diff --git a/.Rbuildignore b/.Rbuildignore
index c075fb6f..e0e82b6a 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -11,5 +11,4 @@
index.md
justfile
^vignettes/articles$
-^assets$
^data-raw$
diff --git a/DESCRIPTION b/DESCRIPTION
index 73179264..08c2b9fc 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: codec
Title: Community Data Explorer for Cincinnati
-Version: 3.0.0
+Version: 3.1.0.9000
Authors@R: c(
person("Cole", "Brokamp",
email = "cole.brokamp@gmail.com",
@@ -16,12 +16,22 @@ Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Suggests:
+ base64enc,
+ bslib,
+ crosstalk,
testthat (>= 3.0.0),
+ DT,
devtools,
+ htmltools,
+ leaflet,
+ markdown,
+ plotly,
roxygen2,
rmarkdown,
dpkg,
- knitr
+ knitr,
+ shiny,
+ writexl
Config/testthat/edition: 3
URL: https://geomarker.io/codec
BugReports: https://github.com/geomarker-io/codec/issues
@@ -29,6 +39,7 @@ Imports:
rlang,
tidyselect,
stringr,
+ scales,
glue,
here,
pins,
diff --git a/R/CoDEC-package.R b/R/CoDEC-package.R
index 48d0081b..fcf54299 100644
--- a/R/CoDEC-package.R
+++ b/R/CoDEC-package.R
@@ -1,12 +1,19 @@
#' About the CoDEC package
#'
#' @description
-#' The CoDEC data package specifications provide a set of patterns designed to make sharing tabular community-level data easier.
-#' Examples of this type of data include the pediatric hospitalization rate per month per census tract, the total number of gunshots per season per neighborhood, and the housing code enforcement density per year per ZIP code.
+#' The CoDEC data package specifications provide a set of patterns designed
+#' to make sharing tabular community-level data easier.
#'
-#' Data is specified as average values or total counts for census tract geographies during a specific year (or year and month).
-#' The required **census tract identifer** and **year** (or *year* and *month*)
-#' columns in a CoDEC table contain the spatiotemporal information that can be used to link other data.
+#' Examples of this type of data include the pediatric hospitalization rate
+#' per month per census tract, the total number of gunshots per season per
+#' neighborhood, and the housing code enforcement density per year per ZIP
+#' code.
+#'
+#' Data is specified as average values or total counts for census tract
+#' geographies during a specific year (or year and month).
+#' The required **census tract identifer** and **year** (or *year* and
+#' *month*) columns in a CoDEC table contain the spatiotemporal information
+#' that can be used to link other data.
#'
#' @keywords internal
"_PACKAGE"
diff --git a/R/cincy_geographies.R b/R/cincy_geographies.R
index 8b42ff3f..392a3bf2 100644
--- a/R/cincy_geographies.R
+++ b/R/cincy_geographies.R
@@ -17,17 +17,18 @@ tiger_download <- function(x) {
#' Cincy census tracts and block groups
#'
#' Read tract and block group ("bg") geographies from the online Census
-#' [TIGER/Line](https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html)
-#' files into R
+#' TIGER/Line files into R.
#' @param geography which type of cincy census geography to return
-#' @param vintage a character vector of a year corresponding to the vintage of TIGER/Line data
-#' @param packaged logical; use the data included with the package instead of (down)loading
-#' from the source data?
+#' @param vintage a character vector of a year corresponding to the
+#' vintage of TIGER/Line data
+#' @param packaged logical; use the data included with the package instead
+#' of (down)loading from the source data?
#' @details
-#' Compressed shapefiles are downloaded from TIGER into an R user data directory and will be cached
-#' for use across other R sessions (see `?dpkg::stow` for more details).
-#' @returns a simple features object with a geographic identifier column (`geoid`)
-#' and a geometry column (`s2_geography`)
+#' Compressed shapefiles are downloaded from TIGER into an R user data
+#' directory and will be cached for use across other R sessions (see
+#' `?dpkg::stow` for more details).
+#' @returns a simple features object with a geographic identifier column
+#' (`geoid`) and a geometry column (`s2_geography`)
#' @export
#' @examples
#' cincy_census_geo("tract", "2020")
@@ -68,13 +69,13 @@ cincy_census_geo <- function(
#' This installs the CAGIS Open Data GIS database (`.gdb`) into the data
#' directory for the codec package. Once downloaded, it will be reused
#' across R sessions on the same computer.
-#' The geodatabase contains many
-#' [layers](https://www.cagis.org/Opendata/Quarterly_GIS_Data/OpenData_Layer_List.txt) that are
-#' updated quarterly. (Historical geodatabases are not available here.)
-#' @seealso This function is called by `cincy_neighborhood_geo()`, `cincy_city_geo()`
-#' and others that import individual layers.
-#' @param cagis_data_url the url to the CAGIS Open Data .gdb.zip file; this changes quarterly, so
-#' [check](https://www.cagis.org/Opendata/Quarterly_GIS_Data) for something more recent if the file cannot be found
+#' The geodatabase contains many layers that are updated quarterly.
+#' Historical geodatabases are not available here.
+#' @seealso This function is called by `cincy_neighborhood_geo()` and
+#' `cincy_city_geo()`, plus other functions that import individual layers.
+#' @param cagis_data_url the url to the CAGIS Open Data .gdb.zip file; this
+#' changes quarterly, so check the CAGIS Open Data page for something more
+#' recent if the file cannot be found.
#' @export
#' @examples
#' \dontrun{
@@ -101,21 +102,31 @@ install_cagis_data <- function(
#' Cincy address geographies
#'
-#' CAGIS data (see `install_cagis_data()`) provides a list of all addresses in Hamilton County.
-#' The s2 cell is derived from LONGITUDE and LATITUDE fields in CAGIS address database.
+#' CAGIS data (see `install_cagis_data()`) provides a list of all addresses
+#' in Hamilton County.
+#' The s2 cell is derived from LONGITUDE and LATITUDE fields in the CAGIS
+#' address database.
#' @details
-#' This function previously excluded addresses with type milemarker (`MM`), park (`PAR`),
-#' infrastructure project (`PRJ`), cell tower (`CTW`), vacant or commercial lot (`LOT`),
-#' and other miscellaneous non-residential addresses (`MIS`, `RR`, `TBA`).
+#' This function previously excluded addresses with type milemarker (`MM`),
+#' park (`PAR`), infrastructure project (`PRJ`), cell tower (`CTW`),
+#' vacant or commercial lot (`LOT`), and other miscellaneous non-residential
+#' addresses (`MIS`, `RR`, `TBA`).
#' Now that they are included, see the examples for how to filter these out.
-#' @param packaged logical; use the data included with the package instead of (down)loading
-#' from the source data?
-#' @return a simple features object with columns `cagis_address`, `cagis_address_place`, `cagis_address_type`,
-#' `cagis_s2`, `cagis_parcel_id`, `cagis_is_condo`, and a geometry column (`s2_geography`)
+#' @param packaged logical; use the data included with the package instead
+#' of (down)loading from the source data?
+#' @return a simple features object with columns `cagis_address`,
+#' `cagis_address_place`, `cagis_address_type`, `cagis_s2`,
+#' `cagis_parcel_id`, `cagis_is_condo`, and a geometry column
+#' (`s2_geography`)
#' @export
#' @examples
#' cincy_addr_geo() |>
-#' dplyr::filter(!cagis_address_type %in% c("MM", "PAR", "PRJ", "CTW", "LOT", "MIS", "RR", "TBA"))
+#' dplyr::filter(
+#' !cagis_address_type %in% c(
+#' "MM", "PAR", "PRJ", "CTW",
+#' "LOT", "MIS", "RR", "TBA"
+#' )
+#' )
cincy_addr_geo <- function(packaged = TRUE) {
if (packaged) {
out <- get("cincy_addr_geo_2025", asNamespace("codec"), inherits = FALSE) |>
@@ -142,15 +153,17 @@ cincy_addr_geo <- function(packaged = TRUE) {
#' Cincy neighborhood geographies
#'
-#' CAGIS data (see `install_cagis_data()`) provides community council boundaries, but these boundaries can
-#' overlap and do not align with census geographies or ZIP codes.
-#' By default, the statistical neighborhood approximations are instead returned,
-#' which are calculated by aggregating census tracts into 50 matching neighborhoods.
+#' CAGIS data (see `install_cagis_data()`) provides community council
+#' boundaries, but these boundaries can overlap and do not align with
+#' census geographies or ZIP codes.
+#' By default, the statistical neighborhood approximations are instead
+#' returned, which are calculated by aggregating census tracts into 50
+#' matching neighborhoods.
#' @param geography which type of cincy neighborhood geography to return
-#' @param packaged logical; use the data included with the package instead of (down)loading
-#' from the source data?
-#' @returns a simple features object with a geographic identifier column (`geoid`)
-#' and a geometry column (`s2_geography`)
+#' @param packaged logical; use the data included with the package instead
+#' of (down)loading from the source data?
+#' @returns a simple features object with a geographic identifier column
+#' (`geoid`) and a geometry column (`s2_geography`)
#' @export
#' @examples
#' cincy_neighborhood_geo()
@@ -196,17 +209,15 @@ cincy_city_geo <- function() {
#' Cincy ZIP Code Tabulation Areas
#'
-#' Read [ZIP Code Tabulation Areas
-#' (ZCTAs)](https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html)
-#' geographies from the online Census
-#' [TIGER/Line](https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html)
-#' files into R
-#' @param vintage a character vector of a year corresponding to the vintage of TIGER/Line data
-#' @param packaged logical; use the data included with the package instead of (down)loading
-#' from the source data?
+#' Read ZIP Code Tabulation Areas (ZCTAs) geographies from the online Census
+#' TIGER/Line files into R.
+#' @param vintage a character vector of a year corresponding to the
+#' vintage of TIGER/Line data
+#' @param packaged logical; use the data included with the package instead
+#' of (down)loading from the source data?
#' @export
-#' @returns a simple features object with a geographic identifier column (`geoid`)
-#' and a geometry column (`s2_geography`)
+#' @returns a simple features object with a geographic identifier column
+#' (`geoid`) and a geometry column (`s2_geography`)
#' @examples
#' cincy_zcta_geo("2020")
cincy_zcta_geo <- function(vintage = as.character(2024:2013), packaged = TRUE) {
diff --git a/R/codec_design.R b/R/codec_design.R
index 03e11427..002dff01 100644
--- a/R/codec_design.R
+++ b/R/codec_design.R
@@ -1,5 +1,6 @@
#' CoDEC colors
-#' @param n a numeric vector of color numbers or character vector of color names; if NULL returns named vector of available colors
+#' @param n a numeric vector of color numbers or character vector of color
+#' names; if NULL returns named vector of available colors
#' @export
#' @examples
#' plot(1:8, rep(1, 8), col = codec_colors(1:8),
@@ -16,6 +17,8 @@ codec_colors <- function(n = NULL) {
"orange" = "#E49865",
"red" = "#C28273"
)
- if (!is.null(n)) return(codec_col[n])
+ if (!is.null(n)) {
+ return(codec_col[n])
+ }
return(codec_col)
}
diff --git a/R/codec_explorer.R b/R/codec_explorer.R
new file mode 100644
index 00000000..d189b6dd
--- /dev/null
+++ b/R/codec_explorer.R
@@ -0,0 +1,240 @@
+# Internal helpers shared by the CoDEC explorer app and data catalog article.
+
+codec_explorer_base_url <- function() {
+ option_url <- getOption("codec.explorer_url", "")
+ env_url <- Sys.getenv("CODEC_EXPLORER_URL", unset = "")
+
+ if (nzchar(option_url)) {
+ return(option_url)
+ }
+
+ if (nzchar(env_url)) {
+ return(env_url)
+ }
+
+ "https://019d3edf-7a64-545d-7539-fdd676fba3f0.share.connect.posit.cloud"
+}
+
+codec_explorer_defaults <- function() {
+ list(
+ x = "prop_poverty",
+ y = "median_home_value",
+ geography = "tract_2020",
+ view = "bivariate",
+ focus = "map"
+ )
+}
+
+codec_explorer_url <- function(
+ x = NULL,
+ y = NULL,
+ geography = NULL,
+ view = NULL,
+ focus = NULL
+) {
+ defaults <- codec_explorer_defaults()
+ params <- list(
+ x = if (is.null(x)) defaults$x else x,
+ y = if (is.null(y)) defaults$y else y,
+ geography = if (is.null(geography)) defaults$geography else geography,
+ view = if (is.null(view)) defaults$view else view,
+ focus = if (is.null(focus)) defaults$focus else focus
+ )
+
+ query <-
+ paste0(
+ names(params),
+ "=",
+ vapply(params, utils::URLencode, character(1), reserved = TRUE),
+ collapse = "&"
+ )
+
+ paste0(codec_explorer_base_url(), "?", query)
+}
+
+codec_explorer_partner_field <- function(field) {
+ defaults <- codec_explorer_defaults()
+ if (identical(field, defaults$y)) {
+ return(defaults$x)
+ }
+ defaults$y
+}
+
+codec_explorer_field_label <- function(field) {
+ field
+}
+
+codec_explorer_field_format <- function(field) {
+ if (
+ grepl(
+ "^(prop_|prcnt_|fraction_)",
+ field
+ ) ||
+ grepl("mean_pct_", field)
+ ) {
+ return("percent")
+ }
+
+ if (grepl("home_value|market_total_value|online_market_total_value", field)) {
+ return("currency")
+ }
+
+ if (grepl("year_built$|^year$", field)) {
+ return("year")
+ }
+
+ if (grepl("^(n_|aadtm_)", field)) {
+ return("count")
+ }
+
+ "number"
+}
+
+codec_explorer_field_value <- function(x, field) {
+ fmt <- codec_explorer_field_format(field)
+ out <- rep("NA", length(x))
+ keep <- !is.na(x)
+
+ if (!any(keep)) {
+ return(out)
+ }
+
+ if (fmt == "percent") {
+ out[keep] <- scales::label_percent(accuracy = 0.1)(x[keep])
+ return(out)
+ }
+
+ if (fmt == "currency") {
+ out[keep] <- scales::label_dollar(accuracy = 1)(x[keep])
+ return(out)
+ }
+
+ if (fmt == "year") {
+ out[keep] <- format(round(x[keep]), trim = TRUE)
+ return(out)
+ }
+
+ if (fmt == "count") {
+ out[keep] <- scales::label_number(accuracy = 1, big.mark = ",")(x[keep])
+ return(out)
+ }
+
+ out[keep] <- scales::label_number(accuracy = 0.1, big.mark = ",")(x[keep])
+ out
+}
+
+codec_latest_annual_fields <- function() {
+ board <- codec_board_local()
+ latest_annual <- codec_latest_annual
+ fields <- setdiff(names(latest_annual), c("census_tract_id_2020", "year"))
+
+ source_lookup <-
+ lapply(codec_list(board), function(name) {
+ table <- codec_read(name, board = board)
+ tibble::tibble(
+ field = setdiff(
+ names(table),
+ c("census_tract_id_2010", "census_tract_id_2020", "year", "month")
+ ),
+ source_table = name,
+ source_title = attr(table, "title"),
+ source_description = attr(table, "description")
+ )
+ }) |>
+ dplyr::bind_rows() |>
+ dplyr::distinct(field, .keep_all = TRUE)
+
+ tibble::tibble(
+ field = fields,
+ label = vapply(fields, codec_explorer_field_label, character(1)),
+ format = vapply(fields, codec_explorer_field_format, character(1)),
+ is_numeric = vapply(latest_annual[fields], is.numeric, logical(1))
+ ) |>
+ dplyr::left_join(source_lookup, by = "field") |>
+ dplyr::mutate(
+ source_table = dplyr::case_when(
+ !is.na(source_table) ~ source_table,
+ grepl("crime|shoot|shots_fired", field) ~ "public_safety",
+ TRUE ~ "derived_latest_annual"
+ ),
+ source_title = dplyr::case_when(
+ !is.na(source_title) ~ source_title,
+ source_table == "public_safety" ~ "Public safety measures",
+ TRUE ~ "Derived latest annual measures"
+ ),
+ source_description = dplyr::case_when(
+ !is.na(source_description) ~ source_description,
+ source_table == "public_safety" ~ "Crime and shooting measures included in the harmonized annual explorer.",
+ TRUE ~ "Field included in the harmonized annual explorer but not directly traced to a single source table."
+ ),
+ choice_label = ifelse(
+ is.na(source_title),
+ label,
+ paste0(label, " - ", source_title)
+ )
+ ) |>
+ dplyr::arrange(source_table, field)
+}
+
+codec_explorer_dataset_choices <- function() {
+ codec_latest_annual_fields() |>
+ dplyr::distinct(source_table, source_title, source_description) |>
+ dplyr::filter(source_table != "derived_latest_annual") |>
+ dplyr::arrange(source_table)
+}
+
+codec_explorer_geography_choices <- function() {
+ dplyr::bind_rows(
+ tibble::tibble(
+ geography = "tract_2020",
+ family = "tract",
+ geography_arg = "tract",
+ vintage = "2020",
+ neighborhood_type = NA_character_,
+ label = "tract 2020"
+ ),
+ tibble::tibble(
+ geography = "zcta_2020",
+ family = "zcta",
+ geography_arg = "zcta",
+ vintage = "2020",
+ neighborhood_type = NA_character_,
+ label = "zcta 2020"
+ ),
+ tibble::tibble(
+ geography = c(
+ "neighborhood_statistical_neighborhood_approximations",
+ "neighborhood_community_council"
+ ),
+ family = "neighborhood",
+ geography_arg = "neighborhood",
+ vintage = NA_character_,
+ neighborhood_type = c(
+ "statistical_neighborhood_approximations",
+ "community_council"
+ ),
+ label = c(
+ "neighborhood statistical_neighborhood_approximations",
+ "neighborhood community_council"
+ )
+ )
+ )
+}
+
+codec_explorer_normalize_geography <- function(geography) {
+ if (is.null(geography) || !nzchar(geography)) {
+ return(codec_explorer_defaults()$geography)
+ }
+
+ legacy_lookup <- c(
+ tract = "tract_2020",
+ zcta = "zcta_2020",
+ neighborhood = "neighborhood_statistical_neighborhood_approximations"
+ )
+
+ if (geography %in% names(legacy_lookup)) {
+ return(legacy_lookup[[geography]])
+ }
+
+ geography
+}
diff --git a/R/codec_interpolate.R b/R/codec_interpolate.R
index b25884a9..2ab403b5 100644
--- a/R/codec_interpolate.R
+++ b/R/codec_interpolate.R
@@ -1,11 +1,13 @@
#' Coerce a CoDEC data table into a simple features object
#'
-#' The name of the census tract column in the CoDEC data table is used to add
-#' the appropriate census tract s2 geography column.
+#' The name of the census tract column in the CoDEC data table is used to
+#' add the appropriate census tract s2 geography column.
#' @param x a CoDEC data table
-#' @details Tract identifers do not change across decennial censuses, but the digital representation of their boundaries
-#' may be improved over time. Here, data tables using 2010 tract identifers use the TIGER/Line 2019 tract shapefiles
-#' and data tables using 2020 tract identifiers use the TIGER/Line 2020 tract shapefiles
+#' @details Tract identifiers do not change across decennial censuses, but
+#' the digital representation of their boundaries may be improved over time.
+#' Here, data tables using 2010 tract identifiers use the TIGER/Line 2019
+#' tract shapefiles and data tables using 2020 tract identifiers use the
+#' TIGER/Line 2020 tract shapefiles.
#' @returns a simple features object with a geometry column (`s2_geography`)
#' in addition to the columns in `x`
#' @export
@@ -31,33 +33,37 @@ codec_as_sf <- function(x) {
}
get_codec_tract_id_name <- function(x) {
- if (!inherits(x, "codec_tbl")) {
- rlang::abort("x must be a CoDEC data package")
+ codec_tract_id_names <- paste0("census_tract_id", c("_2010", "_2020"))
+ codec_tract_id_name <- codec_tract_id_names[
+ codec_tract_id_names %in% names(x)
+ ]
+ if (length(codec_tract_id_name) != 1) {
+ rlang::abort(
+ "x must contain exactly one census tract id column named `census_tract_id_2010` or `census_tract_id_2020`"
+ )
}
- ifelse(
- any(grepl("census_tract_id_2010", names(x), fixed = TRUE)),
- "census_tract_id_2010",
- "census_tract_id_2020"
- )
+ codec_tract_id_name
}
#' Spatially interpolate community-level data
#'
-#' Census block-level weights are used to spatially interpolate CoDEC data packages from the census tract-level
-#' to other Cincy geographies.
+#' Census block-level weights are used to spatially interpolate CoDEC data
+#' packages from the census tract-level to other Cincy geographies.
#' @param from a CoDEC data package
-#' @param to A simple features object returned by one of the `cincy_*_geo()` functions
-#' (i.e., `cincy_census_geo()`, `cincy_neighborhood_geo()`, or cincy_zcta_geo()`)
+#' @param to A simple features object returned by one of the
+#' `cincy_*_geo()` functions (for example `cincy_census_geo()`,
+#' `cincy_neighborhood_geo()`, or `cincy_zcta_geo()`)
#' @param weights which census block-level weights to use; see details
-#' @returns a tibble with a new geographic identifier column for the `to` target geography (`geoid`)
-#' in addition to the (interpolated) columns in `from`
+#' @returns a tibble with a new geographic identifier column for the `to`
+#' target geography (`geoid`) in addition to the interpolated columns in `from`
#' @details
-#' Block-level total population (`pop`), total number of homes (`homes`), or total land area (`area`)
-#' from the 2020 Census can be chosen to use for the weights.
+#' Block-level total population (`pop`), total number of homes (`homes`), or
+#' total land area (`area`) from the 2020 Census can be chosen to use for the
+#' weights.
#' Geospatial intersection happens after transforming geographies to epsg:5072.
#' See `codec_as_sf()` for adding geography to a CoDEC data package.
-#' Variables beginning with "n_" are interpolated using a weighted sum;
-#' all other variables are interpolated using a weighted mean.
+#' Variables beginning with "n_" are interpolated using a weighted sum; all
+#' other variables are interpolated using a weighted mean.
