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CoDEC online data catalog

Source: R/codec_pins.R
codec_read.Rd

The CoDEC online data catalog is hosted on GitHub alongside the source code for this package.

  • Use codec_read() as a shortcut to read a CoDEC table into R as a codec_tbl object (see ?as_codec_tbl)

  • Use codec_list() as a shortcut to list available CoDEC table pins

  • codec_board() can be used to create a pin board object (see ?pins::pins) based on a specific version of the codec package

Usage

codec_read(name, board = codec_board())

codec_list(board = codec_board())

codec_board(
  version = paste0("v", utils::packageVersion("codec")),
  cache = NULL,
  use_cache_on_failure = rlang::is_interactive(),
  headers = NULL
)

Arguments

name

The name of the CoDEC table in the online CoDEC data catalog.

board

a pins board object; create with codec_board() to read from earlier versions of the catalog or to change the caching behavior of the pins package

version

specify a version of the online data catalog using a commit SHA, tag, or branch of geomarker-io/codec; syncs with the version of the installed package by default

cache

Cache path. Every board requires a local cache to avoid downloading files multiple times. The default stores in a standard cache location for your operating system, but you can override if needed.

use_cache_on_failure

If the pin fails to download, is it ok to use the last cached version? Defaults to is_interactive() so you'll be robust to poor internet connectivity when exploring interactively, but you'll get clear errors when the code is deployed.

headers

Named character vector for additional HTTP headers (such as for authentication). See connect_auth_headers() for Posit Connect support.

Value

For codec_read(), a codec_tbl object (see as_codec_tbl())

For codec_list(), a character vector CoDEC table names

For codec_board(), a pins_board object

Details

The pin for each CoDEC table has versions (see ?pins::pin_versions), but codec_board() can be used to specify a state of the online data catalog based on the version of the codec package. (See examples)

Examples

# list available CoDEC tables
codec_list()
#> [1] "acs_measures"                "crime"                      
#> [3] "drivetime"                   "environmental_justice_index"
#> [5] "landcover"                   "parcel"                     
#> [7] "property_code_enforcements"  "traffic"                    

# read a CoDEC table and inspect its metadata
d <- codec_read("traffic")
head(d)
#> # A tibble: 6 × 5
#>   census_tract_id_2020 aadtm_trucks_buses aadtm_tractor_trailer aadtm_passenger
#>   <chr>                             <dbl>                 <dbl>           <dbl>
#> 1 39061005200                          0                     0               0 
#> 2 39061026200                   53551460.            207033030.     1108175821.
#> 3 39061023901                   27090895.             39769940.      621615559.
#> 4 39061023701                          0                     0               0 
#> 5 39061010500                          0                     0               0 
#> 6 39061020501                   23210991.             50060424.      556823936.
#> # ℹ 1 more variable: year <int>
attr(d, "title")
#> [1] "Average Annual Vehicle-Meters Driven"
message(attr(d, "description"))
#> # Average Annual Vehicle-Meters Driven
#> 
#> ## About
#> 
#> AADT stands for **A**verage **A**nual **D**aily **T**raffic.
#> Aggregated at the census tract-level, AADT is measured in vehicle-meter counts (`aadtm`) and grouped by class (`passenger`, `trucks_buses`, `tractor_trailer`).
#> 
#> Data is downloaded from the 2020 Highway Performance Monitoring System (HPMS) geodatabase hosted by ESRI using the {[appc](https://github.com/geomarker-io/appc)} package for R.
#> For more details about the HPMS, see:
#> 
#> - <https://www.fhwa.dot.gov/policyinformation/hpms.cfm>
#> - <https://data-usdot.opendata.arcgis.com/datasets/usdot::highway-performance-monitoring-system-hpms-2020/about>
#> - <https://www.fhwa.dot.gov/policyinformation/hpms/fieldmanual/hpms_field_manual_dec2016.pdf>
#> 
#> ## Data
#> 
#> Only roads with `F_SYSTEM` classification of 1 ("interstate") or 2 ("principal arterial - other freeways and expressways") are used.
#> Passenger vehicles (FHWA 1-3) are calculated as the total minus FHWA class 4-7 (single unit) and 8-13 (combo).
#> 
#> For each 2020 census tract geography, sum the class-specific AADT for all intersecting roads, weighted by their intersecting lengths.

# change the defaults for codec_board() to read from older versions of the board
codec_board() |>
  pins::pin_versions("crime")
#> # A tibble: 5 × 3
#>   version                created             hash 
#>   <chr>                  <dttm>              <chr>
#> 1 20250829T181659Z-bf502 2025-08-29 18:16:59 bf502
#> 2 20250831T023010Z-bf502 2025-08-31 02:30:10 bf502
#> 3 20250901T033049Z-bf502 2025-09-01 03:30:49 bf502
#> 4 20250902T005725Z-bf502 2025-09-02 00:57:25 bf502
#> 5 20250902T182616Z-91afb 2025-09-02 18:26:16 91afb
codec_board("v3.0.0-rc1") |>
  pins::pin_versions("crime")
#> # A tibble: 4 × 3
#>   version                created             hash 
#>   <chr>                  <dttm>              <chr>
#> 1 20250829T181659Z-bf502 2025-08-29 18:16:59 bf502
#> 2 20250831T023010Z-bf502 2025-08-31 02:30:10 bf502
#> 3 20250901T033049Z-bf502 2025-09-01 03:30:49 bf502
#> 4 20250902T005725Z-bf502 2025-09-02 00:57:25 bf502