hercgeos

The goal of hercgeos is to make it a little easier and more efficient to work with spatial data from the US Census and related sources.

Installation

You can install the development version of hercgeos from GitHub with:

# install.packages("devtools")
devtools::install_github("higherX4Racine/hercgeos")

Example

The fresh-from-the-servers TIGER/Line® shapefiles have decennial-census-specific column names. hercgeos helps with this.

library(hercgeos)
NASHVILLE_NH |>
    purrr::discard_at("historic_district") |>
    purrr::map(names) |>
    tibble::enframe(name = "Layer", value = "Names") |>
    knitr::kable(caption = "Original column names")

Layer	Names
blocks	STATEFP20 , COUNTYFP20, TRACTCE20 , BLOCKCE20 , GEOID20 , NAME20 , MTFCC20 , UR20 , UACE20 , UATYPE20 , FUNCSTAT20, ALAND20 , AWATER20 , INTPTLAT20, INTPTLON20, HOUSING20 , POP20 , geometry
tracts	STATEFP , COUNTYFP, TRACTCE , GEOID , NAME , NAMELSAD, MTFCC , FUNCSTAT, ALAND , AWATER , INTPTLAT, INTPTLON, geometry

Original column names

NASHVILLE_NH |>
    purrr::discard_at("historic_district") |>
    purrr::map(fix_old_year_suffixes) |>
    purrr::map(names) |>
    tibble::enframe(name = "Layer", value = "Names") |>
    knitr::kable(caption = "Repaired column names")

Layer	Names
blocks	STATEFP , COUNTYFP, TRACTCE , BLOCKCE , GEOID , NAME , MTFCC , UR , UACE , UATYPE , FUNCSTAT, ALAND , AWATER , INTPTLAT, INTPTLON, HOUSING , POP , geometry
tracts	STATEFP , COUNTYFP, TRACTCE , GEOID , NAME , NAMELSAD, MTFCC , FUNCSTAT, ALAND , AWATER , INTPTLAT, INTPTLON, geometry

Repaired column names

There are also some nice presets for mapping

ggplot2::ggplot() +
    geom_terrain(
        NASHVILLE_NH$blocks |>
            fix_old_year_suffixes() |>
            fix_latlong_to_numeric() |>
            transform_tiger_to_utm() |>
            dplyr::mutate(
                Terrain = terrain_factor(.data$UR,
                                         .data$AWATER,
                                         .data$ALAND)
            )
    ) +
    ggplot2::geom_sf(
        data = NASHVILLE_NH$tracts |>
            fix_latlong_to_numeric() |>
            transform_tiger_to_utm(),
        fill = NA,
        color = "#ff2222",
        linewidth = ggplot2::rel(2)
    ) +
    ggplot2::theme_minimal()