#' @export
#' @examples
#' codec_interpolate(codec_read("acs_measures"),
@@ -65,24 +71,15 @@ get_codec_tract_id_name <- function(x) {
#' codec_interpolate(codec_read("property_code_enforcements"),
#' cincy_census_geo("tract", "2019"))
codec_interpolate <- function(from, to, weights = c("pop", "homes", "area")) {
- if (!inherits(from, "codec_tbl"))
- rlang::abort("from must be a CoDEC data table")
- codec_tract_id_name <- get_codec_tract_id_name(from)
weights <- rlang::arg_match(weights)
- from_sf <-
- from |>
- codec_as_sf() |>
- dplyr::slice_sample(n = 1, by = tidyselect::all_of(codec_tract_id_name)) |>
- dplyr::select(geoid = !!codec_tract_id_name) |>
- sf::st_transform(5072)
- if (
- !grepl("^cincy_(census|neighborhood|zcta)_geo\\(", deparse(substitute(to)))
- ) {
- rlang::abort(
- "`to` must be supplied via `cincy_census_geo()`, `cincy_neighborhood_geo()`, or `cincy_zcta_geo()`"
- )
+ if (inherits(from, "codec_tbl")) {
+ from <- codec_as_sf(from)
+ } else if (!inherits(from, "sf")) {
+ rlang::abort("from must be a CoDEC data table or sf object")
}
- to_sf <- sf::st_transform(to, 5072)
+
+ from_sf <- codec_interpolate_source_sf(from)
+ to_sf <- codec_interpolate_target_sf(to)
bw <-
cincy_block_weights() |>
@@ -111,8 +108,10 @@ codec_interpolate <- function(from, to, weights = c("pop", "homes", "area")) {
suppressWarnings()
out <-
- from |>
- dplyr::rename("geoid.1" := {{ codec_tract_id_name }}) |>
+ sf::st_drop_geometry(from) |>
+ dplyr::rename(
+ "geoid.1" := tidyselect::all_of(get_codec_tract_id_name(from))
+ ) |>
dplyr::left_join(interpolation_weights, by = "geoid.1") |>
dplyr::group_by(geoid, year, dplyr::across(dplyr::any_of("month"))) |>
dplyr::summarize(
@@ -134,6 +133,33 @@ codec_interpolate <- function(from, to, weights = c("pop", "homes", "area")) {
return(out)
}
+codec_interpolate_source_sf <- function(from) {
+ codec_tract_id_name <- get_codec_tract_id_name(from)
+ if (!inherits(from, "sf") || !"s2_geography" %in% names(from)) {
+ rlang::abort(
+ "from must be an sf object with an `s2_geography` column, such as the output of `codec_as_sf()`"
+ )
+ }
+ from |>
+ dplyr::slice_sample(n = 1, by = tidyselect::all_of(codec_tract_id_name)) |>
+ dplyr::select(geoid = tidyselect::all_of(codec_tract_id_name)) |>
+ sf::st_transform(5072)
+}
+
+codec_interpolate_target_sf <- function(to) {
+ if (!inherits(to, "sf")) {
+ rlang::abort(
+ "`to` must be an sf object returned by `cincy_census_geo()`, `cincy_neighborhood_geo()`, or `cincy_zcta_geo()`"
+ )
+ }
+ if (!all(c("geoid", "s2_geography") %in% names(to))) {
+ rlang::abort(
+ "`to` must contain `geoid` and `s2_geography` columns, like the output of `cincy_census_geo()`, `cincy_neighborhood_geo()`, or `cincy_zcta_geo()`"
+ )
+ }
+ sf::st_transform(to, 5072)
+}
+
cincy_block_weights <- function(packaged = TRUE) {
if (packaged) {
return(get(
diff --git a/R/codec_pins.R b/R/codec_pins.R
index 14b4b13b..c8d4af22 100644
--- a/R/codec_pins.R
+++ b/R/codec_pins.R
@@ -1,21 +1,30 @@
#' CoDEC online data catalog
#'
-#' The CoDEC online data catalog is hosted on GitHub alongside
-#' the source code for this package.
+#' The CoDEC data catalog is shipped with the package and older versions
+#' can be read from 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`)
+#' 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
+#' - `codec_board()` can be used to create a pin board object
+#' (see `?pins::pins`) based on a specific version of the codec package
#'
#' 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)
+#' 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)
#' @export
-#' @param name The name of the CoDEC table in the online CoDEC data catalog.
-#' @param 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
-#' @return For `codec_read()`, a codec_tbl object (see `as_codec_tbl()`)
+#' @param name the name of the CoDEC table in the CoDEC data catalog.
+#' @param board a pins board object; create with `codec_board()` to read
+#' from the bundled catalog or earlier versions of the catalog, or to
+#' change the caching behavior of the pins package
+#' @param to optional target geography for interpolation; supply the output
+#' of `cincy_census_geo()`, `cincy_neighborhood_geo()`, or `cincy_zcta_geo()`
+#' to interpolate the table while reading
+#' @param weights which census block-level weights to use when `to` is
+#' supplied; passed to `codec_interpolate()`
+#' @param include_geography logical; include the `s2_geography` column in
+#' the result? Defaults to `FALSE`
+#' @return For `codec_read()`, a `codec_tbl` by default, or an interpolated
+#' tibble / simple-features tibble when `to` or `include_geography` is used
#' @export
#' @examples
#' # list available CoDEC tables
@@ -27,24 +36,45 @@
#' attr(d, "title")
#' message(attr(d, "description"))
#'
-#' # change the defaults for codec_board() to read from older versions of the board
+#' # interpolate while reading
+#' codec_read("acs_measures", to = cincy_neighborhood_geo())
+#' codec_read("acs_measures", include_geography = TRUE)
+#'
+#' # inspect the bundled board or read from an older online version
#' codec_board() |>
#' pins::pin_versions("crime")
-#' codec_board("v3.0.0-rc1") |>
+#' codec_board("v3.0.0") |>
#' pins::pin_versions("crime")
codec_read <- function(
name,
- board = codec_board()
+ board = codec_board(),
+ to = NULL,
+ weights = c("pop", "homes", "area"),
+ include_geography = FALSE
) {
stopifnot(length(name) == 1, inherits(name, "character"))
stopifnot(
inherits(board, "pins_board_url") | inherits(board, "pins_board_folder")
)
+ stopifnot(is.logical(include_geography), length(include_geography) == 1)
codec_pins <- pins::pin_list(board)
stopifnot(name %in% codec_pins)
d <- pins::pin_read(board, name)
md <- pins::pin_meta(board, name)
- as_codec_tbl(d, name = md$name, description = md$description)
+ d <- as_codec_tbl(d, name = md$name, description = md$description)
+
+ if (is.null(to)) {
+ if (isTRUE(include_geography)) {
+ return(codec_as_sf(d))
+ }
+ return(d)
+ }
+
+ out <- codec_interpolate(codec_as_sf(d), to = to, weights = weights)
+ if (isTRUE(include_geography)) {
+ return(dplyr::right_join(to, out, by = "geoid"))
+ }
+ out
}
#' @rdname codec_read
@@ -56,8 +86,9 @@ codec_list <- function(board = codec_board()) {
#' @rdname codec_read
#' @return For `codec_board()`, a pins_board object
-#' @param 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
+#' @param version specify a version of the online data catalog using a
+#' commit SHA, tag, or branch of geomarker-io/codec; uses the bundled board
+#' for the installed package version by default
#' @inheritParams pins::board_url
#' @export
codec_board <- function(
@@ -66,23 +97,75 @@ codec_board <- function(
use_cache_on_failure = rlang::is_interactive(),
headers = NULL
) {
- codec_board_url <-
- glue::glue(
- "https://raw.githubusercontent.com/",
- "geomarker-io/codec/{ version }/assets/data/"
+ current_version <- paste0("v", utils::packageVersion("codec"))
+ if (identical(as.character(version), current_version)) {
+ return(codec_board_local())
+ }
+ codec_board_remote(
+ version = version,
+ cache = cache,
+ use_cache_on_failure = use_cache_on_failure,
+ headers = headers
+ )
+}
+
+codec_board_remote <- function(
+ version,
+ cache = NULL,
+ use_cache_on_failure = rlang::is_interactive(),
+ headers = NULL
+) {
+ board_paths <- c("inst/board", "assets/data")
+ for (board_path in board_paths) {
+ board <- tryCatch(
+ {
+ codec_board_url <-
+ glue::glue(
+ "https://raw.githubusercontent.com/",
+ "geomarker-io/codec/{ version }/{ board_path }/"
+ )
+ pins::board_url(
+ as.character(codec_board_url),
+ cache = cache,
+ use_cache_on_failure = use_cache_on_failure,
+ headers = headers
+ )
+ },
+ error = function(...) NULL
)
- pins::board_url(as.character(codec_board_url))
+ if (!is.null(board)) {
+ return(board)
+ }
+ }
+ rlang::abort(glue::glue(
+ "No CoDEC board found online for version `{version}`."
+ ))
+}
+
+codec_board_local <- function() {
+ installed_path <- system.file("board", package = "codec")
+ if (nzchar(installed_path)) {
+ return(pins::board_folder(installed_path))
+ }
+
+ repo_path <- here::here("inst/board")
+ if (file.exists(file.path(repo_path, "_pins.yaml"))) {
+ return(pins::board_folder(repo_path))
+ }
+
+ rlang::abort("Local CoDEC board not found.")
}
#' @rdname write_codec_pin
codec_board_local_dev <- function() {
- pins::board_folder(here::here("assets/data"))
+ codec_board_local()
}
#' Write a CoDEC data table to the local CoDEC board directory
#'
-#' This function is used by developers creating and updating CoDEC data tables.
+#' This function is used by developers creating and updating CoDEC data
+#' tables.
#' @param x a codec_tbl object created with as_codec_tbl()
#' @keywords internal
write_codec_pin <- function(x) {
diff --git a/R/codec_tbl.R b/R/codec_tbl.R
index 47e993a0..77379f59 100644
--- a/R/codec_tbl.R
+++ b/R/codec_tbl.R
@@ -1,18 +1,22 @@
#' Convert a data frame, name, and description into a CoDEC table
#'
#' **CoDEC Specifications:**
-#' 1. The data must include a [census tract](https://www2.census.gov/geo/pdfs/education/CensusTracts.pdf)
-#' identifier column (i.e., `census_tract_id_2010`, or `census_tract_id_2020`).
-#' The column must contain 11-digit
-#' [GEOID](https://www.census.gov/programs-surveys/geography/guidance/geo-identifiers.html)
-#' identifiers for every census tract in Hamilton County, OH.
-#' 2. Data must be structured in a tidy format such that each row is an observation
-#' for a specific census tract at a specific year (and month). This means that the data
-#' includes a year column (`year`), an integer year representing the vintage of the data (e.g. `2021`).
-#' The data can optionally include a month column (`month`), an integer month of the year.
-#' 3. The name must only contain lower case alphanumeric characters, `-`, or `_`
-#' 4. The description should be markdown text and the first line must contain the title of
-#' the CoDEC data table as a level one header (e.g., `# My Community Data`). Titles must be less than 80 characters.
+#' 1. The data must include a census tract identifier column (i.e.,
+#' `census_tract_id_2010` or `census_tract_id_2020`).
+#' The column must contain 11-digit GEOID identifiers for every census
+#' tract in Hamilton County, OH.
+#' 2. Data must be structured in a tidy format such that each row is an
+#' observation for a specific census tract at a specific year (and month).
+#' This means that the data includes a year column (`year`), an integer
+#' year representing the vintage of the data (e.g. `2021`).
+#' The data can optionally include a month column (`month`), an integer
+#' month of the year.
+#' 3. The name must only contain lower case alphanumeric characters, `-`,
+#' or `_`
+#' 4. The description should be markdown text and the first line must
+#' contain the title of the CoDEC data table as a level one header
+#' (e.g., `# My Community Data`). Titles must be less than 80
+#' characters.
#'
#' @param x data.frame or tibble meeting CoDEC data specifications above
#' @param name name of CoDEC table
@@ -27,10 +31,16 @@
#' ) |>
#' as_codec_tbl(
#' name = "n_things",
-#' "# Number of Things\n Number of things were averaged by census tract using the survey from 2024"
+#' paste0(
+#' "# Number of Things\n",
+#' "Number of things were averaged by census tract ",
+#' "using the survey from 2024"
+#' )
#' )
as_codec_tbl <- function(x, name, description = character()) {
- if (inherits(x, "codec_tbl")) return(x)
+ if (inherits(x, "codec_tbl")) {
+ return(x)
+ }
codec_check_census_tract_id(x)
codec_check_date(x)
name <- codec_check_label(name, "name", required = TRUE)
diff --git a/R/data.R b/R/data.R
index 477b3da9..e35445f3 100644
--- a/R/data.R
+++ b/R/data.R
@@ -1,10 +1,12 @@
#' CoDEC latest annual
#'
-#' CoDEC data is harmonized as the most recently available annual (or annual average of monthly) values
-#' at the census tract 2020 geography.
-#' The year represents the year this table was assembled and mainly used as a placeholder to this object
-#' can be used with functions that take a codec_tbl object (see `?as_codec_tbl`).
-#' See the description metadata for the actual latest years used for each CoDEC table.
+#' CoDEC data is harmonized as the most recently available annual
+#' (or annual average of monthly) values at the census tract 2020 geography.
+#' The year represents the year this table was assembled and mainly used as
+#' a placeholder so this object can be used with functions that take a
+#' `codec_tbl` object (see `?as_codec_tbl`).
+#' See the description metadata for the actual latest years used for each
+#' CoDEC table.
#' @examples
#' glue::glue(attr(codec_latest_annual, "description"))
#' tibble::glimpse(codec_latest_annual)
diff --git a/README.md b/README.md
index a3629556..a124d336 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,10 @@
# CoDEC
+
[](https://github.com/geomarker-io/codec/actions/workflows/R-CMD-check.yaml)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
+
The goal of the R package {codec} is to support [CoDEC](https://geomarker.io/codec) data
@@ -25,3 +27,62 @@ install.packages("codec", repos = c("https://geomarker-io.r-universe.dev", "http
### Usage
See https://geomarker.io/codec/reference/index.html for reference pages on included functions.
+
+### Accessing CoDEC data with or without `{codec}`
+
+If you are using the package, `codec_board()` and `codec_read()` can read the
+bundled board or older remote boards without needing to know where the board is
+stored in the repository. That is the recommended path when you want the full
+package API, including interpolation helpers and other utilities.
+
+Installing the released version from
+[R-universe](https://geomarker-io.r-universe.dev/codec) is especially important
+when `{codec}` needs to be included in wasm builds or other deployed content,
+because those environments should rely on a published package build rather than
+a development checkout.
+
+If you only need the latest CoDEC table data and do not want to install
+`{codec}`, you can read the remote pins board directly with `{pins}`.
+
+For version `3.1.0` and later, the simplest option is:
+
+```r
+codec_board <- pins::board_url(
+ "https://raw.githubusercontent.com/geomarker-io/codec/main/inst/board/"
+)
+
+acs_measures <- pins::pin_read(codec_board, "acs_measures")
+```
+
+If you need something that also works with older repository layouts, use:
+
+```r
+board_paths <- c("inst/board", "assets/board")
+
+codec_board <- NULL
+for (board_path in board_paths) {
+ board <- tryCatch(
+ pins::board_url(
+ paste0(
+ "https://raw.githubusercontent.com/geomarker-io/codec/main/",
+ board_path,
+ "/"
+ )
+ ),
+ error = function(...) NULL
+ )
+ if (!is.null(board)) {
+ codec_board <- board
+ break
+ }
+}
+
+stopifnot(!is.null(codec_board))
+acs_measures <- pins::pin_read(codec_board, "acs_measures")
+```
+
+This repository layout changed over time: prior to version `3.1.0`, the board
+was published from `assets/board`; starting with `3.1.0`, it is published from
+`inst/board`. The `{codec}` package handles that difference for you when
+reading remotely, but the direct `{pins}` approach above is useful when you
+want to include CoDEC data without installing the package.
diff --git a/data-raw/codec_tbl/acs_measures/README.md b/data-raw/codec_tbl/acs_measures/README.md
index 76ee4f09..775d06c7 100644
--- a/data-raw/codec_tbl/acs_measures/README.md
+++ b/data-raw/codec_tbl/acs_measures/README.md
@@ -2,7 +2,7 @@
## About
-Select population, socioeconomic, and housing measures derived from the 2023 5-yr U.S. Census American Community Survey (ACS) and were selected to cover three domains:
+Select population, socioeconomic, and housing measures derived from the 2024 5-yr U.S. Census American Community Survey (ACS) and were selected to cover three domains:
- **Population**: number of kids, number of households (with kids), single-parent households, racial and ethnic composition, limited English speaking households
- **Socioeconomic**: education, income, poverty, employment, health insurance, public income assistance
diff --git a/data-raw/codec_tbl/acs_measures/make.R b/data-raw/codec_tbl/acs_measures/make.R
index 3647108a..8a497f44 100644
--- a/data-raw/codec_tbl/acs_measures/make.R
+++ b/data-raw/codec_tbl/acs_measures/make.R
@@ -4,17 +4,18 @@ codec_name <- "acs_measures"
library(dplyr, warn.conflicts = FALSE)
all_acs5_variables <-
- dpkg::stow("https://api.census.gov/data/2023/acs/acs5/variables.json") |>
+ dpkg::stow("https://api.census.gov/data/2025/acs/acs5/variables.json") |>
jsonlite::read_json()
get_acs_5yr_data <- function(
acs_variables,
state = "39",
county = "061",
- year = "2023"
+ year = "2024"
) {
- if (Sys.getenv("CENSUS_API_KEY") == "")
+ if (Sys.getenv("CENSUS_API_KEY") == "") {
stop("set CENSUS_API_KEY enviroment variable")
+ }
cli::cli_alert_info(glue::glue(
"getting {paste(acs_variables, collapse = ', ')}; defined as:"
))
@@ -234,7 +235,7 @@ out$edu <-
out_tbl <- purrr::reduce(out, dplyr::left_join, by = "census_tract_id_2020")
out_tbl |>
- dplyr::mutate(year = 2023L) |>
+ dplyr::mutate(year = 2024L) |>
as_codec_tbl(
name = codec_name,
description = paste(
diff --git a/data-raw/codec_tbl/drivetime/README.md b/data-raw/codec_tbl/drivetime/README.md
index b7e49b57..8d3cf781 100644
--- a/data-raw/codec_tbl/drivetime/README.md
+++ b/data-raw/codec_tbl/drivetime/README.md
@@ -6,4 +6,4 @@ A census tract-level measure of drive time to Cincinnati Children's Hospital Med
## Data
-Each tract-level drive time is an area-weighted average of intersecting 6-minute interval drive time isochrones.
+Each tract-level drive time is an area-weighted average of intersecting 6-minute interval drive time isochrones calculated for the packaged 2020 census tract geographies.
diff --git a/data-raw/codec_tbl/drivetime/make.R b/data-raw/codec_tbl/drivetime/make.R
index 7539db1a..de66be69 100644
--- a/data-raw/codec_tbl/drivetime/make.R
+++ b/data-raw/codec_tbl/drivetime/make.R
@@ -5,23 +5,27 @@ library(dplyr, warn.conflicts = FALSE)
library(sf)
isochrones <-
- s3::s3_get("s3://geomarker/drivetime/isochrones/cchmc_isochrones.rds") |>
- readRDS()
-# used the cache! but should switch to github asset
+ readRDS(url(
+ "https://github.com/degauss-org/drivetime/releases/download/1.3.0/cchmc_isochrones.rds"
+ ))
out <-
- sf::st_intersection(cincy::tract_tigris_2010, isochrones) |>
+ sf::st_intersection(
+ sf::st_transform(cincy_census_geo("tract", "2020"), sf::st_crs(isochrones)),
+ isochrones
+ ) |>
dplyr::mutate(
- area = round(as.numeric(sf::st_area(geometry))),
+ area = round(as.numeric(sf::st_area(s2_geography))),
drive_time = as.numeric(as.character(drive_time))
) |>
- dplyr::group_by(census_tract_id_2010) |>
+ dplyr::group_by(geoid) |>
dplyr::mutate(wt_drive_time = drive_time * area / sum(area)) |>
dplyr::summarize(drive_time_avg = round(sum(wt_drive_time), 1)) |>
sf::st_drop_geometry() |>
dplyr::mutate(year = 2024L)
out |>
+ rename(census_tract_id_2020 = geoid) |>
as_codec_tbl(
name = codec_name,
description = paste(
diff --git a/data-raw/codec_tbl/environmental_justice_index/README.md b/data-raw/codec_tbl/environmental_justice_index/README.md
index b541f663..dfcad65e 100644
--- a/data-raw/codec_tbl/environmental_justice_index/README.md
+++ b/data-raw/codec_tbl/environmental_justice_index/README.md
@@ -4,14 +4,13 @@
> The Environmental Justice Index uses data from the U.S. Census Bureau, the U.S. Environmental Protection Agency, the U.S. Mine Safety and Health Administration, and the U.S. Centers for Disease Control and Prevention to rank the cumulative impacts of environmental injustice on health for every census tract. ... The EJI ranks each tract on 36 environmental, social, and health factors and groups them into three overarching modules and ten different domains.
-
-The ATSDR's [Environmental Justice Index (EJI)](https://www.atsdr.cdc.gov/placeandhealth/eji/index.html) was most recently released in 2022, but utilizes data from several older sources.
-Note that although the EJI data has a `year` of 2022 in the CoDEC data package, fields in the EJI are from different sources that are each actually older.
-Find the full documentation of the EJI in PDF form here: https://eji.cdc.gov/Documents/Data/2022/EJI_2022_Data_Dictionary_508.pdf
+The ATSDR's [Environmental Justice Index (EJI)](https://www.atsdr.cdc.gov/placeandhealth/eji/index.html) was most recently released in 2024, but utilizes data from several older sources.
+Note that although the EJI data has a `year` of 2024 in the CoDEC data package, fields in the EJI are from different sources that are each actually older.
+Find the full documentation of the EJI in PDF form here: https://www.atsdr.cdc.gov/place-health/media/pdfs/2024/10/EJI_2024_Technical_Documentation.pdf
## Data
- Data download from https://www.atsdr.cdc.gov/placeandhealth/eji/eji-data-download.html as a geodatabase
-- Data fields representing "estimates" (i.e., not "percentile" or "summed ranks") selected if not avilable elsewhere (e.g., not American Community Survey estimates)
+- Data fields representing "estimates" (i.e., not "percentile" or "summed ranks") selected if not available elsewhere (e.g., not American Community Survey estimates)
- Field names were renamed to be longer and more descriptive
-- Although this is the 2022 release, 2010 vintage census tract geographies and identifers are used in the EJI data
+- Although this is the 2022 release, 2010 vintage census tract geographies and identifiers are used in the EJI data
diff --git a/data-raw/codec_tbl/environmental_justice_index/make.R b/data-raw/codec_tbl/environmental_justice_index/make.R
index 5ac31047..cee526a3 100644
--- a/data-raw/codec_tbl/environmental_justice_index/make.R
+++ b/data-raw/codec_tbl/environmental_justice_index/make.R
@@ -3,20 +3,22 @@ codec_name <- "environmental_justice_index"
library(dplyr, warn.conflicts = FALSE)
-
tf <- tempfile(fileext = ".zip")
-download.file("https://eji.cdc.gov/Documents/Data/2022/DBS/Ohio.zip", tf)
+download.file(
+ "https://eji.cdc.gov/Documents/Data/2024/2024_DBS/EJI_2024_Ohio_GDB.zip",
+ tf
+)
unzip(tf, exdir = tempdir())
rd <-
- sf::st_read(fs::path_temp("Ohio.gdb")) |>
+ sf::st_read(fs::path_temp("EJI_2024_Ohio", "EJI_2024_Ohio.gdb")) |>
tibble::as_tibble()
out <-
rd |>
filter(substr(GEOID, 1, 5) == "39061") |>
select(
- census_tract_id_2010 = GEOID,
+ census_tract_id_2020 = GEOID,
prcnt_area_within_1mi_epa_npl_site = E_NPL,
prcnt_area_within_1mi_epa_tri_site = E_TRI,
prcnt_area_within_1m_epa_tsd_site = E_TSD,
@@ -32,7 +34,7 @@ out <-
prcnt_area_huc12_watershed = E_IMPWTR
)
-out$year <- 2022L
+out$year <- 2024L
out |>
as_codec_tbl(
diff --git a/data-raw/codec_tbl/landcover/README.md b/data-raw/codec_tbl/landcover/README.md
index 98a555e7..b374fb7f 100644
--- a/data-raw/codec_tbl/landcover/README.md
+++ b/data-raw/codec_tbl/landcover/README.md
@@ -2,19 +2,8 @@
## About
-Taken from https://github.com/geomarker-io/hamilton_landcover.
-Census tract-level measures of greenness, imperviousness, and treecanopy are derived from the National Land Cover Database (NLCD) and NASA MODIS satellite data.
-
-Although `year=2019` for this product, it is a compilation of other annual products with unique years denoted in the field names.
+The National Landcover Database (NLCD) is an annual product that summarizes fraction imperviousness (fractional surface area covered with artificial substrate or structures) at a 30 m grid. The fraction imperviousness is averaged through spatial intersection with the 2020 census tract boundaries.
## Data
-See https://github.com/geomarker-io/hamilton_landcover for data source scripts.
