## 4 Queens 49.8
## 5 Staten Island 15.8The results show that Manhattan has the highest average number of total housing units per building, while Staten Island has the lowest average. The bar chart below provides a visual comparison of the five boroughs.
# Create a bar chart comparing average total units by borough
ggplot2::ggplot(borough_summary,ggplot2::aes(x = Borough, y = Average_Total_Units)) + ggplot2::geom_col() + ggplot2::labs( title = "Average Total Housing Units by Borough", x = "Borough", y = "Average Total Units")
Data Source
New York City Department of Housing Preservation and Development (HPD). “Affordable Housing Production by Building”. NYC Open Data.