A R script to convert Maryland open data on notice of intent to foreclose by zipcode from a wide to a long format and create basic visualizations. Data: https://opendata.maryland.gov/Housing/Maryland-Notices-of-Intent-to-Foreclose-by-Zip-Cod/ftsr-vapt

2022-07-20_noi-zip.R

library(dplyr)
library(ggplot2)
# pak::pkg_install("elipousson/mapmaryland")

plot_theme <- list(
  hrbrthemes::theme_ipsum_pub(base_size = 15),
  cols4all::scale_color_discrete_c4a_cat(palette = "tol.medium"),
  cols4all::scale_fill_discrete_c4a_cat(palette = "tol.medium")
)

plot_caption <-
  "Source: Maryland Office of the Commissioner of Financial Regulation (OCFR) /
  Maryland Open Data\n
Plot by @elipousson"

noi_zip <-
  mapmaryland::get_md_open_data(
    resource = "ftsr-vapt"
    )

md_zctas <-
  mapmaryland::get_md_tigris(
  type = "zctas",
  year = 2010
)

md_counties <-
  select(
    mapmaryland::md_counties,
    county_name = namelsad,
    countyfp,
    region
  )

md_zctas <- sf::st_join(md_zctas, md_counties, largest = TRUE)

noi_zip <-
  tidyr::pivot_longer(
  noi_zip,
  cols = starts_with("x"),
  names_to = "date",
  values_to = "count"
)

noi_zip_sf <-
  mutate(
    noi_zip,
    date = stringr::str_remove_all(date, "x_|t00_00_00_000"),
    date =  lubridate::ymd(stringr::str_replace_all(date, "_", "-")),
    date = dplyr::case_when(
      date >= lubridate::ymd("2022-07-21") ~ as.Date(date - lubridate::dyears(1)),
      TRUE ~ date
    )
  ) %>% 
  left_join(
    sf::st_drop_geometry(md_zctas),
    by = c("zip" = "zcta5ce10")
  )

ggplot(data = noi_zip_sf %>% filter(!is.na(county_name)), aes(x = date, y = as.integer(count), color = region)) +
  geom_line(alpha = 0.3, aes(group = zip), size = 0.8) +
  geom_point(alpha = 0.2, size = 1.6) +
  scale_x_date(minor_breaks = NULL, date_labels = "%b '%y") +
  labs(
   x = "",
    y = "Notices (#)",
    title = "Notice of intent to foreclose (NOI) in Maryland by zipcode",
    subtitle = "All regions of the state saw an increase between July '21 and June '22",
    caption = plot_caption
  ) +
  facet_wrap(~ region) +
  guides(color = "none") +
  plot_theme

noi_county_wide <-
  mapmaryland::get_md_open_data(
    resource = "w3bc-8mnv"
  )

noi_county <-
  noi_county_wide %>% 
  tidyr::pivot_longer(
    cols = ends_with(c("county", "city", "blank")),
    names_to = "county_name",
    values_to = "count"
  ) %>% 
  mutate(
    county_name = case_when(
      county_name == "blank" ~ "Missing",
      county_name == "baltimore_city" ~ "Baltimore city",
      TRUE ~ stringr::str_to_title(stringr::str_replace(county_name, "_", " "))
    ),
    date = lubridate::ymd(date),
    count = as.integer(count)
  ) %>% 
  left_join(mapmaryland::md_counties %>% select(county_name = namelsad, region) %>% sf::st_drop_geometry())

noi_region <-
  noi_county %>%
  filter(region != "Missing county",
         type == "Notice of Intent to Foreclose") %>% 
  group_by(date, region) %>% 
  summarise(
    count = sum(as.integer(count))
  )

ggplot(data = noi_region, aes(x = date, y = count, fill = region)) +
  geom_col(alpha = 0.8) +
  scale_x_date(minor_breaks = NULL, date_labels = "%b '%y") +
  labs(
    title = "Notices of intent to foreclose (NOI) in Maryland by region",
    y = "Notices (#)",
    x = "",
    caption = plot_caption
  ) +
  guides(fill = "none") +
  facet_wrap(~ region) +
  plot_theme