-
-### Defining greenspace using NLCD land cover classifications
-
-A grid cell is considered greenspace if its NLCD land cover classification is in any category except water, ice/snow, developed medium intensity, developed high intensity, rock/sand/clay.
-
-### Enhanced Vegetation Index (EVI)
-
-The Enhanced Vegetation Index (EVI) is a measure of greenness that ranges from -0.2 to 1, with higher values corresponding to more vegetation. A cloud-free composite EVI raster at a resolution of 250 × 250 m was created by assembling individual images collected via remote sensing between June 10 and June 25, 2018.
+Cloud-optimized GeoTIFF files are hosted on Harvard's Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KXETFC). These files were downloaded from the [Annual NLCD Product Suite](https://www.usgs.gov/centers/eros/science/annual-nlcd-product-suite) and converted from GeoTIFF to cloud-optimized GeoTIFF (COG) using `gdal_translate`.
diff --git a/data-raw/codec_tbl/landcover/make.R b/data-raw/codec_tbl/landcover/make.R
index 548f7027..16838bf0 100644
--- a/data-raw/codec_tbl/landcover/make.R
+++ b/data-raw/codec_tbl/landcover/make.R
@@ -1,19 +1,109 @@
devtools::load_all()
codec_name <- "landcover"
-rd <- readr::read_csv(
- "https://github.com/geomarker-io/hamilton_landcover/releases/download/v0.1.0/hamilton_landcover.csv",
- col_types = "cdddd"
-)
-
-out <-
- rd |>
- tibble::as_tibble() |>
- dplyr::rename(
- enhanced_vegatation_index_2018 = evi_2018,
- census_tract_id_2010 = census_tract_id
+d <- cincy_census_geo("tract", "2020")
+
+get_dv_url <- function(
+ persistent_id,
+ filename = NULL,
+ version = "latest",
+ server_url = "https://dataverse.harvard.edu"
+) {
+ stopifnot(is.character(persistent_id))
+ stopifnot(is.character(version))
+ stopifnot(is.character(server_url))
+ if (!substr(persistent_id, 1, 4) == "doi:") {
+ stop("`persistent_id` must begin with 'doi:'", call. = FALSE)
+ }
+ if (version == "latest") {
+ version <- ":latest"
+ }
+
+ req <-
+ httr2::request(server_url) |>
+ httr2::req_user_agent("pcog (https://github.com/geomarker-io/pcog)") |>
+ httr2::req_url_path_append(
+ "api",
+ "datasets",
+ ":persistentId",
+ "versions",
+ version
+ ) |>
+ httr2::req_url_query("persistentId" = persistent_id) |>
+ httr2::req_error(
+ is_error = function(resp) httr2::resp_status(resp) != 200,
+ body = function(resp) {
+ glue::glue(
+ "version {version} of {persistent_id} not found at {server_url}"
+ )
+ }
+ )
+ resp <- httr2::req_perform(req)
+
+ if (httr2::resp_content_type(resp) == "application/xhtml+xml") {
+ stop(
+ "This dataverse is returning xhtml+xml content and likey running a demo during maintainence; try again later",
+ call. = FALSE
+ )
+ }
+ the_files <-
+ httr2::resp_body_json(resp)$data$files |>
+ vapply(\(.) .$dataFile[["id"]], integer(1))
+
+ names(the_files) <-
+ httr2::resp_body_json(resp)$data$files |>
+ vapply(\(.) .$dataFile[["filename"]], character(1))
+
+ if (length(filename) == 1 && filename %in% names(the_files)) {
+ file_id <- the_files[[filename]]
+ } else {
+ message(
+ "available files for ",
+ persistent_id,
+ " include: \n ",
+ paste(names(the_files), collapse = "\n ")
+ )
+ if (length(filename) == 0) {
+ stop("no filename requested", call. = FALSE)
+ }
+ stop("filename ", filename, " not found.", call. = FALSE)
+ }
+
+ cog_url <- glue::glue(
+ "https://dataverse.harvard.edu/api/access/datafile/{file_id}"
+ )
+ return(as.character(cog_url))
+}
+
+
+for (nlcd_year in as.character(2023:2020)) {
+ message("extracting data for ", nlcd_year)
+ r <-
+ get_dv_url(
+ persistent_id = "doi:10.7910/DVN/KXETFC",
+ filename = glue::glue("Annual_NLCD_FctImp_{nlcd_year}_CU_C1V0_COG.tif"),
+ version = "latest"
+ ) |>
+ terra::rast(vsi = TRUE)
+ d[[glue::glue("mean_pct_impervious_{nlcd_year}")]] <- terra::extract(
+ r,
+ terra::vect(d),
+ fun = "mean",
+ ID = FALSE
+ )[[1]]
+}
+
+out <- d |>
+ sf::st_drop_geometry() |>
+ tidyr::pivot_longer(
+ -geoid,
+ names_to = "year",
+ names_prefix = "mean_pct_impervious_",
+ values_to = "mean_pct_impervious"
) |>
- dplyr::mutate(year = 2019L)
+ dplyr::rename(census_tract_id_2020 = geoid)
+
+out$year <- as.integer(out$year)
out |>
as_codec_tbl(
diff --git a/data-raw/codec_tbl/traffic/README.md b/data-raw/codec_tbl/traffic/README.md
index fe02ca16..5de747f6 100644
--- a/data-raw/codec_tbl/traffic/README.md
+++ b/data-raw/codec_tbl/traffic/README.md
@@ -2,10 +2,8 @@
## 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`).
+Traffic is measured in AADTM or Annual Average Daily Traffic Meters, which is the average number of total meters driven by all vehicles per day when grouped into classes (trucks/buses, tractor/trailer, passenger).
-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:
-
@@ -14,7 +12,8 @@ For more details about the HPMS, see:
## Data
+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.
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.
+For each 2020 census tract geography, sum the class-specific AADTM for all intersecting roads, weighted by their intersecting lengths.
diff --git a/data-raw/make_codec_latest_annual.R b/data-raw/make_codec_latest_annual.R
index fc2cda46..52ff5f77 100644
--- a/data-raw/make_codec_latest_annual.R
+++ b/data-raw/make_codec_latest_annual.R
@@ -2,9 +2,12 @@ devtools::load_all()
library(dplyr, warn.conflicts = FALSE)
# average values harmonized to 2020 tracts from all months in the latest year
-# if second_latest is true, when the most recent year has less than 12 monthly values, the second latest year will be used instead
+# if second_latest is true, when the most recent year has less than 12 monthly
+# values, the second latest year will be used instead
codec_harmonize_latest_annual <- function(x, second_latest = FALSE) {
- if (!inherits(x, "codec_tbl")) rlang::abort("x must be a codec_tbl object")
+ if (!inherits(x, "codec_tbl")) {
+ rlang::abort("x must be a codec_tbl object")
+ }
x_2020_tract <- codec_interpolate(x, cincy_census_geo("tract", "2020"))
latest_year <- max(x_2020_tract$year)
x_latest <-
@@ -48,20 +51,20 @@ codec_harmonize_latest_annual <- function(x, second_latest = FALSE) {
d <-
purrr::map(
pins::pin_list(codec_board_local_dev()),
- \(x)
+ \(x) {
codec_harmonize_latest_annual(
codec_read(x, codec_board_local_dev()),
second_latest = TRUE
- ),
+ )
+ },
.progress = "harmonizing CoDEC tables to latest annual for 2020 tracts"
)
-
codec_latest_annual <-
d |>
purrr::map(~ tibble::as_tibble(select(., -year))) |>
purrr::reduce(left_join, by = "census_tract_id_2020") |>
- mutate(year = 2025L) |>
+ mutate(year = 2026L) |>
as_codec_tbl(
name = "codec_latest_annual",
description = glue::glue(
diff --git a/data/codec_latest_annual.rda b/data/codec_latest_annual.rda
index 705b7783..146751f4 100644
Binary files a/data/codec_latest_annual.rda and b/data/codec_latest_annual.rda differ
diff --git a/assets/data/_pins.yaml b/inst/board/_pins.yaml
similarity index 88%
rename from assets/data/_pins.yaml
rename to inst/board/_pins.yaml
index a98eb7d5..5988e56a 100644
--- a/assets/data/_pins.yaml
+++ b/inst/board/_pins.yaml
@@ -3,6 +3,7 @@ acs_measures:
- acs_measures/20250831T021158Z-8f122/
- acs_measures/20250831T023115Z-8f122/
- acs_measures/20250901T032818Z-8f122/
+- acs_measures/20260503T001200Z-62ad0/
crime:
- crime/20250829T181659Z-bf502/
- crime/20250831T023010Z-bf502/
@@ -15,11 +16,13 @@ drivetime:
- drivetime/20250901T025854Z-69555/
- drivetime/20250901T033138Z-69555/
- drivetime/20250902T010120Z-69555/
+- drivetime/20260503T002359Z-31248/
environmental_justice_index:
- environmental_justice_index/20250828T021012Z-e4c31/
- environmental_justice_index/20250831T023444Z-e4c31/
- environmental_justice_index/20250901T033148Z-e4c31/
- environmental_justice_index/20250902T010746Z-e4c31/
+- environmental_justice_index/20260503T003413Z-0dc9e/
landcover:
- landcover/20250828T024022Z-5a480/
- landcover/20250831T023527Z-5a480/
@@ -27,6 +30,7 @@ landcover:
- landcover/20250831T152750Z-97558/
- landcover/20250901T033154Z-97558/
- landcover/20250902T010753Z-97558/
+- landcover/20260503T004925Z-b235f/
parcel:
- parcel/20250828T024230Z-146a7/
- parcel/20250831T023639Z-25a36/
@@ -44,3 +48,4 @@ traffic:
- traffic/20250831T024013Z-32c9c/
- traffic/20250901T033447Z-32c9c/
- traffic/20250902T011043Z-32c9c/
+- traffic/20260503T010145Z-32c9c/
diff --git a/assets/data/acs_measures/20250828T023008Z-0ef1f/acs_measures.json b/inst/board/acs_measures/20250828T023008Z-0ef1f/acs_measures.json
similarity index 100%
rename from assets/data/acs_measures/20250828T023008Z-0ef1f/acs_measures.json
rename to inst/board/acs_measures/20250828T023008Z-0ef1f/acs_measures.json
diff --git a/assets/data/acs_measures/20250828T023008Z-0ef1f/data.txt b/inst/board/acs_measures/20250828T023008Z-0ef1f/data.txt
similarity index 100%
rename from assets/data/acs_measures/20250828T023008Z-0ef1f/data.txt
rename to inst/board/acs_measures/20250828T023008Z-0ef1f/data.txt
diff --git a/assets/data/acs_measures/20250831T021158Z-8f122/acs_measures.json b/inst/board/acs_measures/20250831T021158Z-8f122/acs_measures.json
similarity index 100%
rename from assets/data/acs_measures/20250831T021158Z-8f122/acs_measures.json
rename to inst/board/acs_measures/20250831T021158Z-8f122/acs_measures.json
diff --git a/assets/data/acs_measures/20250831T021158Z-8f122/data.txt b/inst/board/acs_measures/20250831T021158Z-8f122/data.txt
similarity index 100%
rename from assets/data/acs_measures/20250831T021158Z-8f122/data.txt
rename to inst/board/acs_measures/20250831T021158Z-8f122/data.txt
diff --git a/assets/data/acs_measures/20250831T023115Z-8f122/acs_measures.json b/inst/board/acs_measures/20250831T023115Z-8f122/acs_measures.json
similarity index 100%
rename from assets/data/acs_measures/20250831T023115Z-8f122/acs_measures.json
rename to inst/board/acs_measures/20250831T023115Z-8f122/acs_measures.json
diff --git a/assets/data/acs_measures/20250831T023115Z-8f122/data.txt b/inst/board/acs_measures/20250831T023115Z-8f122/data.txt
similarity index 100%
rename from assets/data/acs_measures/20250831T023115Z-8f122/data.txt
rename to inst/board/acs_measures/20250831T023115Z-8f122/data.txt
diff --git a/assets/data/acs_measures/20250901T032818Z-8f122/acs_measures.json b/inst/board/acs_measures/20250901T032818Z-8f122/acs_measures.json
similarity index 100%
rename from assets/data/acs_measures/20250901T032818Z-8f122/acs_measures.json
rename to inst/board/acs_measures/20250901T032818Z-8f122/acs_measures.json
diff --git a/assets/data/acs_measures/20250901T032818Z-8f122/data.txt b/inst/board/acs_measures/20250901T032818Z-8f122/data.txt
similarity index 100%
rename from assets/data/acs_measures/20250901T032818Z-8f122/data.txt
rename to inst/board/acs_measures/20250901T032818Z-8f122/data.txt
diff --git a/inst/board/acs_measures/20260503T001200Z-62ad0/acs_measures.json b/inst/board/acs_measures/20260503T001200Z-62ad0/acs_measures.json
new file mode 100644
index 00000000..5d3de814
--- /dev/null
+++ b/inst/board/acs_measures/20260503T001200Z-62ad0/acs_measures.json
@@ -0,0 +1 @@
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lic_assistance_income":0.132,"prop_family_households_with_single_householder":0.2804,"prop_employment_among_civilian_workforce":0.9527,"prop_housing_units_occupied_by_renters":0.4841,"prop_median_rent_to_income_ratio_among_renters":29.2,"prop_housing_units_vacant":0.0888,"prop_white_and_not_hispanic_or_latino":0.703,"prop_black_and_not_hispanic_or_latino":0.197,"prop_white_and_hispanic_or_latino":0.0037,"prop_black_and_hispanic_or_latino":0,"n_persons_under_18":701,"prop_health_insurance":0.9389,"prop_rent_burdened":0.4311,"prop_housing_conditions":0.2915,"prop_built_prior_1980":0.3067,"prop_limited_english_speaking":0,"prop_adults_hs_edu":0.9452,"year":2024}]
diff --git a/inst/board/acs_measures/20260503T001200Z-62ad0/data.txt b/inst/board/acs_measures/20260503T001200Z-62ad0/data.txt
new file mode 100644
index 00000000..6636b339
--- /dev/null
+++ b/inst/board/acs_measures/20260503T001200Z-62ad0/data.txt
@@ -0,0 +1,47 @@
+file: acs_measures.json
+file_size: 190668
+pin_hash: 62ad052da5cb1453
+type: json
+title: American Community Survey Measures
+description: |-
+ # American Community Survey Measures
+
+ ## About
+
+ Select population, socioeconomic, and housing measures derived from the 2024 5-yr U.S. Census American Community Survey (ACS) and were selected to cover three domains:
+
+ - **Population**: number of kids, number of households (with kids), single-parent households, racial and ethnic composition, limited English speaking households
+ - **Socioeconomic**: education, income, poverty, employment, health insurance, public income assistance
+ - **Housing**: vacancy, age, value, tenure, rent to income ratio
+
+ ## Data
+
+ ### Types of ACS measures
+
+ Measures and their definitions are contained in `make.R`.
+ Generally, each of the derived ACS measures are expressed in one of three ways:
+
+ 1. measures starting with **`n_`** represent a **number** of something, such as `n_household`
+
+ 2. measures starting with **`prop_`** represent a **proportion** of some total, such as `prop_poverty`
+
+ 3. measures starting with **`median_`** represent a **median** of a number in a population, such as `median_income`
+
+ ### Missing Data
+
+ Additionally, data summaries may be [suppressed ](https://www.census.gov/programs-surveys/acs/technical-documentation/data-suppression.html) by the census bureau.
+tags: ~
+urls:
+- https://github.com/geomarker-io/codec
+created: 20260503T001200Z
+api_version: 1
+user:
+ sesh:
+ r_version: R version 4.4.3 (2025-02-28)
+ platform: aarch64-apple-darwin24.2.0
+ date: 20575.0
+ loaded_packages:
+ - dplyr-v1.1.4
+ - codec-v3.0.0
+ - testthat-v3.2.1.1
+ - colorout-v1.3-3
diff --git a/assets/data/crime/20250829T181659Z-bf502/crime.json b/inst/board/crime/20250829T181659Z-bf502/crime.json
similarity index 100%
rename from assets/data/crime/20250829T181659Z-bf502/crime.json
rename to inst/board/crime/20250829T181659Z-bf502/crime.json
diff --git a/assets/data/crime/20250829T181659Z-bf502/data.txt b/inst/board/crime/20250829T181659Z-bf502/data.txt
similarity index 100%
rename from assets/data/crime/20250829T181659Z-bf502/data.txt
rename to inst/board/crime/20250829T181659Z-bf502/data.txt
diff --git a/assets/data/crime/20250831T023010Z-bf502/crime.json b/inst/board/crime/20250831T023010Z-bf502/crime.json
similarity index 100%
rename from assets/data/crime/20250831T023010Z-bf502/crime.json
rename to inst/board/crime/20250831T023010Z-bf502/crime.json
diff --git a/assets/data/crime/20250831T023010Z-bf502/data.txt b/inst/board/crime/20250831T023010Z-bf502/data.txt
similarity index 100%
rename from assets/data/crime/20250831T023010Z-bf502/data.txt
rename to inst/board/crime/20250831T023010Z-bf502/data.txt
diff --git a/assets/data/crime/20250901T033049Z-bf502/crime.json b/inst/board/crime/20250901T033049Z-bf502/crime.json
similarity index 100%
rename from assets/data/crime/20250901T033049Z-bf502/crime.json
rename to inst/board/crime/20250901T033049Z-bf502/crime.json
diff --git a/assets/data/crime/20250901T033049Z-bf502/data.txt b/inst/board/crime/20250901T033049Z-bf502/data.txt
similarity index 100%
rename from assets/data/crime/20250901T033049Z-bf502/data.txt
rename to inst/board/crime/20250901T033049Z-bf502/data.txt
diff --git a/assets/data/crime/20250902T005725Z-bf502/crime.json b/inst/board/crime/20250902T005725Z-bf502/crime.json
similarity index 100%
rename from assets/data/crime/20250902T005725Z-bf502/crime.json
rename to inst/board/crime/20250902T005725Z-bf502/crime.json
diff --git a/assets/data/crime/20250902T005725Z-bf502/data.txt b/inst/board/crime/20250902T005725Z-bf502/data.txt
similarity index 100%
rename from assets/data/crime/20250902T005725Z-bf502/data.txt
rename to inst/board/crime/20250902T005725Z-bf502/data.txt
diff --git a/assets/data/crime/20250902T182616Z-91afb/crime.json b/inst/board/crime/20250902T182616Z-91afb/crime.json
similarity index 100%
rename from assets/data/crime/20250902T182616Z-91afb/crime.json
rename to inst/board/crime/20250902T182616Z-91afb/crime.json
diff --git a/assets/data/crime/20250902T182616Z-91afb/data.txt b/inst/board/crime/20250902T182616Z-91afb/data.txt
similarity index 100%
rename from assets/data/crime/20250902T182616Z-91afb/data.txt
rename to inst/board/crime/20250902T182616Z-91afb/data.txt
diff --git a/assets/data/drivetime/20250828T023328Z-69555/data.txt b/inst/board/drivetime/20250828T023328Z-69555/data.txt
similarity index 100%
rename from assets/data/drivetime/20250828T023328Z-69555/data.txt
rename to inst/board/drivetime/20250828T023328Z-69555/data.txt
diff --git a/assets/data/drivetime/20250828T023328Z-69555/drivetime.json b/inst/board/drivetime/20250828T023328Z-69555/drivetime.json
similarity index 100%
rename from assets/data/drivetime/20250828T023328Z-69555/drivetime.json
rename to inst/board/drivetime/20250828T023328Z-69555/drivetime.json
diff --git a/assets/data/drivetime/20250831T023414Z-69555/data.txt b/inst/board/drivetime/20250831T023414Z-69555/data.txt
similarity index 100%
rename from assets/data/drivetime/20250831T023414Z-69555/data.txt
rename to inst/board/drivetime/20250831T023414Z-69555/data.txt
diff --git a/assets/data/drivetime/20250831T023414Z-69555/drivetime.json b/inst/board/drivetime/20250831T023414Z-69555/drivetime.json
similarity index 100%
rename from assets/data/drivetime/20250831T023414Z-69555/drivetime.json
rename to inst/board/drivetime/20250831T023414Z-69555/drivetime.json
diff --git a/assets/data/drivetime/20250901T025854Z-69555/data.txt b/inst/board/drivetime/20250901T025854Z-69555/data.txt
similarity index 100%
rename from assets/data/drivetime/20250901T025854Z-69555/data.txt
rename to inst/board/drivetime/20250901T025854Z-69555/data.txt
diff --git a/assets/data/drivetime/20250901T025854Z-69555/drivetime.json b/inst/board/drivetime/20250901T025854Z-69555/drivetime.json
similarity index 100%
rename from assets/data/drivetime/20250901T025854Z-69555/drivetime.json
rename to inst/board/drivetime/20250901T025854Z-69555/drivetime.json
diff --git a/assets/data/drivetime/20250901T033138Z-69555/data.txt b/inst/board/drivetime/20250901T033138Z-69555/data.txt
similarity index 100%
rename from assets/data/drivetime/20250901T033138Z-69555/data.txt
rename to inst/board/drivetime/20250901T033138Z-69555/data.txt
diff --git a/assets/data/drivetime/20250901T033138Z-69555/drivetime.json b/inst/board/drivetime/20250901T033138Z-69555/drivetime.json
similarity index 100%
rename from assets/data/drivetime/20250901T033138Z-69555/drivetime.json
rename to inst/board/drivetime/20250901T033138Z-69555/drivetime.json
diff --git a/assets/data/drivetime/20250902T010120Z-69555/data.txt b/inst/board/drivetime/20250902T010120Z-69555/data.txt
similarity index 100%
rename from assets/data/drivetime/20250902T010120Z-69555/data.txt
rename to inst/board/drivetime/20250902T010120Z-69555/data.txt
diff --git a/assets/data/drivetime/20250902T010120Z-69555/drivetime.json b/inst/board/drivetime/20250902T010120Z-69555/drivetime.json
similarity index 100%
rename from assets/data/drivetime/20250902T010120Z-69555/drivetime.json
rename to inst/board/drivetime/20250902T010120Z-69555/drivetime.json
diff --git a/inst/board/drivetime/20260503T002359Z-31248/data.txt b/inst/board/drivetime/20260503T002359Z-31248/data.txt
new file mode 100644
index 00000000..f95086a7
--- /dev/null
+++ b/inst/board/drivetime/20260503T002359Z-31248/data.txt
@@ -0,0 +1,31 @@
+file: drivetime.json
+file_size: 16331
+pin_hash: 31248bb85b69f4d0
+type: json
+title: Average Drive Time to Cincinnati Children's
+description: |-
+ # Average Drive Time to Cincinnati Children's
+
+ ## About
+
+ A census tract-level measure of drive time to Cincinnati Children's Hospital Medical Center derived using 6-minute interval drive time [isochrones](https://github.com/degauss-org/drivetime?tab=readme-ov-file#geomarker-methods) obtained from [openroute service](https://classic-maps.openrouteservice.org/reach?n1=38.393339&n2=-95.339355&n3=5&b=0&i=0&j1=30&j2=15&k1=en-US&k2=km).
+
+ ## Data
+
+ Each tract-level drive time is an area-weighted average of intersecting 6-minute interval drive time isochrones calculated for the packaged 2020 census tract geographies.
+tags: ~
+urls:
+- https://github.com/geomarker-io/codec
+created: 20260503T002359Z
+api_version: 1
+user:
+ sesh:
+ r_version: R version 4.4.3 (2025-02-28)
+ platform: aarch64-apple-darwin24.2.0
+ date: 20575.0
+ loaded_packages:
+ - codec-v3.0.0
+ - testthat-v3.2.1.1
+ - sf-v1.0-19
+ - dplyr-v1.1.4
+ - colorout-v1.3-3
diff --git a/inst/board/drivetime/20260503T002359Z-31248/drivetime.json b/inst/board/drivetime/20260503T002359Z-31248/drivetime.json
new file mode 100644
index 00000000..dc3ac037
--- /dev/null
+++ b/inst/board/drivetime/20260503T002359Z-31248/drivetime.json
@@ -0,0 +1 @@
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+file: environmental_justice_index.json
+file_size: 123718
+pin_hash: 0dc9ef021429dcf2
+type: json
+title: Environmental Justice Index
+description: |-
+ # Environmental Justice Index
+
+ ## About
+
+ > The Environmental Justice Index uses data from the U.S. Census Bureau, the U.S. Environmental Protection Agency, the U.S. Mine Safety and Health Administration, and the U.S. Centers for Disease Control and Prevention to rank the cumulative impacts of environmental injustice on health for every census tract. ... The EJI ranks each tract on 36 environmental, social, and health factors and groups them into three overarching modules and ten different domains.
+
+ The ATSDR's [Environmental Justice Index (EJI)](https://www.atsdr.cdc.gov/placeandhealth/eji/index.html) was most recently released in 2024, but utilizes data from several older sources.
+ Note that although the EJI data has a `year` of 2024 in the CoDEC data package, fields in the EJI are from different sources that are each actually older.
+ Find the full documentation of the EJI in PDF form here: https://www.atsdr.cdc.gov/place-health/media/pdfs/2024/10/EJI_2024_Technical_Documentation.pdf
+
+ ## Data
+
+ - Data download from https://www.atsdr.cdc.gov/placeandhealth/eji/eji-data-download.html as a geodatabase
+ - Data fields representing "estimates" (i.e., not "percentile" or "summed ranks") selected if not available elsewhere (e.g., not American Community Survey estimates)
+ - Field names were renamed to be longer and more descriptive
+ - Although this is the 2022 release, 2010 vintage census tract geographies and identifiers are used in the EJI data
+tags: ~
+urls:
+- https://github.com/geomarker-io/codec
+created: 20260503T003413Z
+api_version: 1
+user:
+ sesh:
+ r_version: R version 4.4.3 (2025-02-28)
+ platform: aarch64-apple-darwin24.2.0
+ date: 20575.0
+ loaded_packages:
+ - dplyr-v1.1.4
+ - codec-v3.0.0
+ - testthat-v3.2.1.1
+ - colorout-v1.3-3
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diff --git a/assets/data/landcover/20250828T024022Z-5a480/data.txt b/inst/board/landcover/20250828T024022Z-5a480/data.txt
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diff --git a/inst/board/landcover/20260503T004925Z-b235f/data.txt b/inst/board/landcover/20260503T004925Z-b235f/data.txt
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--- /dev/null
+++ b/inst/board/landcover/20260503T004925Z-b235f/data.txt
@@ -0,0 +1,29 @@
+file: landcover.json
+file_size: 72937
+pin_hash: b235fe35de6c134f
+type: json
+title: Landcover, Built Environment, and Greenness
+description: |-
+ # Landcover, Built Environment, and Greenness
+
+ ## About
+
+ The National Landcover Database (NLCD) is an annual product that summarizes fraction imperviousness (fractional surface area covered with artificial substrate or structures) at a 30 m grid. The fraction imperviousness is averaged through spatial intersection with the 2020 census tract boundaries.
+
+ ## Data
+
+ Cloud-optimized GeoTIFF files are hosted on Harvard's Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KXETFC). These files were downloaded from the [Annual NLCD Product Suite](https://www.usgs.gov/centers/eros/science/annual-nlcd-product-suite) and converted from GeoTIFF to cloud-optimized GeoTIFF (COG) using `gdal_translate`.
+tags: ~
+urls:
+- https://github.com/geomarker-io/codec
+created: 20260503T004925Z
+api_version: 1
+user:
+ sesh:
+ r_version: R version 4.4.3 (2025-02-28)
+ platform: aarch64-apple-darwin24.2.0
+ date: 20575.0
+ loaded_packages:
+ - codec-v3.0.0
+ - testthat-v3.2.1.1
+ - colorout-v1.3-3
diff --git a/inst/board/landcover/20260503T004925Z-b235f/landcover.json b/inst/board/landcover/20260503T004925Z-b235f/landcover.json
new file mode 100644
index 00000000..332f10b9
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+++ b/inst/board/landcover/20260503T004925Z-b235f/landcover.json
@@ -0,0 +1 @@
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diff --git a/inst/board/traffic/20260503T010145Z-32c9c/data.txt b/inst/board/traffic/20260503T010145Z-32c9c/data.txt
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+file: traffic.json
+file_size: 30371
+pin_hash: 32c9cc0929fb590e
+type: json
+title: Average Annual Vehicle-Meters Driven
+description: |-
+ # Average Annual Vehicle-Meters Driven
+
+ ## About
+
+ Traffic is measured in AADTM or Annual Average Daily Traffic Meters, which is the average number of total meters driven by all vehicles per day when grouped into classes (trucks/buses, tractor/trailer, passenger).
+
+ For more details about the HPMS, see:
+
+ -
+ -
+ -
+
+ ## Data
+
+ 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.
+ 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 AADTM for all intersecting roads, weighted by their intersecting lengths.
+tags: ~
+urls:
+- https://github.com/geomarker-io/codec
+created: 20260503T010145Z
+api_version: 1
+user:
+ sesh:
+ r_version: R version 4.4.3 (2025-02-28)
+ platform: aarch64-apple-darwin24.2.0
+ date: 20575.0
+ loaded_packages:
+ - s2-v1.1.9
+ - dplyr-v1.1.4
+ - codec-v3.0.0
+ - testthat-v3.2.1.1
+ - colorout-v1.3-3
diff --git a/inst/board/traffic/20260503T010145Z-32c9c/traffic.json b/inst/board/traffic/20260503T010145Z-32c9c/traffic.json
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diff --git a/inst/codec_catalog/app.R b/inst/codec_catalog/app.R
index a92b7ca9..6992068d 100644
--- a/inst/codec_catalog/app.R
+++ b/inst/codec_catalog/app.R
@@ -1,62 +1,1812 @@
+app_file <- tryCatch(normalizePath(sys.frame(1)$ofile), error = function(...) {
+ ""
+})
+app_dir <- if (nzchar(app_file)) dirname(app_file) else normalizePath(getwd())
+repo_root <- normalizePath(file.path(app_dir, "..", ".."), mustWork = FALSE)
+
+if (
+ file.exists(file.path(repo_root, "DESCRIPTION")) &&
+ requireNamespace("pkgload", quietly = TRUE)
+) {
+ pkgload::load_all(
+ repo_root,
+ export_all = FALSE,
+ helpers = FALSE,
+ quiet = TRUE
+ )
+}
+
library(codec)
library(shiny)
library(bslib)
+library(leaflet)
+library(plotly)
+library(htmltools)
+library(sf)
+
+field_meta <- codec:::codec_latest_annual_fields()
+field_lookup <- split(field_meta, field_meta$field)
+dataset_meta <- codec:::codec_explorer_dataset_choices()
+dataset_lookup <- split(dataset_meta, dataset_meta$source_table)
+dataset_values <- dataset_meta$source_table
+dataset_choices <- stats::setNames(dataset_values, dataset_values)
+geography_meta <- codec:::codec_explorer_geography_choices()
+geography_lookup <- split(geography_meta, geography_meta$geography)
+numeric_fields <- field_meta$field[
+ field_meta$is_numeric & field_meta$field != "year"
+]
+defaults <- codec:::codec_explorer_defaults()
+dataset_cache <- new.env(parent = emptyenv())
-dpkgs <- readRDS("codec_latest_annual.rds")
+coalesce_string <- function(x, y) {
+ if (is.null(x) || is.na(x) || !nzchar(x)) {
+ return(y)
+ }
+ x
+}
-names(dpkgs) <- vapply(dpkgs, \(.) dpkg::dpkg_meta(.)$title, character(1))
+field_label <- function(field) {
+ field_lookup[[field]]$label[[1]]
+}
-ui <- page_sidebar(
- title = "CoDEC",
- sidebar = sidebar(
- selectInput(
- inputId = "codec_dpkg",
- label = "CoDEC Data Package",
- selected = "American Community Survey Measures",
- choices = names(dpkgs),
- selectize = FALSE,
- size = NULL
- ),
- downloadButton(
- "download_excel",
- "Download Excel",
- style = "width: 200px; padding: 3px 3px; font-size: 12px; text-align: center; background-color: #396175; color: #ffffff; border: none;"
+field_format <- function(field) {
+ field_lookup[[field]]$format[[1]]
+}
+
+dataset_title <- function(dataset) {
+ dataset_lookup[[dataset]]$source_title[[1]]
+}
+
+dataset_description <- function(dataset) {
+ dataset_lookup[[dataset]]$source_description[[1]]
+}
+
+dataset_description_summary <- function(dataset, max_chars = 420L) {
+ description <- dataset_description(dataset)
+
+ if (is.null(description) || is.na(description) || !nzchar(description)) {
+ return("No dataset description is available.")
+ }
+
+ description <- gsub("\r", "", description, fixed = TRUE)
+ if (grepl("## About", description, fixed = TRUE)) {
+ description <- sub(
+ "^.*## About\\s*",
+ "",
+ description
+ )
+ }
+ description <- sub("\\s*## .*", "", description)
+ description <- gsub("\\[([^]]+)\\]\\([^)]+\\)", "\\1", description)
+ description <- gsub("[#*_`>]", "", description)
+ description <- gsub("\\s*[-+]\\s+", " ", description)
+ description <- trimws(gsub("\\s+", " ", description))
+
+ if (nchar(description) > max_chars) {
+ description <- paste0(substr(description, 1, max_chars - 1L), "...")
+ }
+
+ description
+}
+
+catalog_url <- function() {
+ option_url <- getOption("codec.catalog_url", "")
+ env_url <- Sys.getenv("CODEC_CATALOG_URL", unset = "")
+
+ if (nzchar(option_url)) {
+ return(option_url)
+ }
+
+ if (nzchar(env_url)) {
+ return(env_url)
+ }
+
+ "https://geomarker.io/codec/articles/data.html"
+}
+
+dataset_for_field <- function(field) {
+ field_lookup[[field]]$source_table[[1]]
+}
+
+fields_for_dataset <- function(dataset) {
+ field_meta |>
+ dplyr::filter(source_table == dataset, is_numeric, field != "year") |>
+ dplyr::arrange(field) |>
+ dplyr::pull(field)
+}
+
+field_choices_for_dataset <- function(dataset) {
+ fields <- fields_for_dataset(dataset)
+ stats::setNames(fields, fields)
+}
+
+geography_values <- geography_meta$geography
+geography_choices <- stats::setNames(
+ geography_meta$geography,
+ geography_meta$label
+)
+
+geography_spec <- function(geography) {
+ geography <- codec:::codec_explorer_normalize_geography(geography)
+ geography_lookup[[geography]][1, , drop = FALSE]
+}
+
+geography_label <- function(geography) {
+ geography_spec(geography)$label[[1]]
+}
+
+format_field_value <- function(value, field) {
+ codec:::codec_explorer_field_value(value, field)
+}
+
+dataset_source_note_ui <- function(dataset) {
+ tags$div(
+ class = "codec-dataset-meta",
+ tags$div(
+ class = "codec-input-note",
+ tags$span(dataset_title(dataset))
),
- uiOutput("field_names"),
- width = "425px"
+ tags$div(
+ class = "codec-dataset-tooltip",
+ role = "tooltip",
+ tags$div(class = "codec-dataset-tooltip__eyebrow", dataset),
+ tags$div(
+ class = "codec-dataset-tooltip__title",
+ dataset_title(dataset)
+ ),
+ tags$p(dataset_description_summary(dataset)),
+ tags$a(
+ href = catalog_url(),
+ target = "_blank",
+ rel = "noopener noreferrer",
+ "Open data catalog"
+ )
+ )
+ )
+}
+
+geography_name <- function(spec, geoid) {
+ if (identical(spec$family[[1]], "neighborhood")) {
+ return(geoid)
+ }
+
+ paste(spec$family[[1]], geoid)
+}
+
+safe_ntile <- function(x, n = 3L) {
+ bins <- rep(NA_integer_, length(x))
+ keep <- !is.na(x)
+ if (!any(keep)) {
+ return(bins)
+ }
+ bins[keep] <- dplyr::ntile(x[keep], n)
+ bins
+}
+
+bivariate_palette <- matrix(
+ c(
+ "#f6edde",
+ "#e5c7ba",
+ "#c28273",
+ "#d9e3e2",
+ "#a9b9b8",
+ "#738d92",
+ "#a9c4cf",
+ "#6e93a1",
+ "#396175"
+ ),
+ nrow = 3,
+ byrow = TRUE
+)
+
+univariate_palette <- c(
+ "#f6edde",
+ "#e8d2c4",
+ "#c9a296",
+ "#789aa4",
+ "#396175"
+)
+
+legend_onclick <- function(view, x_field, y_field, bin) {
+ js_quote <- function(x) {
+ paste0("'", gsub("'", "\\\\'", x, fixed = TRUE), "'")
+ }
+ paste0(
+ "Shiny.setInputValue('legend_selection', ",
+ "{view:",
+ js_quote(view),
+ ",x:",
+ js_quote(x_field),
+ ",y:",
+ js_quote(y_field),
+ ",bin:",
+ js_quote(bin),
+ ",nonce:Date.now()}, {priority: 'event'});"
+ )
+}
+
+base_geography_sf <- function(spec) {
+ family <- spec$family[[1]]
+ vintage <- spec$vintage[[1]]
+ neighborhood_type <- spec$neighborhood_type[[1]]
+
+ if (identical(family, "tract") && identical(vintage, "2020")) {
+ return(get("cincy_tract_geo_2020", asNamespace("codec"), inherits = FALSE))
+ }
+
+ if (identical(family, "zcta") && identical(vintage, "2020")) {
+ return(
+ get("cincy_zcta_geo_2020", asNamespace("codec"), inherits = FALSE) |>
+ sf::st_as_sf(sf_column_name = "s2_geography")
+ )
+ }
+
+ if (
+ identical(family, "neighborhood") &&
+ identical(neighborhood_type, "statistical_neighborhood_approximations")
+ ) {
+ return(get(
+ "cincy_neighborhood_geo_sna",
+ asNamespace("codec"),
+ inherits = FALSE
+ ))
+ }
+
+ if (identical(family, "tract")) {
+ return(codec::cincy_census_geo("tract", vintage))
+ }
+
+ if (identical(family, "zcta")) {
+ return(codec::cincy_zcta_geo(vintage))
+ }
+
+ if (identical(family, "neighborhood")) {
+ return(codec::cincy_neighborhood_geo(neighborhood_type))
+ }
+
+ stop("Unsupported geography: ", spec$geography[[1]], call. = FALSE)
+}
+
+attach_latest_annual_values <- function(geo_sf, spec) {
+ if (
+ identical(spec$family[[1]], "tract") &&
+ identical(spec$vintage[[1]], "2020")
+ ) {
+ values <- codec::codec_latest_annual
+ idx <- match(geo_sf$geoid, values$census_tract_id_2020)
+ value_names <- setdiff(names(values), "census_tract_id_2020")
+ } else {
+ values <- codec::codec_interpolate(codec::codec_latest_annual, geo_sf)
+ idx <- match(geo_sf$geoid, values$geoid)
+ value_names <- setdiff(names(values), "geoid")
+ }
+
+ geo_sf$geo_id <- geo_sf$geoid
+ geo_sf$geo_name <- geography_name(spec, geo_sf$geoid)
+
+ for (name in value_names) {
+ geo_sf[[name]] <- values[[name]][idx]
+ }
+
+ geo_sf$geography <- spec$geography[[1]]
+ geo_sf$geography_label <- spec$label[[1]]
+
+ sf::st_transform(geo_sf, 4326)
+}
+
+build_geography_data <- function(geography) {
+ spec <- geography_spec(geography)
+ geo_sf <- base_geography_sf(spec)
+ attach_latest_annual_values(geo_sf, spec)
+}
+
+cached_geography_data <- function(geography) {
+ key <- codec:::codec_explorer_normalize_geography(geography)
+
+ if (!exists(key, envir = dataset_cache, inherits = FALSE)) {
+ assign(key, build_geography_data(key), envir = dataset_cache)
+ }
+
+ get(key, envir = dataset_cache, inherits = FALSE)
+}
+
+map_data_for_view <- function(
+ data,
+ x_field,
+ y_field,
+ view,
+ selection = NULL,
+ selected_geo_id = NULL
+) {
+ data$x_value <- data[[x_field]]
+ data$y_value <- data[[y_field]]
+ data$x_bin <- safe_ntile(data$x_value)
+ data$y_bin <- safe_ntile(data$y_value)
+
+ if (identical(view, "bivariate")) {
+ data$fill_color <- "#d7dde3"
+ keep <- !is.na(data$x_bin) & !is.na(data$y_bin)
+ data$fill_color[keep] <- vapply(
+ seq_len(sum(keep)),
+ function(i) {
+ bivariate_palette[data$y_bin[keep][i], data$x_bin[keep][i]]
+ },
+ character(1)
+ )
+ data$legend_bin <- ifelse(
+ keep,
+ paste(data$x_bin, data$y_bin, sep = "-"),
+ NA_character_
+ )
+ data$legend_title <- paste(field_label(x_field), "vs", field_label(y_field))
+ } else {
+ active_field <- if (identical(view, "x")) x_field else y_field
+ data$value_bin <- safe_ntile(data[[active_field]], 5L)
+ keep <- !is.na(data$value_bin)
+ data$fill_color <- "#d7dde3"
+ data$fill_color[keep] <- univariate_palette[data$value_bin[keep]]
+ data$legend_bin <- ifelse(
+ keep,
+ as.character(data$value_bin),
+ NA_character_
+ )
+ data$legend_title <- field_label(active_field)
+ }
+
+ selected_bin <- selection$bin %||% NA_character_
+ has_selection <- !is.null(selection) &&
+ !is.na(selected_bin) &&
+ selected_bin %in% data$legend_bin
+ data$legend_selected <- has_selection & data$legend_bin == selected_bin
+ data$geo_selected <- if (is.null(selected_geo_id)) {
+ rep(FALSE, nrow(data))
+ } else {
+ !is.na(data$geo_id) & data$geo_id == selected_geo_id
+ }
+ has_geo_selection <- any(data$geo_selected, na.rm = TRUE)
+
+ data$map_fill_opacity <- if (has_selection) {
+ ifelse(data$legend_selected, 0.95, 0.16)
+ } else if (has_geo_selection) {
+ ifelse(data$geo_selected, 0.95, 0.38)
+ } else {
+ 0.85
+ }
+ data$map_weight <- if (has_selection) {
+ ifelse(data$legend_selected, 1.7, 0.55)
+ } else if (has_geo_selection) {
+ ifelse(data$geo_selected, 2.4, 0.65)
+ } else {
+ 0.9
+ }
+ data$map_color <- if (has_selection) {
+ ifelse(data$legend_selected, "#1f2e38", "#7b858b")
+ } else if (has_geo_selection) {
+ ifelse(data$geo_selected, "#1f2e38", "#7b858b")
+ } else {
+ "#4c5961"
+ }
+
+ data$popup_html <- paste0(
+ ""
+ )
+ data
+}
+
+bucket_summary <- function(data, field, bin_column, bin) {
+ keep <- data[[bin_column]] == as.integer(bin) & !is.na(data[[field]])
+ count <- sum(keep, na.rm = TRUE)
+
+ if (!count) {
+ return(paste(field_label(field), ": no geographies"))
+ }
+
+ rng <- range(data[[field]][keep], na.rm = TRUE)
+ paste0(
+ field_label(field),
+ ": ",
+ format_field_value(rng[[1]], field),
+ " to ",
+ format_field_value(rng[[2]], field),
+ " (",
+ count,
+ " geographies)"
+ )
+}
+
+legend_detail_ui <- function(lines) {
+ tags$div(
+ class = "codec-legend__detail",
+ lapply(lines, tags$div)
+ )
+}
+
+bin_range_labels <- function(data, field, bin_column, bins) {
+ vapply(
+ bins,
+ function(bin) {
+ values <- data[[field]][data[[bin_column]] == as.integer(bin)]
+ values <- values[!is.na(values)]
+
+ if (!length(values)) {
+ return("no data")
+ }
+
+ rng <- range(values, na.rm = TRUE)
+ paste0(
+ format_field_value(rng[[1]], field),
+ " to ",
+ format_field_value(rng[[2]], field)
+ )
+ },
+ character(1)
+ )
+}
+
+map_legend_ui <- function(view, x_field, y_field, data, selection = NULL) {
+ if (identical(view, "bivariate")) {
+ cells <- unlist(
+ lapply(3:1, function(y_bin) {
+ lapply(1:3, function(x_bin) {
+ bin <- paste(x_bin, y_bin, sep = "-")
+ selected <- !is.null(selection) && identical(selection$bin, bin)
+ tags$button(
+ type = "button",
+ class = paste(
+ "codec-legend__cell",
+ if (selected) "is-selected" else NULL
+ ),
+ style = paste0("background:", bivariate_palette[y_bin, x_bin], ";"),
+ title = paste(
+ field_label(x_field),
+ "bin",
+ x_bin,
+ "and",
+ field_label(y_field),
+ "bin",
+ y_bin
+ ),
+ onclick = legend_onclick("bivariate", x_field, y_field, bin)
+ )
+ })
+ }),
+ recursive = FALSE
+ )
+
+ detail <- if (!is.null(selection) && grepl("-", selection$bin)) {
+ bins <- strsplit(selection$bin, "-", fixed = TRUE)[[1]]
+ legend_detail_ui(c(
+ bucket_summary(data, x_field, "x_bin", bins[[1]]),
+ bucket_summary(data, y_field, "y_bin", bins[[2]])
+ ))
+ } else {
+ legend_detail_ui("Select a legend cell to highlight matching geographies.")
+ }
+
+ return(tags$div(
+ class = "codec-legend codec-legend--bivariate",
+ tags$div(
+ class = "codec-legend__body",
+ tags$div(
+ class = "codec-legend__axis codec-legend__axis--y",
+ "\u2191 ",
+ field_label(y_field)
+ ),
+ tags$div(class = "codec-legend__grid", cells),
+ tags$div(
+ class = "codec-legend__axis codec-legend__axis--x",
+ field_label(x_field),
+ " \u2192"
+ )
+ ),
+ detail
+ ))
+ }
+
+ active_field <- if (identical(view, "x")) x_field else y_field
+ bins <- seq_along(univariate_palette)
+ labels <- bin_range_labels(data, active_field, "value_bin", bins)
+ cells <- lapply(bins, function(bin) {
+ selected <- !is.null(selection) && identical(selection$bin, as.character(bin))
+ tags$div(
+ class = "codec-legend__bin",
+ tags$button(
+ type = "button",
+ class = paste(
+ "codec-legend__step",
+ if (selected) "is-selected" else NULL
+ ),
+ style = paste0("background:", univariate_palette[[bin]], ";"),
+ title = paste(field_label(active_field), labels[[bin]]),
+ onclick = legend_onclick(view, x_field, y_field, as.character(bin))
+ ),
+ tags$span(class = "codec-legend__bin-label", labels[[bin]])
+ )
+ })
+
+ detail <- if (!is.null(selection)) {
+ legend_detail_ui(bucket_summary(
+ data,
+ active_field,
+ "value_bin",
+ selection$bin
+ ))
+ } else {
+ legend_detail_ui("Select a color to highlight matching geographies.")
+ }
+
+ tags$div(
+ class = "codec-legend codec-legend--univariate",
+ tags$div(class = "codec-legend__title", field_label(active_field)),
+ tags$div(class = "codec-legend__bar", cells),
+ detail
+ )
+}
+
+query_value <- function(query, name, fallback, choices = NULL) {
+ value <- coalesce_string(query[[name]], fallback)
+ if (!is.null(choices) && !(value %in% choices)) {
+ return(fallback)
+ }
+ value
+}
+
+theme <- bs_theme(
+ version = 5,
+ bg = "#f3f0eb",
+ fg = "#27485c",
+ primary = "#c28273",
+ secondary = "#8cb4c3",
+ border_radius = "0.85rem",
+ font_scale = 1
+)
+
+ui <- page_fillable(
+ theme = theme,
+ title = "CoDEC Explorer",
+ fillable_mobile = TRUE,
+ tags$head(
+ tags$script(HTML(
+ "
+ document.addEventListener('DOMContentLoaded', function() {
+ document.documentElement.classList.add('codec-booting');
+
+ document.querySelectorAll('form, input, select, textarea').forEach(function(el) {
+ el.setAttribute('autocomplete', 'off');
+ });
+
+ const pushStartupQuery = function() {
+ if (!window.Shiny || !window.Shiny.setInputValue) {
+ return false;
+ }
+
+ window.Shiny.setInputValue('startup_query', window.location.search || '', { priority: 'event' });
+ return true;
+ };
+
+ const armControls = function(event) {
+ if (!event.target.closest('.codec-controls, .codec-sidebar')) {
+ return;
+ }
+
+ if (window.Shiny && window.Shiny.setInputValue) {
+ window.Shiny.setInputValue('controls_interacted', Date.now(), { priority: 'event' });
+ }
+ };
+
+ document.addEventListener('pointerdown', armControls, true);
+ document.addEventListener('keydown', armControls, true);
+
+ ['legend_panel']
+ .forEach(function(id) {
+ const el = document.getElementById(id);
+ if (el) {
+ el.innerHTML = '';
+ }
+ });
+
+ const registerSyncHandler = function() {
+ if (!window.Shiny || !window.Shiny.addCustomMessageHandler || window.__codecSyncHandlerRegistered) {
+ return false;
+ }
+
+ window.__codecSyncHandlerRegistered = true;
+ window.Shiny.addCustomMessageHandler('codec-sync-controls', function(payload) {
+ const values = payload && payload.values ? payload.values : {};
+
+ Object.entries(values).forEach(function(entry) {
+ const id = entry[0];
+ const value = entry[1];
+ const el = document.getElementById(id);
+
+ if (!el) {
+ return;
+ }
+
+ if (el.tagName === 'SELECT') {
+ Array.from(el.options).forEach(function(option) {
+ option.selected = option.value === value;
+ });
+ }
+
+ if ('value' in el) {
+ el.value = value;
+ }
+ });
+
+ document.documentElement.classList.remove('codec-booting');
+ });
+
+ return true;
+ };
+
+ if (!registerSyncHandler()) {
+ const syncRegistrationTimer = window.setInterval(function() {
+ if (registerSyncHandler()) {
+ window.clearInterval(syncRegistrationTimer);
+ }
+ }, 50);
+
+ window.setTimeout(function() {
+ window.clearInterval(syncRegistrationTimer);
+ }, 5000);
+ }
+
+ if (!pushStartupQuery()) {
+ const startupQueryTimer = window.setInterval(function() {
+ if (pushStartupQuery()) {
+ window.clearInterval(startupQueryTimer);
+ }
+ }, 50);
+
+ window.setTimeout(function() {
+ window.clearInterval(startupQueryTimer);
+ }, 5000);
+ }
+
+ window.addEventListener('pageshow', pushStartupQuery, { once: true });
+
+ window.setTimeout(function() {
+ document.documentElement.classList.remove('codec-booting');
+ }, 4000);
+ });
+ "
+ )),
+ tags$style(HTML(
+ "
+ :root {
+ --codec-bg: #f3f0eb;
+ --codec-panel: #fffdfa;
+ --codec-ink: #27485c;
+ --codec-muted: #71828d;
+ --codec-accent: #c28273;
+ --codec-border: #d7d3cd;
+ --codec-mapline: #48545d;
+ }
+ html, body {
+ background: linear-gradient(180deg, #f7f4ef 0%, var(--codec-bg) 100%);
+ }
+ .bslib-page-fill {
+ gap: 1rem;
+ padding: 1rem;
+ }
+ .codec-booting .codec-controls,
+ .codec-booting .codec-sidebar,
+ .codec-booting .codec-map {
+ visibility: hidden;
+ }
+ .codec-shell {
+ background: var(--codec-panel);
+ border: 1px solid var(--codec-border);
+ border-radius: 1rem;
+ box-shadow: 0 18px 36px rgba(57, 97, 117, 0.08);
+ overflow: hidden;
+ }
+ .codec-header {
+ padding: 1.15rem 1.25rem;
+ border-bottom: 1px solid var(--codec-border);
+ }
+ .codec-brand {
+ display: grid;
+ gap: 0.2rem;
+ }
+ .codec-kicker {
+ color: var(--codec-accent);
+ font-size: 0.8rem;
+ letter-spacing: 0.08em;
+ text-transform: uppercase;
+ font-weight: 700;
+ }
+ .codec-title {
+ font-size: 1.3rem;
+ font-weight: 700;
+ color: var(--codec-ink);
+ line-height: 1.1;
+ }
+ .codec-subtitle {
+ color: var(--codec-muted);
+ font-size: 0.92rem;
+ }
+ .codec-controls {
+ display: grid;
+ gap: 1rem;
+ min-height: 0;
+ }
+ .codec-workspace {
+ display: grid;
+ grid-template-columns: minmax(280px, 0.34fr) minmax(0, 0.66fr);
+ min-height: 0;
+ }
+ .codec-sidebar {
+ padding: 1rem;
+ display: grid;
+ gap: 1rem;
+ min-height: 0;
+ border-right: 1px solid var(--codec-border);
+ align-content: start;
+ }
+ .codec-sidebar .shiny-input-container {
+ margin-bottom: 0;
+ }
+ .codec-field-card {
+ display: grid;
+ gap: 0.6rem;
+ padding: 0.85rem 0.9rem;
+ border: 1px solid var(--codec-border);
+ border-radius: 0.9rem;
+ background: #fcfaf7;
+ }
+ .codec-field-card__title {
+ color: var(--codec-muted);
+ font-size: 0.78rem;
+ text-transform: uppercase;
+ letter-spacing: 0.08em;
+ font-weight: 700;
+ }
+ .codec-input-note {
+ display: grid;
+ gap: 0.15rem;
+ color: var(--codec-muted);
+ font-size: 0.84rem;
+ line-height: 1.35;
+ margin-top: -0.35rem;
+ }
+ .codec-dataset-control {
+ position: relative;
+ display: grid;
+ gap: 0.6rem;
+ }
+ .codec-dataset-meta {
+ position: relative;
+ width: fit-content;
+ max-width: 100%;
+ }
+ .codec-dataset-tooltip {
+ position: absolute;
+ left: 0;
+ top: calc(100% + 0.45rem);
+ z-index: 600;
+ width: min(22rem, calc(100vw - 3rem));
+ padding: 0.85rem 0.9rem;
+ color: var(--codec-ink);
+ background: #fffdfa;
+ border: 1px solid var(--codec-border);
+ border-radius: 0.75rem;
+ box-shadow: 0 16px 32px rgba(39, 72, 92, 0.18);
+ opacity: 0;
+ pointer-events: none;
+ transform: translateY(-0.25rem);
+ transition: opacity 120ms ease, transform 120ms ease;
+ }
+ .codec-dataset-control:hover .codec-dataset-tooltip,
+ .codec-dataset-control:focus-within .codec-dataset-tooltip {
+ opacity: 1;
+ pointer-events: auto;
+ transform: translateY(0);
+ }
+ .codec-dataset-tooltip__eyebrow {
+ color: var(--codec-accent);
+ font-size: 0.72rem;
+ font-weight: 700;
+ letter-spacing: 0.08em;
+ text-transform: uppercase;
+ overflow-wrap: anywhere;
+ }
+ .codec-dataset-tooltip__title {
+ margin-top: 0.2rem;
+ color: var(--codec-ink);
+ font-weight: 700;
+ }
+ .codec-dataset-tooltip p {
+ margin: 0.45rem 0 0.65rem;
+ color: var(--codec-muted);
+ font-size: 0.86rem;
+ line-height: 1.35;
+ }
+ .codec-dataset-tooltip a {
+ color: var(--codec-accent);
+ font-size: 0.84rem;
+ font-weight: 700;
+ text-decoration: none;
+ }
+ .codec-dataset-tooltip a:hover,
+ .codec-dataset-tooltip a:focus {
+ text-decoration: underline;
+ }
+ .codec-map {
+ padding: 1rem;
+ display: grid;
+ gap: 0.8rem;
+ min-height: 0;
+ }
+ .codec-map__frame {
+ min-height: 520px;
+ }
+ .codec-note {
+ color: var(--codec-muted);
+ font-size: 0.92rem;
+ line-height: 1.45;
+ }
+ .codec-link {
+ color: var(--codec-accent);
+ text-decoration: none;
+ font-weight: 700;
+ }
+ .codec-popup__title {
+ font-weight: 700;
+ margin-bottom: 0.3rem;
+ color: var(--codec-ink);
+ }
+ .codec-legend {
+ display: flex;
+ flex-wrap: wrap;
+ gap: 0.8rem 1rem;
+ align-content: start;
+ align-items: end;
+ border-top: 1px solid var(--codec-border);
+ padding-top: 0.8rem;
+ }
+ .codec-legend__title {
+ font-size: 0.82rem;
+ text-transform: uppercase;
+ letter-spacing: 0.08em;
+ color: var(--codec-muted);
+ font-weight: 700;
+ }
+ .codec-legend__axis {
+ font-size: 0.84rem;
+ color: var(--codec-muted);
+ }
+ .codec-legend__body {
+ display: grid;
+ gap: 0.3rem;
+ width: max-content;
+ }
+ .codec-legend__grid {
+ display: grid;
+ grid-template-columns: repeat(3, 1fr);
+ gap: 0.18rem;
+ width: 5.5rem;
+ }
+ .codec-legend__cell {
+ display: block;
+ aspect-ratio: 1;
+ border-radius: 0.2rem;
+ border: 2px solid transparent;
+ cursor: pointer;
+ padding: 0;
+ }
+ .codec-legend__bar {
+ display: grid;
+ grid-template-columns: repeat(5, 1fr);
+ gap: 0.32rem;
+ min-width: min(100%, 32rem);
+ max-width: 42rem;
+ }
+ .codec-legend__bin {
+ display: grid;
+ gap: 0.25rem;
+ min-width: 0;
+ }
+ .codec-legend__step {
+ display: block;
+ height: 0.85rem;
+ border-radius: 999px;
+ border: 2px solid transparent;
+ cursor: pointer;
+ padding: 0;
+ }
+ .codec-legend__bin-label {
+ color: var(--codec-muted);
+ font-size: 0.68rem;
+ line-height: 1.15;
+ overflow-wrap: anywhere;
+ }
+ .codec-legend__cell.is-selected,
+ .codec-legend__step.is-selected {
+ border-color: #1f2e38;
+ box-shadow: 0 0 0 2px rgba(255, 253, 250, 0.95);
+ }
+ .codec-legend__detail {
+ color: var(--codec-muted);
+ font-size: 0.86rem;
+ line-height: 1.35;
+ max-width: 34rem;
+ }
+ .codec-histogram {
+ border-top: 1px solid var(--codec-border);
+ padding-top: 0.8rem;
+ }
+ .codec-histogram__title {
+ color: var(--codec-muted);
+ font-size: 0.82rem;
+ font-weight: 700;
+ letter-spacing: 0.08em;
+ text-transform: uppercase;
+ margin-bottom: 0.35rem;
+ }
+ .form-label {
+ color: var(--codec-ink);
+ font-weight: 700;
+ margin-bottom: 0.35rem;
+ }
+ .leaflet-container {
+ border-radius: 0.9rem;
+ overflow: hidden;
+ }
+ @media (max-width: 920px) {
+ .codec-header > .bslib-grid {
+ grid-template-columns: minmax(0, 1fr) !important;
+ }
+ .codec-workspace {
+ grid-template-columns: minmax(0, 1fr) !important;
+ }
+ .codec-sidebar {
+ border-right: 0;
+ border-bottom: 1px solid var(--codec-border);
+ }
+ .codec-map__frame {
+ min-height: 460px;
+ }
+ }
+ .plotly .modebar {
+ top: 8px;
+ right: 8px;
+ }
+ "
+ ))
),
- uiOutput("codec_dpkg_desc")
+ div(
+ class = "codec-shell",
+ div(
+ class = "codec-header",
+ layout_columns(
+ col_widths = c(5, 7),
+ div(
+ class = "codec-brand",
+ tags$div(
+ class = "codec-kicker",
+ "Community Data Explorer for Cincinnati"
+ ),
+ tags$div(class = "codec-title", "CoDEC Latest Annual Explorer"),
+ tags$div(
+ class = "codec-subtitle",
+ paste("CoDEC version", utils::packageVersion("codec"))
+ )
+ ),
+ div(
+ class = "codec-controls",
+ layout_columns(
+ col_widths = c(7, 3, 2),
+ selectInput(
+ "geography_control",
+ "Geography",
+ choices = geography_choices,
+ selected = defaults$geography
+ ),
+ selectInput(
+ "view_control",
+ "Map view",
+ choices = c(
+ "Bivariate" = "bivariate",
+ "X variable" = "x",
+ "Y variable" = "y"
+ ),
+ selected = defaults$view
+ ),
+ actionButton(
+ "reset_controls",
+ "Reset",
+ class = "btn btn-outline-secondary"
+ )
+ )
+ )
+ )
+ ),
+ div(
+ class = "codec-workspace",
+ div(
+ class = "codec-sidebar",
+ div(
+ class = "codec-field-card",
+ tags$div(class = "codec-field-card__title", "X"),
+ div(
+ class = "codec-dataset-control",
+ selectInput(
+ "x_dataset_control",
+ "Dataset",
+ choices = dataset_choices,
+ selected = dataset_for_field(defaults$x)
+ ),
+ uiOutput("x_source_note")
+ ),
+ selectInput(
+ "x_var_control",
+ "Variable",
+ choices = field_choices_for_dataset(dataset_for_field(defaults$x)),
+ selected = defaults$x
+ )
+ ),
+ div(
+ class = "codec-field-card",
+ tags$div(class = "codec-field-card__title", "Y"),
+ div(
+ class = "codec-dataset-control",
+ selectInput(
+ "y_dataset_control",
+ "Dataset",
+ choices = dataset_choices,
+ selected = dataset_for_field(defaults$y)
+ ),
+ uiOutput("y_source_note")
+ ),
+ selectInput(
+ "y_var_control",
+ "Variable",
+ choices = field_choices_for_dataset(dataset_for_field(defaults$y)),
+ selected = defaults$y
+ )
+ )
+ ),
+ div(
+ class = "codec-map",
+ div(class = "codec-map__frame", leafletOutput("map", height = "100%")),
+ uiOutput("legend_panel"),
+ uiOutput("map_detail_panel")
+ )
+ )
+ )
)
-server <- function(input, output) {
- codec_dpkg <- reactive(dpkgs[[input$codec_dpkg]])
+server <- function(input, output, session) {
+ dataset_values <- dataset_meta$source_table
+ dataset_choices <- stats::setNames(dataset_values, dataset_values)
+ default_state <- list(
+ geography = defaults$geography,
+ view = defaults$view,
+ x_dataset = dataset_for_field(defaults$x),
+ x = defaults$x,
+ y_dataset = dataset_for_field(defaults$y),
+ y = defaults$y
+ )
+
+ app_state <- reactiveVal(default_state)
+ app_started <- reactiveVal(FALSE)
+ ui_ready <- reactiveVal(FALSE)
+ controls_live <- reactiveVal(FALSE)
+ controls_interacted <- reactiveVal(FALSE)
+ last_query <- reactiveVal(NULL)
+ selected_legend <- reactiveVal(NULL)
+ selected_geography <- reactiveVal(NULL)
+ control_id <- function(name) {
+ switch(
+ name,
+ geography = "geography_control",
+ view = "view_control",
+ reset_controls = "reset_controls",
+ x_dataset = "x_dataset_control",
+ x_var = "x_var_control",
+ y_dataset = "y_dataset_control",
+ y_var = "y_var_control",
+ name
+ )
+ }
+
+ normalize_state <- function(state) {
+ state$geography <- codec:::codec_explorer_normalize_geography(
+ state$geography
+ )
+ if (!(state$geography %in% geography_values)) {
+ state$geography <- default_state$geography
+ }
+
+ if (!(state$view %in% c("bivariate", "x", "y"))) {
+ state$view <- default_state$view
+ }
+
+ if (is.null(state$x_dataset) || !(state$x_dataset %in% dataset_values)) {
+ state$x_dataset <- default_state$x_dataset
+ }
+
+ if (is.null(state$y_dataset) || !(state$y_dataset %in% dataset_values)) {
+ state$y_dataset <- default_state$y_dataset
+ }
+
+ x_fields <- fields_for_dataset(state$x_dataset)
+ y_fields <- fields_for_dataset(state$y_dataset)
+
+ if (!(state$x %in% x_fields)) {
+ state$x <- if (default_state$x %in% x_fields) {
+ default_state$x
+ } else {
+ x_fields[[1]]
+ }
+ }
+
+ if (!(state$y %in% y_fields)) {
+ state$y <- if (default_state$y %in% y_fields) {
+ default_state$y
+ } else {
+ y_fields[[1]]
+ }
+ }
+
+ state
+ }
+
+ state_query <- function(state) {
+ paste0(
+ "?x=",
+ utils::URLencode(state$x, reserved = TRUE),
+ "&y=",
+ utils::URLencode(state$y, reserved = TRUE),
+ "&geography=",
+ utils::URLencode(state$geography, reserved = TRUE),
+ "&view=",
+ utils::URLencode(state$view, reserved = TRUE)
+ )
+ }
+
+ set_state <- function(state) {
+ state <- normalize_state(state)
+ if (!identical(state, app_state())) {
+ selected_legend(NULL)
+ selected_geography(NULL)
+ app_state(state)
+ }
+ }
+
+ control_values_from_state <- function(state) {
+ x_choices <- field_choices_for_dataset(state$x_dataset)
+ y_choices <- field_choices_for_dataset(state$y_dataset)
+
+ list(
+ geography = state$geography,
+ view = state$view,
+ x_dataset = state$x_dataset,
+ x_var = state$x,
+ x_choices = x_choices,
+ y_dataset = state$y_dataset,
+ y_var = state$y,
+ y_choices = y_choices
+ )
+ }
+
+ sync_controls_from_values <- function(values) {
+ shiny::updateSelectInput(
+ session,
+ control_id("geography"),
+ choices = geography_choices,
+ selected = values$geography
+ )
+ shiny::updateSelectInput(
+ session,
+ control_id("view"),
+ selected = values$view
+ )
+
+ shiny::updateSelectInput(
+ session,
+ control_id("x_dataset"),
+ choices = dataset_choices,
+ selected = values$x_dataset
+ )
+ shiny::updateSelectInput(
+ session,
+ control_id("x_var"),
+ choices = values$x_choices,
+ selected = values$x_var
+ )
+
+ shiny::updateSelectInput(
+ session,
+ control_id("y_dataset"),
+ choices = dataset_choices,
+ selected = values$y_dataset
+ )
+ shiny::updateSelectInput(
+ session,
+ control_id("y_var"),
+ choices = values$y_choices,
+ selected = values$y_var
+ )
+
+ session$sendCustomMessage(
+ "codec-sync-controls",
+ list(values = stats::setNames(
+ list(
+ values$geography,
+ values$view,
+ values$x_dataset,
+ values$x_var,
+ values$y_dataset,
+ values$y_var
+ ),
+ c(
+ control_id("geography"),
+ control_id("view"),
+ control_id("x_dataset"),
+ control_id("x_var"),
+ control_id("y_dataset"),
+ control_id("y_var")
+ )
+ ))
+ )
+ }
+
+ queue_control_sync <- function(values, delays = c(0, 0.35, 1)) {
+ for (delay in delays) {
+ later::later(
+ function() {
+ sync_controls_from_values(values)
+ },
+ delay = delay
+ )
+ }
+ }
+
+ initialize_from_query <- function(query_string = "") {
+ query <- shiny::parseQueryString(query_string %||% "")
+ x_field <- query_value(query, "x", defaults$x, choices = numeric_fields)
+ y_field <- query_value(query, "y", defaults$y, choices = numeric_fields)
+
+ state <- normalize_state(list(
+ geography = coalesce_string(
+ query[["geography"]],
+ default_state$geography
+ ),
+ view = query_value(
+ query,
+ "view",
+ default_state$view,
+ choices = c("bivariate", "x", "y")
+ ),
+ x_dataset = dataset_for_field(x_field),
+ x = x_field,
+ y_dataset = dataset_for_field(y_field),
+ y = y_field
+ ))
+
+ app_state(state)
+ canonical_query <- state_query(state)
+ last_query(canonical_query)
+ app_started(TRUE)
+ ui_ready(FALSE)
+ controls_live(FALSE)
+ controls_interacted(FALSE)
+ startup_values <- control_values_from_state(state)
+
+ session$onFlushed(
+ function() {
+ shiny::updateQueryString(
+ canonical_query,
+ mode = "replace",
+ session = session
+ )
+ later::later(
+ function() {
+ ui_ready(TRUE)
+ queue_control_sync(startup_values, c(0.15, 0.6, 1.1))
+ },
+ delay = 1
+ )
+ later::later(
+ function() {
+ controls_live(TRUE)
+ },
+ delay = 1.5
+ )
+ },
+ once = TRUE
+ )
+ }
+
+ observeEvent(
+ input$startup_query,
+ {
+ initialize_from_query(input$startup_query %||% "")
+ },
+ once = TRUE,
+ ignoreInit = FALSE,
+ ignoreNULL = TRUE
+ )
+
+ observeEvent(
+ input$controls_interacted,
+ {
+ if (isTRUE(app_started()) && isTRUE(controls_live())) {
+ controls_interacted(TRUE)
+ }
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input[[control_id("geography")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ geography <- codec:::codec_explorer_normalize_geography(input[[control_id(
+ "geography"
+ )]])
+ if (
+ !(geography %in% geography_values) ||
+ identical(geography, state$geography)
+ ) {
+ return()
+ }
+ state$geography <- geography
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input[[control_id("view")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ if (identical(input[[control_id("view")]], state$view)) {
+ return()
+ }
+ state$view <- input[[control_id("view")]]
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
- output$download_excel <-
- downloadHandler(
- filename = function() {
- paste0(
- "CoDEC-",
- dpkg::dpkg_meta(codec_dpkg())$name,
- "-v",
- dpkg::dpkg_meta(codec_dpkg())$version,
- ".xlsx"
+ observeEvent(
+ input[[control_id("x_dataset")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ if (identical(input[[control_id("x_dataset")]], state$x_dataset)) {
+ return()
+ }
+ state$x_dataset <- input[[control_id("x_dataset")]]
+ state$x <- fields_for_dataset(state$x_dataset)[[1]]
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input[[control_id("y_dataset")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ if (identical(input[[control_id("y_dataset")]], state$y_dataset)) {
+ return()
+ }
+ state$y_dataset <- input[[control_id("y_dataset")]]
+ state$y <- fields_for_dataset(state$y_dataset)[[1]]
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input[[control_id("x_var")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ if (
+ !(input[[control_id("x_var")]] %in% numeric_fields) ||
+ identical(input[[control_id("x_var")]], state$x)
+ ) {
+ return()
+ }
+ state$x <- input[[control_id("x_var")]]
+ state$x_dataset <- dataset_for_field(input[[control_id("x_var")]])
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input[[control_id("y_var")]],
+ {
+ if (!isTRUE(app_started()) || !isTRUE(controls_live()) || !isTRUE(controls_interacted())) {
+ return()
+ }
+ state <- app_state()
+ if (
+ !(input[[control_id("y_var")]] %in% numeric_fields) ||
+ identical(input[[control_id("y_var")]], state$y)
+ ) {
+ return()
+ }
+ state$y <- input[[control_id("y_var")]]
+ state$y_dataset <- dataset_for_field(input[[control_id("y_var")]])
+ set_state(state)
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(input[[control_id("reset_controls")]], {
+ controls_live(FALSE)
+ controls_interacted(TRUE)
+ selected_legend(NULL)
+ selected_geography(NULL)
+ app_state(default_state)
+ last_query(NULL)
+ reset_values <- control_values_from_state(default_state)
+ later::later(
+ function() {
+ queue_control_sync(reset_values, c(0, 0.25, 0.75))
+ controls_live(TRUE)
+ },
+ delay = 0.25
+ )
+ })
+
+ observeEvent(
+ input$legend_selection,
+ {
+ selection <- input$legend_selection
+ if (
+ is.null(selection$view) ||
+ is.null(selection$x) ||
+ is.null(selection$y) ||
+ is.null(selection$bin)
+ ) {
+ return()
+ }
+
+ next_selection <- list(
+ view = selection$view,
+ x = selection$x,
+ y = selection$y,
+ bin = selection$bin
+ )
+
+ if (identical(selected_legend(), next_selection)) {
+ selected_legend(NULL)
+ } else {
+ selected_geography(NULL)
+ selected_legend(next_selection)
+ }
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ input$map_shape_click,
+ {
+ click <- input$map_shape_click
+ if (is.null(click$id) || !nzchar(click$id)) {
+ return()
+ }
+
+ if (identical(selected_geography(), click$id)) {
+ selected_geography(NULL)
+ } else {
+ selected_legend(NULL)
+ selected_geography(click$id)
+ }
+ },
+ ignoreInit = TRUE
+ )
+
+ observeEvent(
+ app_state(),
+ {
+ if (!isTRUE(app_started())) {
+ return()
+ }
+
+ state <- app_state()
+ query <- state_query(state)
+ if (!identical(query, last_query())) {
+ last_query(query)
+ shiny::updateQueryString(
+ query,
+ mode = "replace",
+ session = session
)
+ }
+ },
+ ignoreInit = TRUE
+ )
+
+ observe({
+ req(app_started())
+ req(ui_ready())
+ values <- control_values_from_state(app_state())
+ session$onFlushed(
+ function() {
+ queue_control_sync(values, c(0, 0.2))
},
- content = function(file) writexl::write_xlsx(codec_dpkg(), path = file)
+ once = TRUE
+ )
+ })
+
+ current_state <- reactive({
+ req(app_started())
+ req(ui_ready())
+ state <- app_state()
+ list(
+ geography = state$geography,
+ view = state$view,
+ x = state$x,
+ y = state$y
+ )
+ })
+
+ base_data <- reactive({
+ req(app_started())
+ req(ui_ready())
+ cached_geography_data(current_state()$geography)
+ })
+
+ active_legend_selection <- reactive({
+ selection <- selected_legend()
+ state <- current_state()
+
+ if (
+ is.null(selection) ||
+ !identical(selection$view, state$view) ||
+ !identical(selection$x, state$x) ||
+ !identical(selection$y, state$y)
+ ) {
+ return(NULL)
+ }
+
+ selection
+ })
+
+ legend_data <- reactive({
+ map_data_for_view(
+ base_data(),
+ current_state()$x,
+ current_state()$y,
+ current_state()$view
+ )
+ })
+
+ map_data <- reactive({
+ map_data_for_view(
+ base_data(),
+ current_state()$x,
+ current_state()$y,
+ current_state()$view,
+ active_legend_selection(),
+ selected_geography()
+ )
+ })
+
+ output$x_source_note <- renderUI({
+ req(ui_ready())
+ dataset_source_note_ui(app_state()$x_dataset)
+ })
+
+ output$y_source_note <- renderUI({
+ req(ui_ready())
+ dataset_source_note_ui(app_state()$y_dataset)
+ })
+
+ output$legend_panel <- renderUI({
+ req(ui_ready())
+ map_legend_ui(
+ current_state()$view,
+ current_state()$x,
+ current_state()$y,
+ legend_data(),
+ active_legend_selection()
)
+ })
+
+ output$map_detail_panel <- renderUI({
+ req(ui_ready())
+ state <- current_state()
+
+ if (identical(state$view, "bivariate")) {
+ return(NULL)
+ }
+
+ active_field <- if (identical(state$view, "x")) state$x else state$y
+ tags$div(
+ class = "codec-histogram",
+ tags$div(
+ class = "codec-histogram__title",
+ paste(field_label(active_field), "distribution")
+ ),
+ plotlyOutput("histogram", height = "190px")
+ )
+ })
+
+ output$histogram <- renderPlotly({
+ req(ui_ready())
+ state <- current_state()
+ req(!identical(state$view, "bivariate"))
- output$field_names <-
- renderUI({
- tibble::tibble(`Field Names` = names(codec_dpkg())) |>
- knitr::kable() |>
- markdown::markdownToHTML(fragment.only = TRUE) |>
- HTML()
- })
+ active_field <- if (identical(state$view, "x")) state$x else state$y
+ dat <- legend_data() |>
+ sf::st_drop_geometry() |>
+ dplyr::mutate(value = .data[[active_field]]) |>
+ dplyr::filter(!is.na(.data$value), !is.na(.data$value_bin))
- output$codec_dpkg_desc <- renderUI({
- attr(codec_dpkg(), "description") |>
- markdown::markdownToHTML(fragment.only = TRUE) |>
- HTML()
+ bins <- seq_along(univariate_palette)
+ bin_ranges <- lapply(
+ bins,
+ function(bin) {
+ values <- dat$value[dat$value_bin == bin]
+ if (!length(values)) {
+ return(c(NA_real_, NA_real_))
+ }
+ range(values, na.rm = TRUE)
+ }
+ )
+
+ shapes <- lapply(
+ bins,
+ function(bin) {
+ rng <- bin_ranges[[bin]]
+ if (any(is.na(rng))) {
+ return(NULL)
+ }
+ list(
+ type = "rect",
+ xref = "x",
+ yref = "paper",
+ x0 = rng[[1]],
+ x1 = rng[[2]],
+ y0 = 0,
+ y1 = 1,
+ fillcolor = univariate_palette[[bin]],
+ opacity = 0.16,
+ line = list(width = 0),
+ layer = "below"
+ )
+ }
+ )
+ shapes <- Filter(Negate(is.null), shapes)
+
+ selected_geo_id <- selected_geography()
+ selected <- active_legend_selection()
+ if (!is.null(selected_geo_id)) {
+ selected_dat <- dat |>
+ dplyr::filter(.data$geo_id == selected_geo_id)
+ selected_name <- if (nrow(selected_dat)) {
+ selected_dat$geo_name[[1]]
+ } else {
+ "Selected geography"
+ }
+ } else if (!is.null(selected)) {
+ selected_dat <- dat |>
+ dplyr::filter(.data$value_bin == as.integer(selected$bin))
+ selected_name <- paste("Selected bin", selected$bin)
+ } else {
+ selected_dat <- dat[0, , drop = FALSE]
+ selected_name <- "Selected"
+ }
+
+ plot <- plotly::plot_ly(
+ data = dat,
+ x = ~value,
+ type = "histogram",
+ name = "All geographies",
+ hoverinfo = "x+y",
+ nbinsx = 28,
+ marker = list(
+ color = "#8cb4c3",
+ opacity = 0.72,
+ line = list(color = "#fffdfa", width = 0.5)
+ )
+ )
+
+ if (nrow(selected_dat)) {
+ plot <- plot |>
+ plotly::add_markers(
+ data = selected_dat,
+ x = ~value,
+ y = rep(0, nrow(selected_dat)),
+ inherit = FALSE,
+ name = selected_name,
+ text = ~paste0(
+ geo_name,
+ "
",
+ field_label(active_field),
+ ": ",
+ format_field_value(value, active_field)
+ ),
+ hoverinfo = "text",
+ marker = list(
+ color = "#c28273",
+ size = if (nrow(selected_dat) == 1) 12 else 8,
+ symbol = "triangle-up",
+ line = list(color = "#1f2e38", width = 1)
+ )
+ )
+ }
+
+ plot |>
+ plotly::layout(
+ margin = list(l = 42, r = 16, t = 8, b = 44),
+ paper_bgcolor = "#fffdfa",
+ plot_bgcolor = "#fffdfa",
+ xaxis = list(title = field_label(active_field), fixedrange = TRUE),
+ yaxis = list(title = "geographies", fixedrange = TRUE),
+ bargap = 0.04,
+ shapes = shapes,
+ showlegend = nrow(selected_dat) > 0
+ ) |>
+ plotly::config(displaylogo = FALSE)
+ })
+
+ output$map <- renderLeaflet({
+ req(ui_ready())
+ dat <- map_data()
+ bounds <- sf::st_bbox(dat)
+ center_lng <- unname(mean(c(bounds["xmin"], bounds["xmax"])))
+ center_lat <- unname(mean(c(bounds["ymin"], bounds["ymax"])))
+
+ leaflet::leaflet(
+ dat,
+ options = leaflet::leafletOptions(zoomControl = TRUE)
+ ) |>
+ leaflet::addProviderTiles("CartoDB.Positron") |>
+ leaflet::setView(lng = center_lng, lat = center_lat, zoom = 10) |>
+ leaflet::addPolygons(
+ layerId = ~geo_id,
+ color = ~map_color,
+ weight = ~map_weight,
+ opacity = 0.75,
+ fillColor = ~fill_color,
+ fillOpacity = ~map_fill_opacity,
+ smoothFactor = 0.2,
+ popup = ~popup_html,
+ label = ~geo_name,
+ highlightOptions = leaflet::highlightOptions(
+ weight = 2.2,
+ color = "#1f2e38",
+ bringToFront = TRUE
+ )
+ )
})
}
diff --git a/inst/codec_catalog/manifest.json b/inst/codec_catalog/manifest.json
new file mode 100644
index 00000000..d7310fb5
--- /dev/null
+++ b/inst/codec_catalog/manifest.json
@@ -0,0 +1,3316 @@
+{
+ "version": 1,
+ "locale": "en_US",
+ "platform": "4.4.3",
+ "metadata": {
+ "appmode": "shiny",
+ "primary_rmd": null,
+ "primary_html": null,
+ "content_category": null,
+ "has_parameters": false
+ },
+ "packages": {
+ "DBI": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "DBI",
+ "Title": "R Database Interface",
+ "Version": "1.2.3",
+ "Date": "2024-06-02",
+ "Authors@R": "c(\n person(\"R Special Interest Group on Databases (R-SIG-DB)\", role = \"aut\"),\n person(\"Hadley\", \"Wickham\", role = \"aut\"),\n person(\"Kirill\", \"Müller\", , \"kirill@cynkra.com\", role = c(\"aut\", \"cre\"),\n comment = c(ORCID = \"0000-0002-1416-3412\")),\n person(\"R Consortium\", role = \"fnd\")\n )",
+ "Description": "A database interface definition for communication between R\n and relational database management systems. All classes in this\n package are virtual and need to be extended by the various R/DBMS\n implementations.",
+ "License": "LGPL (>= 2.1)",
+ "URL": "https://dbi.r-dbi.org, https://github.com/r-dbi/DBI",
+ "BugReports": "https://github.com/r-dbi/DBI/issues",
+ "Depends": "methods, R (>= 3.0.0)",
+ "Suggests": "arrow, blob, covr, DBItest, dbplyr, downlit, dplyr, glue,\nhms, knitr, magrittr, nanoarrow (>= 0.3.0.1), RMariaDB,\nrmarkdown, rprojroot, RSQLite (>= 1.1-2), testthat (>= 3.0.0),\nvctrs, xml2",
+ "VignetteBuilder": "knitr",
+ "Config/autostyle/scope": "line_breaks",
+ "Config/autostyle/strict": "false",
+ "Config/Needs/check": "r-dbi/DBItest",
+ "Encoding": "UTF-8",
+ "RoxygenNote": "7.3.1",
+ "Config/Needs/website": "r-dbi/DBItest, r-dbi/dbitemplate, adbi,\nAzureKusto, bigrquery, DatabaseConnector, dittodb, duckdb,\nimplyr, lazysf, odbc, pool, RAthena, IMSMWU/RClickhouse, RH2,\nRJDBC, RMariaDB, RMySQL, RPostgres, RPostgreSQL, RPresto,\nRSQLite, sergeant, sparklyr, withr",
+ "Config/testthat/edition": "3",
+ "NeedsCompilation": "no",
+ "Packaged": "2024-06-02 20:26:05 UTC; kirill",
+ "Author": "R Special Interest Group on Databases (R-SIG-DB) [aut],\n Hadley Wickham [aut],\n Kirill Müller [aut, cre] (),\n R Consortium [fnd]",
+ "Maintainer": "Kirill Müller ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-06-02 21:50:02 UTC",
+ "Built": "R 4.4.0; ; 2024-07-29 15:30:13 UTC; unix"
+ }
+ },
+ "KernSmooth": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "KernSmooth",
+ "Priority": "recommended",
+ "Version": "2.23-26",
+ "Date": "2024-12-10",
+ "Title": "Functions for Kernel Smoothing Supporting Wand & Jones (1995)",
+ "Authors@R": "c(person(\"Matt\", \"Wand\", role = \"aut\",\n\t email = \"Matt.Wand@uts.edu.au\"),\n\t person(\"Cleve\", \"Moler\", role = \"ctb\",\n\t comment = \"LINPACK routines in src/d*\"),\n person(\"Brian\", \"Ripley\", role = c(\"trl\", \"cre\", \"ctb\"),\n email = \"Brian.Ripley@R-project.org\",\n\t\t comment = \"R port and updates\"))",
+ "Note": "Maintainers are not available to give advice on using a package\nthey did not author.",
+ "Depends": "R (>= 2.5.0), stats",
+ "Suggests": "MASS, carData",
+ "Description": "Functions for kernel smoothing (and density estimation)\n corresponding to the book: \n Wand, M.P. and Jones, M.C. (1995) \"Kernel Smoothing\".",
+ "License": "Unlimited",
+ "ByteCompile": "yes",
+ "NeedsCompilation": "yes",
+ "Packaged": "2024-12-10 15:33:25 UTC; ripley",
+ "Author": "Matt Wand [aut],\n Cleve Moler [ctb] (LINPACK routines in src/d*),\n Brian Ripley [trl, cre, ctb] (R port and updates)",
+ "Maintainer": "Brian Ripley ",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-01-01 10:25:36 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-02-28 11:23:17 UTC; unix"
+ }
+ },
+ "MASS": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "MASS",
+ "Priority": "recommended",
+ "Version": "7.3-61",
+ "Date": "2024-06-10",
+ "Revision": "$Rev: 3657 $",
+ "Depends": "R (>= 4.4.0), grDevices, graphics, stats, utils",
+ "Imports": "methods",
+ "Suggests": "lattice, nlme, nnet, survival",
+ "Authors@R": "c(person(\"Brian\", \"Ripley\", role = c(\"aut\", \"cre\", \"cph\"),\n email = \"ripley@stats.ox.ac.uk\"),\n\t person(\"Bill\", \"Venables\", role = c(\"aut\", \"cph\")),\n\t person(c(\"Douglas\", \"M.\"), \"Bates\", role = \"ctb\"),\n\t person(\"Kurt\", \"Hornik\", role = \"trl\",\n comment = \"partial port ca 1998\"),\n\t person(\"Albrecht\", \"Gebhardt\", role = \"trl\",\n comment = \"partial port ca 1998\"),\n\t person(\"David\", \"Firth\", role = \"ctb\",\n\t comment = \"support functions for polr\"))",
+ "Description": "Functions and datasets to support Venables and Ripley,\n \"Modern Applied Statistics with S\" (4th edition, 2002).",
+ "Title": "Support Functions and Datasets for Venables and Ripley's MASS",
+ "LazyData": "yes",
+ "ByteCompile": "yes",
+ "License": "GPL-2 | GPL-3",
+ "URL": "http://www.stats.ox.ac.uk/pub/MASS4/",
+ "Contact": "",
+ "NeedsCompilation": "yes",
+ "Packaged": "2024-06-13 08:23:32 UTC; ripley",
+ "Author": "Brian Ripley [aut, cre, cph],\n Bill Venables [aut, cph],\n Douglas M. Bates [ctb],\n Kurt Hornik [trl] (partial port ca 1998),\n Albrecht Gebhardt [trl] (partial port ca 1998),\n David Firth [ctb] (support functions for polr)",
+ "Maintainer": "Brian Ripley ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-06-13 10:23:32",
+ "Built": "R 4.4.1; aarch64-apple-darwin23.4.0; 2024-07-29 20:49:51 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "MASS",
+ "RemoteRef": "MASS",
+ "RemoteRepos": "https://cran.rstudio.com/",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "7.3-61"
+ }
+ },
+ "R6": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "R6",
+ "Title": "Encapsulated Classes with Reference Semantics",
+ "Version": "2.5.1",
+ "Authors@R": "person(\"Winston\", \"Chang\", role = c(\"aut\", \"cre\"), email = \"winston@stdout.org\")",
+ "Description": "Creates classes with reference semantics, similar to R's built-in\n reference classes. Compared to reference classes, R6 classes are simpler\n and lighter-weight, and they are not built on S4 classes so they do not\n require the methods package. These classes allow public and private\n members, and they support inheritance, even when the classes are defined in\n different packages.",
+ "Depends": "R (>= 3.0)",
+ "Suggests": "testthat, pryr",
+ "License": "MIT + file LICENSE",
+ "URL": "https://r6.r-lib.org, https://github.com/r-lib/R6/",
+ "BugReports": "https://github.com/r-lib/R6/issues",
+ "RoxygenNote": "7.1.1",
+ "NeedsCompilation": "no",
+ "Packaged": "2021-08-06 20:18:46 UTC; winston",
+ "Author": "Winston Chang [aut, cre]",
+ "Maintainer": "Winston Chang ",
+ "Repository": "CRAN",
+ "Date/Publication": "2021-08-19 14:00:05 UTC",
+ "Built": "R 4.4.0; ; 2024-05-12 14:22:02 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "R6",
+ "RemoteRef": "R6",
+ "RemoteRepos": "https://cran.rstudio.com/",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "2.5.1"
+ }
+ },
+ "RColorBrewer": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "RColorBrewer",
+ "Version": "1.1-3",
+ "Date": "2022-04-03",
+ "Title": "ColorBrewer Palettes",
+ "Authors@R": "c(person(given = \"Erich\", family = \"Neuwirth\", role = c(\"aut\",\n \"cre\"), email = \"erich.neuwirth@univie.ac.at\"))",
+ "Author": "Erich Neuwirth [aut, cre]",
+ "Maintainer": "Erich Neuwirth ",
+ "Depends": "R (>= 2.0.0)",
+ "Description": "Provides color schemes for maps (and other graphics)\n designed by Cynthia Brewer as described at http://colorbrewer2.org.",
+ "License": "Apache License 2.0",
+ "Packaged": "2022-04-03 10:26:20 UTC; neuwirth",
+ "NeedsCompilation": "no",
+ "Repository": "CRAN",
+ "Date/Publication": "2022-04-03 19:20:13 UTC",
+ "Built": "R 4.4.0; ; 2024-05-16 13:36:09 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "RColorBrewer",
+ "RemoteRef": "RColorBrewer",
+ "RemoteRepos": "https://cran.rstudio.com/",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "1.1-3"
+ }
+ },
+ "Rcpp": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "Rcpp",
+ "Title": "Seamless R and C++ Integration",
+ "Version": "1.0.14",
+ "Date": "2025-01-11",
+ "Authors@R": "c(person(\"Dirk\", \"Eddelbuettel\", role = c(\"aut\", \"cre\"), email = \"edd@debian.org\",\n comment = c(ORCID = \"0000-0001-6419-907X\")),\n person(\"Romain\", \"Francois\", role = \"aut\",\n comment = c(ORCID = \"0000-0002-2444-4226\")),\n person(\"JJ\", \"Allaire\", role = \"aut\",\n comment = c(ORCID = \"0000-0003-0174-9868\")),\n person(\"Kevin\", \"Ushey\", role = \"aut\",\n comment = c(ORCID = \"0000-0003-2880-7407\")),\n person(\"Qiang\", \"Kou\", role = \"aut\",\n comment = c(ORCID = \"0000-0001-6786-5453\")),\n person(\"Nathan\", \"Russell\", role = \"aut\"),\n person(\"Iñaki\", \"Ucar\", role = \"aut\",\n comment = c(ORCID = \"0000-0001-6403-5550\")),\n person(\"Doug\", \"Bates\", role = \"aut\",\n comment = c(ORCID = \"0000-0001-8316-9503\")),\n person(\"John\", \"Chambers\", role = \"aut\"))",
+ "Description": "The 'Rcpp' package provides R functions as well as C++ classes which\n offer a seamless integration of R and C++. Many R data types and objects can be\n mapped back and forth to C++ equivalents which facilitates both writing of new\n code as well as easier integration of third-party libraries. Documentation\n about 'Rcpp' is provided by several vignettes included in this package, via the\n 'Rcpp Gallery' site at , the paper by Eddelbuettel and\n Francois (2011, ), the book by Eddelbuettel (2013,\n ) and the paper by Eddelbuettel and Balamuta (2018,\n ); see 'citation(\"Rcpp\")' for details.",
+ "Imports": "methods, utils",
+ "Suggests": "tinytest, inline, rbenchmark, pkgKitten (>= 0.1.2)",
+ "URL": "https://www.rcpp.org,\nhttps://dirk.eddelbuettel.com/code/rcpp.html,\nhttps://github.com/RcppCore/Rcpp",
+ "License": "GPL (>= 2)",
+ "BugReports": "https://github.com/RcppCore/Rcpp/issues",
+ "MailingList": "rcpp-devel@lists.r-forge.r-project.org",
+ "RoxygenNote": "6.1.1",
+ "Encoding": "UTF-8",
+ "NeedsCompilation": "yes",
+ "Packaged": "2025-01-11 20:21:25 UTC; edd",
+ "Author": "Dirk Eddelbuettel [aut, cre] (),\n Romain Francois [aut] (),\n JJ Allaire [aut] (),\n Kevin Ushey [aut] (),\n Qiang Kou [aut] (),\n Nathan Russell [aut],\n Iñaki Ucar [aut] (),\n Doug Bates [aut] (),\n John Chambers [aut]",
+ "Maintainer": "Dirk Eddelbuettel ",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-01-12 16:10:02 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-03-10 18:20:15 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "Rcpp",
+ "RemoteRef": "Rcpp",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "1.0.14"
+ }
+ },
+ "S7": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "S7",
+ "Title": "An Object Oriented System Meant to Become a Successor to S3 and\nS4",
+ "Version": "0.2.0",
+ "Authors@R": "c(\n person(\"Object-Oriented Programming Working Group\", role = \"cph\"),\n person(\"Davis\", \"Vaughan\", role = \"aut\"),\n person(\"Jim\", \"Hester\", role = \"aut\",\n comment = c(ORCID = \"0000-0002-2739-7082\")),\n person(\"Tomasz\", \"Kalinowski\", role = \"aut\"),\n person(\"Will\", \"Landau\", role = \"aut\"),\n person(\"Michael\", \"Lawrence\", role = \"aut\"),\n person(\"Martin\", \"Maechler\", role = \"aut\",\n comment = c(ORCID = \"0000-0002-8685-9910\")),\n person(\"Luke\", \"Tierney\", role = \"aut\"),\n person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\"),\n comment = c(ORCID = \"0000-0003-4757-117X\"))\n )",
+ "Description": "A new object oriented programming system designed to be a\n successor to S3 and S4. It includes formal class, generic, and method\n specification, and a limited form of multiple dispatch. It has been\n designed and implemented collaboratively by the R Consortium\n Object-Oriented Programming Working Group, which includes\n representatives from R-Core, 'Bioconductor', 'Posit'/'tidyverse', and\n the wider R community.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://rconsortium.github.io/S7/,\nhttps://github.com/RConsortium/S7",
+ "BugReports": "https://github.com/RConsortium/S7/issues",
+ "Depends": "R (>= 3.5.0)",
+ "Imports": "utils",
+ "Suggests": "bench, callr, covr, knitr, methods, rmarkdown, testthat (>=\n3.2.0), tibble",
+ "VignetteBuilder": "knitr",
+ "Config/build/compilation-database": "true",
+ "Config/Needs/website": "sloop",
+ "Config/testthat/edition": "3",
+ "Config/testthat/parallel": "TRUE",
+ "Config/testthat/start-first": "external-generic",
+ "Encoding": "UTF-8",
+ "RoxygenNote": "7.3.2",
+ "NeedsCompilation": "yes",
+ "Packaged": "2024-11-06 17:18:31 UTC; hadleywickham",
+ "Author": "Object-Oriented Programming Working Group [cph],\n Davis Vaughan [aut],\n Jim Hester [aut] (),\n Tomasz Kalinowski [aut],\n Will Landau [aut],\n Michael Lawrence [aut],\n Martin Maechler [aut] (),\n Luke Tierney [aut],\n Hadley Wickham [aut, cre] ()",
+ "Maintainer": "Hadley Wickham ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-11-07 12:50:02 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-03-19 01:42:21 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "S7",
+ "RemoteRef": "S7",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "0.2.0"
+ }
+ },
+ "askpass": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "askpass",
+ "Type": "Package",
+ "Title": "Password Entry Utilities for R, Git, and SSH",
+ "Version": "1.2.1",
+ "Authors@R": "person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), \n email = \"jeroenooms@gmail.com\", comment = c(ORCID = \"0000-0002-4035-0289\"))",
+ "Description": "Cross-platform utilities for prompting the user for credentials or a \n passphrase, for example to authenticate with a server or read a protected key.\n Includes native programs for MacOS and Windows, hence no 'tcltk' is required. \n Password entry can be invoked in two different ways: directly from R via the \n askpass() function, or indirectly as password-entry back-end for 'ssh-agent' \n or 'git-credential' via the SSH_ASKPASS and GIT_ASKPASS environment variables.\n Thereby the user can be prompted for credentials or a passphrase if needed \n when R calls out to git or ssh.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://r-lib.r-universe.dev/askpass",
+ "BugReports": "https://github.com/r-lib/askpass/issues",
+ "Encoding": "UTF-8",
+ "Imports": "sys (>= 2.1)",
+ "RoxygenNote": "7.2.3",
+ "Suggests": "testthat",
+ "Language": "en-US",
+ "NeedsCompilation": "yes",
+ "Packaged": "2024-10-03 14:12:09 UTC; jeroen",
+ "Author": "Jeroen Ooms [aut, cre] ()",
+ "Maintainer": "Jeroen Ooms ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-10-04 07:20:03 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-03-12 13:30:55 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "askpass",
+ "RemoteRef": "askpass",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "1.2.1"
+ }
+ },
+ "base64enc": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "base64enc",
+ "Version": "0.1-3",
+ "Title": "Tools for base64 encoding",
+ "Author": "Simon Urbanek ",
+ "Maintainer": "Simon Urbanek ",
+ "Depends": "R (>= 2.9.0)",
+ "Enhances": "png",
+ "Description": "This package provides tools for handling base64 encoding. It is more flexible than the orphaned base64 package.",
+ "License": "GPL-2 | GPL-3",
+ "URL": "http://www.rforge.net/base64enc",
+ "NeedsCompilation": "yes",
+ "Packaged": "2015-02-04 20:31:00 UTC; svnuser",
+ "Repository": "CRAN",
+ "Date/Publication": "2015-07-28 08:03:37",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-04-24 17:06:18 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "base64enc",
+ "RemoteRef": "base64enc",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "0.1-3"
+ }
+ },
+ "bslib": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "bslib",
+ "Title": "Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'",
+ "Version": "0.9.0",
+ "Authors@R": "c(\n person(\"Carson\", \"Sievert\", , \"carson@posit.co\", role = c(\"aut\", \"cre\"),\n comment = c(ORCID = \"0000-0002-4958-2844\")),\n person(\"Joe\", \"Cheng\", , \"joe@posit.co\", role = \"aut\"),\n person(\"Garrick\", \"Aden-Buie\", , \"garrick@posit.co\", role = \"aut\",\n comment = c(ORCID = \"0000-0002-7111-0077\")),\n person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\")),\n person(, \"Bootstrap contributors\", role = \"ctb\",\n comment = \"Bootstrap library\"),\n person(, \"Twitter, Inc\", role = \"cph\",\n comment = \"Bootstrap library\"),\n person(\"Javi\", \"Aguilar\", role = c(\"ctb\", \"cph\"),\n comment = \"Bootstrap colorpicker library\"),\n person(\"Thomas\", \"Park\", role = c(\"ctb\", \"cph\"),\n comment = \"Bootswatch library\"),\n person(, \"PayPal\", role = c(\"ctb\", \"cph\"),\n comment = \"Bootstrap accessibility plugin\")\n )",
+ "Description": "Simplifies custom 'CSS' styling of both 'shiny' and\n 'rmarkdown' via 'Bootstrap' 'Sass'. Supports 'Bootstrap' 3, 4 and 5 as\n well as their various 'Bootswatch' themes. An interactive widget is\n also provided for previewing themes in real time.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://rstudio.github.io/bslib/, https://github.com/rstudio/bslib",
+ "BugReports": "https://github.com/rstudio/bslib/issues",
+ "Depends": "R (>= 2.10)",
+ "Imports": "base64enc, cachem, fastmap (>= 1.1.1), grDevices, htmltools\n(>= 0.5.8), jquerylib (>= 0.1.3), jsonlite, lifecycle, memoise\n(>= 2.0.1), mime, rlang, sass (>= 0.4.9)",
+ "Suggests": "bsicons, curl, fontawesome, future, ggplot2, knitr, magrittr,\nrappdirs, rmarkdown (>= 2.7), shiny (> 1.8.1), testthat,\nthematic, tools, utils, withr, yaml",
+ "Config/Needs/deploy": "BH, chiflights22, colourpicker, commonmark, cpp11,\ncpsievert/chiflights22, cpsievert/histoslider, dplyr, DT,\nggplot2, ggridges, gt, hexbin, histoslider, htmlwidgets,\nlattice, leaflet, lubridate, markdown, modelr, plotly,\nreactable, reshape2, rprojroot, rsconnect, rstudio/shiny,\nscales, styler, tibble",
+ "Config/Needs/routine": "chromote, desc, renv",
+ "Config/Needs/website": "brio, crosstalk, dplyr, DT, ggplot2, glue,\nhtmlwidgets, leaflet, lorem, palmerpenguins, plotly, purrr,\nrprojroot, rstudio/htmltools, scales, stringr, tidyr, webshot2",
+ "Config/testthat/edition": "3",
+ "Config/testthat/parallel": "true",
+ "Config/testthat/start-first": "zzzz-bs-sass, fonts, zzz-precompile,\ntheme-*, rmd-*",
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+ "URL": "https://docs.ropensci.org/commonmark/\nhttps://ropensci.r-universe.dev/commonmark",
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+ "Description": "Bindings to 'libcurl' for performing fully\n configurable HTTP/FTP requests where responses can be processed in memory, on\n disk, or streaming via the callback or connection interfaces. Some knowledge\n of 'libcurl' is recommended; for a more-user-friendly web client see the \n 'httr2' package which builds on this package with http specific tools and logic.",
+ "License": "MIT + file LICENSE",
+ "SystemRequirements": "libcurl (>= 7.73): libcurl-devel (rpm) or\nlibcurl4-openssl-dev (deb)",
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+ "Author": "Joe Cheng [aut],\n Winston Chang [aut, cre],\n Posit, PBC fnd [cph],\n Hector Corrada Bravo [ctb],\n Jeroen Ooms [ctb],\n Andrzej Krzemienski [cph] (optional.hpp),\n libuv project contributors [cph] (libuv library, see src/libuv/AUTHORS\n file),\n Joyent, Inc. and other Node contributors [cph] (libuv library, see\n src/libuv/AUTHORS file; and http-parser library, see\n src/http-parser/AUTHORS file),\n Niels Provos [cph] (libuv subcomponent: tree.h),\n Internet Systems Consortium, Inc. [cph] (libuv subcomponent: inet_pton\n and inet_ntop, contained in src/libuv/src/inet.c),\n Alexander Chemeris [cph] (libuv subcomponent: stdint-msvc2008.h (from\n msinttypes)),\n Google, Inc. [cph] (libuv subcomponent: pthread-fixes.c),\n Sony Mobile Communcations AB [cph] (libuv subcomponent:\n pthread-fixes.c),\n Berkeley Software Design Inc. [cph] (libuv subcomponent:\n android-ifaddrs.h, android-ifaddrs.c),\n Kenneth MacKay [cph] (libuv subcomponent: android-ifaddrs.h,\n android-ifaddrs.c),\n Emergya (Cloud4all, FP7/2007-2013, grant agreement no 289016) [cph]\n (libuv subcomponent: android-ifaddrs.h, android-ifaddrs.c),\n Steve Reid [aut] (SHA-1 implementation),\n James Brown [aut] (SHA-1 implementation),\n Bob Trower [aut] (base64 implementation),\n Alexander Peslyak [aut] (MD5 implementation),\n Trantor Standard Systems [cph] (base64 implementation),\n Igor Sysoev [cph] (http-parser)",
+ "Maintainer": "Winston Chang ",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-04-16 08:00:06 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-04-25 02:43:05 UTC; unix",
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+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
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+ }
+ },
+ "httr": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "httr",
+ "Title": "Tools for Working with URLs and HTTP",
+ "Version": "1.4.7",
+ "Authors@R": "c(\n person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\")),\n person(\"Posit, PBC\", role = c(\"cph\", \"fnd\"))\n )",
+ "Description": "Useful tools for working with HTTP organised by HTTP verbs\n (GET(), POST(), etc). Configuration functions make it easy to control\n additional request components (authenticate(), add_headers() and so\n on).",
+ "License": "MIT + file LICENSE",
+ "URL": "https://httr.r-lib.org/, https://github.com/r-lib/httr",
+ "BugReports": "https://github.com/r-lib/httr/issues",
+ "Depends": "R (>= 3.5)",
+ "Imports": "curl (>= 5.0.2), jsonlite, mime, openssl (>= 0.8), R6",
+ "Suggests": "covr, httpuv, jpeg, knitr, png, readr, rmarkdown, testthat\n(>= 0.8.0), xml2",
+ "VignetteBuilder": "knitr",
+ "Config/Needs/website": "tidyverse/tidytemplate",
+ "Encoding": "UTF-8",
+ "RoxygenNote": "7.2.3",
+ "NeedsCompilation": "no",
+ "Packaged": "2023-08-15 02:56:56 UTC; hadleywickham",
+ "Author": "Hadley Wickham [aut, cre],\n Posit, PBC [cph, fnd]",
+ "Maintainer": "Hadley Wickham ",
+ "Repository": "CRAN",
+ "Date/Publication": "2023-08-15 09:00:02 UTC",
+ "Built": "R 4.4.0; ; 2024-05-12 14:25:27 UTC; unix",
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+ },
+ "isoband": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "isoband",
+ "Title": "Generate Isolines and Isobands from Regularly Spaced Elevation\nGrids",
+ "Version": "0.2.7",
+ "Authors@R": "c(\n person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = c(\"aut\", \"cre\"),\n comment = c(ORCID = \"0000-0003-4757-117X\")),\n person(\"Claus O.\", \"Wilke\", , \"wilke@austin.utexas.edu\", role = \"aut\",\n comment = c(\"Original author\", ORCID = \"0000-0002-7470-9261\")),\n person(\"Thomas Lin\", \"Pedersen\", , \"thomasp85@gmail.com\", role = \"aut\",\n comment = c(ORCID = \"0000-0002-5147-4711\"))\n )",
+ "Description": "A fast C++ implementation to generate contour lines\n (isolines) and contour polygons (isobands) from regularly spaced grids\n containing elevation data.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://isoband.r-lib.org",
+ "BugReports": "https://github.com/r-lib/isoband/issues",
+ "Imports": "grid, utils",
+ "Suggests": "covr, ggplot2, knitr, magick, microbenchmark, rmarkdown, sf,\ntestthat, xml2",
+ "VignetteBuilder": "knitr",
+ "Config/Needs/website": "tidyverse/tidytemplate",
+ "Config/testthat/edition": "3",
+ "Encoding": "UTF-8",
+ "RoxygenNote": "7.2.3",
+ "SystemRequirements": "C++11",
+ "NeedsCompilation": "yes",
+ "Packaged": "2022-12-19 20:10:02 UTC; hadleywickham",
+ "Author": "Hadley Wickham [aut, cre] (),\n Claus O. Wilke [aut] (Original author,\n ),\n Thomas Lin Pedersen [aut] ()",
+ "Maintainer": "Hadley Wickham ",
+ "Repository": "CRAN",
+ "Date/Publication": "2022-12-20 10:00:13 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-04-24 17:06:19 UTC; unix",
+ "RemoteType": "standard",
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+ "RemoteRepos": "https://cloud.r-project.org",
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+ }
+ },
+ "jquerylib": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "jquerylib",
+ "Title": "Obtain 'jQuery' as an HTML Dependency Object",
+ "Version": "0.1.4",
+ "Authors@R": "c(\n person(\"Carson\", \"Sievert\", role = c(\"aut\", \"cre\"), email = \"carson@rstudio.com\", comment = c(ORCID = \"0000-0002-4958-2844\")),\n person(\"Joe\", \"Cheng\", role = \"aut\", email = \"joe@rstudio.com\"),\n person(family = \"RStudio\", role = \"cph\"),\n person(family = \"jQuery Foundation\", role = \"cph\",\n comment = \"jQuery library and jQuery UI library\"),\n person(family = \"jQuery contributors\", role = c(\"ctb\", \"cph\"),\n comment = \"jQuery library; authors listed in inst/lib/jquery-AUTHORS.txt\")\n )",
+ "Description": "Obtain any major version of 'jQuery' () and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown').\n Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.",
+ "License": "MIT + file LICENSE",
+ "Encoding": "UTF-8",
+ "Config/testthat/edition": "3",
+ "RoxygenNote": "7.0.2",
+ "Imports": "htmltools",
+ "Suggests": "testthat",
+ "NeedsCompilation": "no",
+ "Packaged": "2021-04-26 16:40:21 UTC; cpsievert",
+ "Author": "Carson Sievert [aut, cre] (),\n Joe Cheng [aut],\n RStudio [cph],\n jQuery Foundation [cph] (jQuery library and jQuery UI library),\n jQuery contributors [ctb, cph] (jQuery library; authors listed in\n inst/lib/jquery-AUTHORS.txt)",
+ "Maintainer": "Carson Sievert ",
+ "Repository": "CRAN",
+ "Date/Publication": "2021-04-26 17:10:02 UTC",
+ "Built": "R 4.4.0; ; 2024-05-15 01:35:25 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "jquerylib",
+ "RemoteRef": "jquerylib",
+ "RemoteRepos": "https://cran.rstudio.com/",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "0.1.4"
+ }
+ },
+ "jsonlite": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "jsonlite",
+ "Version": "1.9.1",
+ "Title": "A Simple and Robust JSON Parser and Generator for R",
+ "License": "MIT + file LICENSE",
+ "Depends": "methods",
+ "Authors@R": "c(\n person(\"Jeroen\", \"Ooms\", role = c(\"aut\", \"cre\"), email = \"jeroenooms@gmail.com\",\n comment = c(ORCID = \"0000-0002-4035-0289\")),\n person(\"Duncan\", \"Temple Lang\", role = \"ctb\"),\n person(\"Lloyd\", \"Hilaiel\", role = \"cph\", comment=\"author of bundled libyajl\"))",
+ "URL": "https://jeroen.r-universe.dev/jsonlite\nhttps://arxiv.org/abs/1403.2805",
+ "BugReports": "https://github.com/jeroen/jsonlite/issues",
+ "Maintainer": "Jeroen Ooms ",
+ "VignetteBuilder": "knitr, R.rsp",
+ "Description": "A reasonably fast JSON parser and generator, optimized for statistical \n data and the web. Offers simple, flexible tools for working with JSON in R, and\n is particularly powerful for building pipelines and interacting with a web API. \n The implementation is based on the mapping described in the vignette (Ooms, 2014).\n In addition to converting JSON data from/to R objects, 'jsonlite' contains \n functions to stream, validate, and prettify JSON data. The unit tests included \n with the package verify that all edge cases are encoded and decoded consistently \n for use with dynamic data in systems and applications.",
+ "Suggests": "httr, vctrs, testthat, knitr, rmarkdown, R.rsp, sf",
+ "RoxygenNote": "7.2.3",
+ "Encoding": "UTF-8",
+ "NeedsCompilation": "yes",
+ "Packaged": "2025-03-03 14:17:56 UTC; jeroen",
+ "Author": "Jeroen Ooms [aut, cre] (),\n Duncan Temple Lang [ctb],\n Lloyd Hilaiel [cph] (author of bundled libyajl)",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-03-03 22:10:02 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-03-12 13:30:54 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "jsonlite",
+ "RemoteRef": "jsonlite",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "1.9.1"
+ }
+ },
+ "knitr": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "knitr",
+ "Type": "Package",
+ "Title": "A General-Purpose Package for Dynamic Report Generation in R",
+ "Version": "1.50",
+ "Authors@R": "c(\n person(\"Yihui\", \"Xie\", role = c(\"aut\", \"cre\"), email = \"xie@yihui.name\", comment = c(ORCID = \"0000-0003-0645-5666\", URL = \"https://yihui.org\")),\n person(\"Abhraneel\", \"Sarma\", role = \"ctb\"),\n person(\"Adam\", \"Vogt\", role = \"ctb\"),\n person(\"Alastair\", \"Andrew\", role = \"ctb\"),\n person(\"Alex\", \"Zvoleff\", role = \"ctb\"),\n person(\"Amar\", \"Al-Zubaidi\", role = \"ctb\"),\n person(\"Andre\", \"Simon\", role = \"ctb\", comment = \"the CSS files under inst/themes/ were derived from the Highlight package http://www.andre-simon.de\"),\n person(\"Aron\", \"Atkins\", role = \"ctb\"),\n person(\"Aaron\", \"Wolen\", role = \"ctb\"),\n person(\"Ashley\", \"Manton\", role = \"ctb\"),\n person(\"Atsushi\", \"Yasumoto\", role = \"ctb\", comment = c(ORCID = \"0000-0002-8335-495X\")),\n person(\"Ben\", \"Baumer\", role = \"ctb\"),\n person(\"Brian\", \"Diggs\", role = \"ctb\"),\n person(\"Brian\", \"Zhang\", role = \"ctb\"),\n person(\"Bulat\", \"Yapparov\", role = \"ctb\"),\n person(\"Cassio\", \"Pereira\", role = \"ctb\"),\n person(\"Christophe\", \"Dervieux\", role = \"ctb\"),\n person(\"David\", \"Hall\", role = \"ctb\"),\n person(\"David\", \"Hugh-Jones\", role = \"ctb\"),\n person(\"David\", \"Robinson\", role = \"ctb\"),\n person(\"Doug\", \"Hemken\", role = \"ctb\"),\n person(\"Duncan\", \"Murdoch\", role = \"ctb\"),\n person(\"Elio\", \"Campitelli\", role = \"ctb\"),\n person(\"Ellis\", \"Hughes\", role = \"ctb\"),\n person(\"Emily\", \"Riederer\", role = \"ctb\"),\n person(\"Fabian\", \"Hirschmann\", role = \"ctb\"),\n person(\"Fitch\", \"Simeon\", role = \"ctb\"),\n person(\"Forest\", \"Fang\", role = \"ctb\"),\n person(c(\"Frank\", \"E\", \"Harrell\", \"Jr\"), role = \"ctb\", comment = \"the Sweavel package at inst/misc/Sweavel.sty\"),\n person(\"Garrick\", \"Aden-Buie\", role = \"ctb\"),\n person(\"Gregoire\", \"Detrez\", role = \"ctb\"),\n person(\"Hadley\", \"Wickham\", role = \"ctb\"),\n person(\"Hao\", \"Zhu\", role = \"ctb\"),\n person(\"Heewon\", \"Jeon\", role = \"ctb\"),\n person(\"Henrik\", \"Bengtsson\", role = \"ctb\"),\n person(\"Hiroaki\", \"Yutani\", role = \"ctb\"),\n person(\"Ian\", \"Lyttle\", role = \"ctb\"),\n person(\"Hodges\", \"Daniel\", role = \"ctb\"),\n person(\"Jacob\", \"Bien\", role = \"ctb\"),\n person(\"Jake\", \"Burkhead\", role = \"ctb\"),\n person(\"James\", \"Manton\", role = \"ctb\"),\n person(\"Jared\", \"Lander\", role = \"ctb\"),\n person(\"Jason\", \"Punyon\", role = \"ctb\"),\n person(\"Javier\", \"Luraschi\", role = \"ctb\"),\n person(\"Jeff\", \"Arnold\", role = \"ctb\"),\n person(\"Jenny\", \"Bryan\", role = \"ctb\"),\n person(\"Jeremy\", \"Ashkenas\", role = c(\"ctb\", \"cph\"), comment = \"the CSS file at inst/misc/docco-classic.css\"),\n person(\"Jeremy\", \"Stephens\", role = \"ctb\"),\n person(\"Jim\", \"Hester\", role = \"ctb\"),\n person(\"Joe\", \"Cheng\", role = \"ctb\"),\n person(\"Johannes\", \"Ranke\", role = \"ctb\"),\n person(\"John\", \"Honaker\", role = \"ctb\"),\n person(\"John\", \"Muschelli\", role = \"ctb\"),\n person(\"Jonathan\", \"Keane\", role = \"ctb\"),\n person(\"JJ\", \"Allaire\", role = \"ctb\"),\n person(\"Johan\", \"Toloe\", role = \"ctb\"),\n person(\"Jonathan\", \"Sidi\", role = \"ctb\"),\n person(\"Joseph\", \"Larmarange\", role = \"ctb\"),\n person(\"Julien\", \"Barnier\", role = \"ctb\"),\n person(\"Kaiyin\", \"Zhong\", role = \"ctb\"),\n person(\"Kamil\", \"Slowikowski\", role = \"ctb\"),\n person(\"Karl\", \"Forner\", role = \"ctb\"),\n person(c(\"Kevin\", \"K.\"), \"Smith\", role = \"ctb\"),\n person(\"Kirill\", \"Mueller\", role = \"ctb\"),\n person(\"Kohske\", \"Takahashi\", role = \"ctb\"),\n person(\"Lorenz\", \"Walthert\", role = \"ctb\"),\n person(\"Lucas\", \"Gallindo\", role = \"ctb\"),\n person(\"Marius\", \"Hofert\", role = \"ctb\"),\n person(\"Martin\", \"Modrák\", role = \"ctb\"),\n person(\"Michael\", \"Chirico\", role = \"ctb\"),\n person(\"Michael\", 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Software, PBC\", role = c(\"cph\", \"fnd\"))\n )",
+ "Description": "Provides a general-purpose tool for dynamic report generation in R\n using Literate Programming techniques.",
+ "Depends": "R (>= 3.6.0)",
+ "Imports": "evaluate (>= 0.15), highr (>= 0.11), methods, tools, xfun (>=\n0.51), yaml (>= 2.1.19)",
+ "Suggests": "bslib, codetools, DBI (>= 0.4-1), digest, formatR, gifski,\ngridSVG, htmlwidgets (>= 0.7), jpeg, JuliaCall (>= 0.11.1),\nmagick, litedown, markdown (>= 1.3), png, ragg, reticulate (>=\n1.4), rgl (>= 0.95.1201), rlang, rmarkdown, sass, showtext,\nstyler (>= 1.2.0), targets (>= 0.6.0), testit, tibble,\ntikzDevice (>= 0.10), tinytex (>= 0.56), webshot, rstudioapi,\nsvglite",
+ "License": "GPL",
+ "URL": "https://yihui.org/knitr/",
+ "BugReports": "https://github.com/yihui/knitr/issues",
+ "Encoding": "UTF-8",
+ "VignetteBuilder": "litedown, knitr",
+ "SystemRequirements": "Package vignettes based on R Markdown v2 or\nreStructuredText require Pandoc (http://pandoc.org). The\nfunction rst2pdf() requires rst2pdf\n(https://github.com/rst2pdf/rst2pdf).",
+ "Collate": "'block.R' 'cache.R' 'citation.R' 'hooks-html.R' 'plot.R'\n'utils.R' 'defaults.R' 'concordance.R' 'engine.R' 'highlight.R'\n'themes.R' 'header.R' 'hooks-asciidoc.R' 'hooks-chunk.R'\n'hooks-extra.R' 'hooks-latex.R' 'hooks-md.R' 'hooks-rst.R'\n'hooks-textile.R' 'hooks.R' 'output.R' 'package.R' 'pandoc.R'\n'params.R' 'parser.R' 'pattern.R' 'rocco.R' 'spin.R' 'table.R'\n'template.R' 'utils-conversion.R' 'utils-rd2html.R'\n'utils-string.R' 'utils-sweave.R' 'utils-upload.R'\n'utils-vignettes.R' 'zzz.R'",
+ "RoxygenNote": "7.3.2",
+ "NeedsCompilation": "no",
+ "Packaged": "2025-03-15 00:17:19 UTC; runner",
+ "Author": "Yihui Xie [aut, cre] (,\n https://yihui.org),\n Abhraneel Sarma [ctb],\n Adam Vogt [ctb],\n Alastair Andrew [ctb],\n Alex Zvoleff [ctb],\n Amar Al-Zubaidi [ctb],\n Andre Simon [ctb] (the CSS files under inst/themes/ were derived from\n the Highlight package http://www.andre-simon.de),\n Aron Atkins [ctb],\n Aaron Wolen [ctb],\n Ashley Manton [ctb],\n Atsushi Yasumoto [ctb] (),\n Ben Baumer [ctb],\n Brian Diggs [ctb],\n Brian Zhang [ctb],\n Bulat Yapparov [ctb],\n Cassio Pereira [ctb],\n Christophe Dervieux [ctb],\n David Hall [ctb],\n David Hugh-Jones [ctb],\n David Robinson [ctb],\n Doug Hemken [ctb],\n Duncan Murdoch [ctb],\n Elio Campitelli [ctb],\n Ellis Hughes [ctb],\n Emily Riederer [ctb],\n Fabian Hirschmann [ctb],\n Fitch Simeon [ctb],\n Forest Fang [ctb],\n Frank E Harrell Jr [ctb] (the Sweavel package at inst/misc/Sweavel.sty),\n Garrick Aden-Buie [ctb],\n Gregoire Detrez [ctb],\n Hadley Wickham [ctb],\n Hao Zhu [ctb],\n Heewon Jeon [ctb],\n Henrik Bengtsson [ctb],\n Hiroaki Yutani [ctb],\n Ian Lyttle [ctb],\n Hodges Daniel [ctb],\n Jacob Bien [ctb],\n Jake Burkhead [ctb],\n James Manton [ctb],\n Jared Lander [ctb],\n Jason Punyon [ctb],\n Javier Luraschi [ctb],\n Jeff Arnold [ctb],\n Jenny Bryan [ctb],\n Jeremy Ashkenas [ctb, cph] (the CSS file at\n inst/misc/docco-classic.css),\n Jeremy Stephens [ctb],\n Jim Hester [ctb],\n Joe Cheng [ctb],\n Johannes Ranke [ctb],\n John Honaker [ctb],\n John Muschelli [ctb],\n Jonathan Keane [ctb],\n JJ Allaire [ctb],\n Johan Toloe [ctb],\n Jonathan Sidi [ctb],\n Joseph Larmarange [ctb],\n Julien Barnier [ctb],\n Kaiyin Zhong [ctb],\n Kamil Slowikowski [ctb],\n Karl Forner [ctb],\n Kevin K. Smith [ctb],\n Kirill Mueller [ctb],\n Kohske Takahashi [ctb],\n Lorenz Walthert [ctb],\n Lucas Gallindo [ctb],\n Marius Hofert [ctb],\n Martin Modrák [ctb],\n Michael Chirico [ctb],\n Michael Friendly [ctb],\n Michal Bojanowski [ctb],\n Michel Kuhlmann [ctb],\n Miller Patrick [ctb],\n Nacho Caballero [ctb],\n Nick Salkowski [ctb],\n Niels Richard Hansen [ctb],\n Noam Ross [ctb],\n Obada Mahdi [ctb],\n Pavel N. Krivitsky [ctb] (),\n Pedro Faria [ctb],\n Qiang Li [ctb],\n Ramnath Vaidyanathan [ctb],\n Richard Cotton [ctb],\n Robert Krzyzanowski [ctb],\n Rodrigo Copetti [ctb],\n Romain Francois [ctb],\n Ruaridh Williamson [ctb],\n Sagiru Mati [ctb] (),\n Scott Kostyshak [ctb],\n Sebastian Meyer [ctb],\n Sietse Brouwer [ctb],\n Simon de Bernard [ctb],\n Sylvain Rousseau [ctb],\n Taiyun Wei [ctb],\n Thibaut Assus [ctb],\n Thibaut Lamadon [ctb],\n Thomas Leeper [ctb],\n Tim Mastny [ctb],\n Tom Torsney-Weir [ctb],\n Trevor Davis [ctb],\n Viktoras Veitas [ctb],\n Weicheng Zhu [ctb],\n Wush Wu [ctb],\n Zachary Foster [ctb],\n Zhian N. Kamvar [ctb] (),\n Posit Software, PBC [cph, fnd]",
+ "Maintainer": "Yihui Xie ",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-03-16 09:20:02 UTC",
+ "Built": "R 4.4.3; ; 2025-06-01 04:07:07 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "knitr",
+ "RemoteRef": "knitr",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "1.50"
+ }
+ },
+ "labeling": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "labeling",
+ "Type": "Package",
+ "Title": "Axis Labeling",
+ "Version": "0.4.3",
+ "Date": "2023-08-29",
+ "Author": "Justin Talbot,",
+ "Maintainer": "Nuno Sempere ",
+ "Description": "Functions which provide a range of axis labeling algorithms. ",
+ "License": "MIT + file LICENSE | Unlimited",
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+ "Type": "Package",
+ "Title": "Utilities for Scheduling Functions to Execute Later with Event\nLoops",
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+ "Description": "Executes arbitrary R or C functions some time after the current\n time, after the R execution stack has emptied. The functions are scheduled\n in an event loop.",
+ "URL": "https://r-lib.github.io/later/, https://github.com/r-lib/later",
+ "BugReports": "https://github.com/r-lib/later/issues",
+ "License": "MIT + file LICENSE",
+ "Imports": "Rcpp (>= 0.12.9), rlang",
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+ "Repository": "CRAN",
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+ "description": {
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+ "Version": "0.22-6",
+ "Date": "2024-03-20",
+ "Priority": "recommended",
+ "Title": "Trellis Graphics for R",
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+ "Description": "A powerful and elegant high-level data visualization\n system inspired by Trellis graphics, with an emphasis on\n multivariate data. Lattice is sufficient for typical graphics needs,\n and is also flexible enough to handle most nonstandard requirements.\n See ?Lattice for an introduction.",
+ "Depends": "R (>= 4.0.0)",
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+ "License": "GPL (>= 2)",
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+ "BugReports": "https://github.com/deepayan/lattice/issues",
+ "NeedsCompilation": "yes",
+ "Packaged": "2024-03-20 03:08:45 UTC; deepayan",
+ "Author": "Deepayan Sarkar [aut, cre] (),\n Felix Andrews [ctb],\n Kevin Wright [ctb] (documentation),\n Neil Klepeis [ctb],\n Johan Larsson [ctb] (miscellaneous improvements),\n Zhijian (Jason) Wen [cph] (filled contour code),\n Paul Murrell [ctb],\n Stefan Eng [ctb] (violin plot improvements),\n Achim Zeileis [ctb] (modern colors),\n Alexandre Courtiol [ctb] (generics for larrows, lpolygon, lrect and\n lsegments)",
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+ "Version": "0.2.2",
+ "Title": "Lazy (Non-Standard) Evaluation",
+ "Description": "An alternative approach to non-standard evaluation using\n formulas. Provides a full implementation of LISP style 'quasiquotation',\n making it easier to generate code with other code.",
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+ "Packaged": "2019-03-15 14:18:01 UTC; lionel",
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+ "Repository": "https://cloud.r-project.org",
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+ "Package": "leaflet",
+ "Title": "Create Interactive Web Maps with the JavaScript 'Leaflet'\nLibrary",
+ "Version": "2.2.2",
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+ "Description": "Create and customize interactive maps using the 'Leaflet'\n JavaScript library and the 'htmlwidgets' package. These maps can be\n used directly from the R console, from 'RStudio', in Shiny\n applications and R Markdown documents.",
+ "License": "GPL-3",
+ "URL": "https://rstudio.github.io/leaflet/,\nhttps://github.com/rstudio/leaflet",
+ "BugReports": "https://github.com/rstudio/leaflet/issues",
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+ "Maintainer": "Joe Cheng ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-03-26 19:10:06 UTC",
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+ "Description": "Contains third-party map tile provider information from\n 'Leaflet.js', ,\n to be used with the 'leaflet' R package. Additionally,\n 'leaflet.providers' enables users to retrieve up-to-date provider\n information between package updates.",
+ "License": "BSD_2_clause + file LICENSE",
+ "URL": "https://rstudio.github.io/leaflet.providers/,\nhttps://github.com/rstudio/leaflet.providers",
+ "BugReports": "https://github.com/rstudio/leaflet.providers/issues",
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+ "Packaged": "2023-10-17 12:24:21 UTC; garrick",
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+ "Description": "Manage the life cycle of your exported functions with shared\n conventions, documentation badges, and user-friendly deprecation\n warnings.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://lifecycle.r-lib.org/, https://github.com/r-lib/lifecycle",
+ "BugReports": "https://github.com/r-lib/lifecycle/issues",
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+ "Repository": "CRAN",
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+ "Repository": "https://cloud.r-project.org",
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+ "License": "MIT + file LICENSE",
+ "URL": "https://magrittr.tidyverse.org,\nhttps://github.com/tidyverse/magrittr",
+ "BugReports": "https://github.com/tidyverse/magrittr/issues",
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+ "License": "MIT + file LICENSE",
+ "URL": "https://jeroen.r-universe.dev/openssl",
+ "BugReports": "https://github.com/jeroen/openssl/issues",
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+ "License": "MIT + file LICENSE",
+ "URL": "https://pillar.r-lib.org/, https://github.com/r-lib/pillar",
+ "BugReports": "https://github.com/r-lib/pillar/issues",
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+ "License": "Apache License (>= 2)",
+ "URL": "https://pins.rstudio.com/, https://github.com/rstudio/pins-r",
+ "BugReports": "https://github.com/rstudio/pins-r/issues",
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+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "pkgbuild",
+ "Title": "Find Tools Needed to Build R Packages",
+ "Version": "1.4.5",
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+ "Description": "Provides functions used to build R packages. Locates\n compilers needed to build R packages on various platforms and ensures\n the PATH is configured appropriately so R can use them.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://github.com/r-lib/pkgbuild, https://pkgbuild.r-lib.org",
+ "BugReports": "https://github.com/r-lib/pkgbuild/issues",
+ "Depends": "R (>= 3.5)",
+ "Imports": "callr (>= 3.2.0), cli (>= 3.4.0), desc, processx, R6",
+ "Suggests": "covr, cpp11, knitr, Rcpp, rmarkdown, testthat (>= 3.2.0),\nwithr (>= 2.3.0)",
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+ "Encoding": "UTF-8",
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+ "Author": "Hadley Wickham [aut],\n Jim Hester [aut],\n Gábor Csárdi [aut, cre],\n Posit Software, PBC [cph, fnd]",
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+ "pkgconfig": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "pkgconfig",
+ "Title": "Private Configuration for 'R' Packages",
+ "Version": "2.0.3",
+ "Author": "Gábor Csárdi",
+ "Maintainer": "Gábor Csárdi ",
+ "Description": "Set configuration options on a per-package basis.\n Options set by a given package only apply to that package,\n other packages are unaffected.",
+ "License": "MIT + file LICENSE",
+ "LazyData": "true",
+ "Imports": "utils",
+ "Suggests": "covr, testthat, disposables (>= 1.0.3)",
+ "URL": "https://github.com/r-lib/pkgconfig#readme",
+ "BugReports": "https://github.com/r-lib/pkgconfig/issues",
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+ "pkgload": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "pkgload",
+ "Title": "Simulate Package Installation and Attach",
+ "Version": "1.4.0",
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+ "Description": "Simulates the process of installing a package and then\n attaching it. This is a key part of the 'devtools' package as it\n allows you to rapidly iterate while developing a package.",
+ "License": "GPL-3",
+ "URL": "https://github.com/r-lib/pkgload, https://pkgload.r-lib.org",
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+ "description": {
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+ "License": "MIT + file LICENSE",
+ "Description": "Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics.",
+ "URL": "https://plotly-r.com, https://github.com/plotly/plotly.R,\nhttps://plotly.com/r/",
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+ "Author": "Simon Urbanek ",
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+ "URL": "http://www.rforge.net/png/",
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+ "Title": "Execute and Control System Processes",
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+ "Description": "Tools to run system processes in the background. It can\n check if a background process is running; wait on a background process\n to finish; get the exit status of finished processes; kill background\n processes. It can read the standard output and error of the processes,\n using non-blocking connections. 'processx' can poll a process for\n standard output or error, with a timeout. It can also poll several\n processes at once.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://processx.r-lib.org, https://github.com/r-lib/processx",
+ "BugReports": "https://github.com/r-lib/processx/issues",
+ "Depends": "R (>= 3.4.0)",
+ "Imports": "ps (>= 1.2.0), R6, utils",
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+ "Repository": "CRAN",
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+ "License": "MIT + file LICENSE",
+ "URL": "https://rstudio.github.io/promises/,\nhttps://github.com/rstudio/promises",
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+ "Maintainer": "Joe Cheng ",
+ "Repository": "CRAN",
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+ "description": {
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+ "Authors@R": "c(person(given = \"David\", family = \"Meyer\", role = c(\"aut\", \"cre\"), email = \"David.Meyer@R-project.org\"),\n person(given = \"Christian\", family = \"Buchta\", role = \"aut\"))",
+ "Description": "Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones. ",
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+ "Imports": "stats, utils",
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+ "Packaged": "2022-06-08 21:36:02 UTC; meyer",
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+ "Title": "Select from a Set of Strings",
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+ "Description": "A backend for the selecting functions of the 'tidyverse'. It\n makes it easy to implement select-like functions in your own packages\n in a way that is consistent with other 'tidyverse' interfaces for\n selection.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://tidyselect.r-lib.org, https://github.com/r-lib/tidyselect",
+ "BugReports": "https://github.com/r-lib/tidyselect/issues",
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+ "Maintainer": "Lionel Henry ",
+ "Repository": "CRAN",
+ "Date/Publication": "2024-03-11 14:10:02 UTC",
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+ }
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+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "tinytex",
+ "Type": "Package",
+ "Title": "Helper Functions to Install and Maintain TeX Live, and Compile\nLaTeX Documents",
+ "Version": "0.54",
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+ "Description": "Helper functions to install and maintain the 'LaTeX' distribution\n named 'TinyTeX' (), a lightweight, cross-platform,\n portable, and easy-to-maintain version of 'TeX Live'. This package also\n contains helper functions to compile 'LaTeX' documents, and install missing\n 'LaTeX' packages automatically.",
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+ "Suggests": "testit, rstudioapi",
+ "License": "MIT + file LICENSE",
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+ "BugReports": "https://github.com/rstudio/tinytex/issues",
+ "Encoding": "UTF-8",
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+ "Repository": "CRAN",
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+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
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+ "Version": "0.8-6",
+ "Title": "Measurement Units for R Vectors",
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+ "Depends": "R (>= 3.0.2)",
+ "Imports": "Rcpp",
+ "LinkingTo": "Rcpp (>= 0.12.10)",
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+ "VignetteBuilder": "knitr",
+ "Description": "Support for measurement units in R vectors, matrices\n and arrays: automatic propagation, conversion, derivation\n and simplification of units; raising errors in case of unit\n incompatibility. Compatible with the POSIXct, Date and difftime \n classes. Uses the UNIDATA udunits library and unit database for \n unit compatibility checking and conversion.\n Documentation about 'units' is provided in the paper by Pebesma, Mailund &\n Hiebert (2016, ), included in this package as a\n vignette; see 'citation(\"units\")' for details.",
+ "SystemRequirements": "udunits-2",
+ "License": "GPL-2",
+ "URL": "https://r-quantities.github.io/units/,\nhttps://github.com/r-quantities/units",
+ "BugReports": "https://github.com/r-quantities/units/issues",
+ "RoxygenNote": "7.3.2",
+ "Encoding": "UTF-8",
+ "Config/testthat/edition": "3",
+ "NeedsCompilation": "yes",
+ "Packaged": "2025-03-07 20:52:20 UTC; edzer",
+ "Author": "Edzer Pebesma [aut, cre] (),\n Thomas Mailund [aut],\n Tomasz Kalinowski [aut],\n James Hiebert [ctb],\n Iñaki Ucar [aut] (),\n Thomas Lin Pedersen [ctb]",
+ "Maintainer": "Edzer Pebesma ",
+ "Repository": "CRAN",
+ "Date/Publication": "2025-03-08 00:40:02 UTC",
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+ "RemoteRef": "units",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "0.8-6"
+ }
+ },
+ "utf8": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "utf8",
+ "Title": "Unicode Text Processing",
+ "Version": "1.2.4",
+ "Authors@R": "\n c(person(given = c(\"Patrick\", \"O.\"),\n family = \"Perry\",\n role = c(\"aut\", \"cph\")),\n person(given = \"Kirill\",\n family = \"M\\u00fcller\",\n role = \"cre\",\n email = \"kirill@cynkra.com\"),\n person(given = \"Unicode, Inc.\",\n role = c(\"cph\", \"dtc\"),\n comment = \"Unicode Character Database\"))",
+ "Description": "Process and print 'UTF-8' encoded international\n text (Unicode). Input, validate, normalize, encode, format, and\n display.",
+ "License": "Apache License (== 2.0) | file LICENSE",
+ "URL": "https://ptrckprry.com/r-utf8/, https://github.com/patperry/r-utf8",
+ "BugReports": "https://github.com/patperry/r-utf8/issues",
+ "Depends": "R (>= 2.10)",
+ "Suggests": "cli, covr, knitr, rlang, rmarkdown, testthat (>= 3.0.0),\nwithr",
+ "VignetteBuilder": "knitr, rmarkdown",
+ "Config/testthat/edition": "3",
+ "Encoding": "UTF-8",
+ "RoxygenNote": "7.2.3",
+ "NeedsCompilation": "yes",
+ "Packaged": "2023-10-22 13:43:19 UTC; kirill",
+ "Author": "Patrick O. Perry [aut, cph],\n Kirill Müller [cre],\n Unicode, Inc. [cph, dtc] (Unicode Character Database)",
+ "Maintainer": "Kirill Müller ",
+ "Repository": "CRAN",
+ "Date/Publication": "2023-10-22 21:50:02 UTC",
+ "Built": "R 4.4.3; aarch64-apple-darwin24.2.0; 2025-03-18 13:25:50 UTC; unix",
+ "RemoteType": "standard",
+ "RemotePkgRef": "utf8",
+ "RemoteRef": "utf8",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
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+ }
+ },
+ "vctrs": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "vctrs",
+ "Title": "Vector Helpers",
+ "Version": "0.7.1",
+ "Authors@R": "c(\n person(\"Hadley\", \"Wickham\", , \"hadley@posit.co\", role = \"aut\"),\n person(\"Lionel\", \"Henry\", , \"lionel@posit.co\", role = \"aut\"),\n person(\"Davis\", \"Vaughan\", , \"davis@posit.co\", role = c(\"aut\", \"cre\")),\n person(\"data.table team\", role = \"cph\",\n comment = \"Radix sort based on data.table's forder() and their contribution to R's order()\"),\n person(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"))\n )",
+ "Description": "Defines new notions of prototype and size that are used to\n provide tools for consistent and well-founded type-coercion and\n size-recycling, and are in turn connected to ideas of type- and\n size-stability useful for analysing function interfaces.",
+ "License": "MIT + file LICENSE",
+ "URL": "https://vctrs.r-lib.org/, https://github.com/r-lib/vctrs",
+ "BugReports": "https://github.com/r-lib/vctrs/issues",
+ "Depends": "R (>= 4.0.0)",
+ "Imports": "cli (>= 3.4.0), glue, lifecycle (>= 1.0.3), rlang (>= 1.1.7)",
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+ "VignetteBuilder": "knitr",
+ "Config/build/compilation-database": "true",
+ "Config/Needs/website": "tidyverse/tidytemplate",
+ "Config/testthat/edition": "3",
+ "Config/testthat/parallel": "true",
+ "Encoding": "UTF-8",
+ "Language": "en-GB",
+ "RoxygenNote": "7.3.3",
+ "NeedsCompilation": "yes",
+ "Packaged": "2026-01-22 13:56:47 UTC; davis",
+ "Author": "Hadley Wickham [aut],\n Lionel Henry [aut],\n Davis Vaughan [aut, cre],\n data.table team [cph] (Radix sort based on data.table's forder() and\n their contribution to R's order()),\n Posit Software, PBC [cph, fnd]",
+ "Maintainer": "Davis Vaughan ",
+ "Repository": "CRAN",
+ "Date/Publication": "2026-01-23 18:50:02 UTC",
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+ "RemoteType": "standard",
+ "RemotePkgRef": "vctrs",
+ "RemoteRef": "vctrs",
+ "RemoteRepos": "https://cloud.r-project.org",
+ "RemotePkgPlatform": "source",
+ "RemoteSha": "0.7.1"
+ }
+ },
+ "viridisLite": {
+ "Source": "CRAN",
+ "Repository": "https://cloud.r-project.org",
+ "description": {
+ "Package": "viridisLite",
+ "Type": "Package",
+ "Title": "Colorblind-Friendly Color Maps (Lite Version)",
+ "Version": "0.4.2",
+ "Date": "2023-05-02",
+ "Authors@R": "c(\n person(\"Simon\", \"Garnier\", email = \"garnier@njit.edu\", role = c(\"aut\", \"cre\")),\n person(\"Noam\", \"Ross\", email = \"noam.ross@gmail.com\", role = c(\"ctb\", \"cph\")),\n person(\"Bob\", \"Rudis\", email = \"bob@rud.is\", role = c(\"ctb\", \"cph\")),\n person(\"Marco\", \"Sciaini\", email = \"sciaini.marco@gmail.com\", role = c(\"ctb\", \"cph\")),\n person(\"Antônio Pedro\", \"Camargo\", role = c(\"ctb\", \"cph\")),\n person(\"Cédric\", \"Scherer\", email = \"scherer@izw-berlin.de\", role = c(\"ctb\", \"cph\"))\n )",
+ "Maintainer": "Simon Garnier