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ENH: #3 Update noaa ghcnd extract code
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| Original file line number | Diff line number | Diff line change |
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| #' This is a simply wrapper function to extract \code{noaa ghcn} | ||
| #' station, states, and countries metadata as individual tibbles. | ||
| #' This uses the \code{rnoaa} package directly to do this. | ||
| #' | ||
| #' @return This will be list with 3 separate tibbles named | ||
| #' \code{ghcnd_stations, ghcnd_states, ghcnd_countries} | ||
| #' | ||
| #' @examples | ||
| #' \dontrun{ | ||
| #' ghcnd_stations_metadata <- backburner::noaa_ghcn_stations_extract() | ||
| #' } | ||
| #' | ||
| #' @export | ||
| noaa_ghcn_stations_extract <- function(){ | ||
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| # Download the ghcn stations, states, countries table directly | ||
| ghcnd_stations <- rnoaa::ghcnd_stations() %>% tibble::as_tibble(x = .) | ||
| ghcnd_states <- rnoaa::ghcnd_states() %>% tibble::as_tibble(x = .) | ||
| ghcnd_countries <- rnoaa::ghcnd_countries() %>% tibble::as_tibble(x = .) | ||
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| # Do renaming of columns for ghcn country table | ||
| ghcnd_countries <- ghcnd_countries %>% | ||
| dplyr::rename(id_fips_code = code, | ||
| country_name = name) | ||
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| # Do renaming of columns for ghcn state table | ||
| ghcnd_states <- ghcnd_states %>% | ||
| dplyr::rename(state_code = code, | ||
| state_name = name) | ||
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| # Return output as a list of tibbles | ||
| out_ghcnd <- list("ghcnd_stations" = ghcnd_stations, | ||
| "ghcnd_states" = ghcnd_states, | ||
| "ghcnd_countries" = ghcnd_countries) | ||
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| base::return(out_ghcnd) | ||
| } |
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| #' Transformed GHCN-Daily Stations file. This is metadata for the GHCN-daily | ||
| #' file. It contains additional info on US/Canada states and country | ||
| #' information for each station | ||
| #' | ||
| #' @examples | ||
| #' \dontrun{ | ||
| #' ghcnd_stations_tform <- backburner::get_transform_ghcnd_stations() | ||
| #' } | ||
| #' | ||
| #' @return (tibble) : Transformed tibble of GHCN stations metadata | ||
| #' @export | ||
| get_transform_ghcnd_stations <- function(){ | ||
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| # First extract the station, states, and countries metadata | ||
| ghcnd_stations_metadata <- backburner::noaa_ghcn_stations_extract() | ||
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| # Download the ghcn stations, states, countries table | ||
| ghcnd_stations <- ghcnd_stations_metadata[["ghcnd_stations"]] | ||
| ghcnd_states <- ghcnd_stations_metadata[["ghcnd_states"]] | ||
| ghcnd_countries <- ghcnd_stations_metadata[["ghcnd_countries"]] | ||
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| # Do cleaning of ghcn station table to US/Canada state and country tables | ||
| ghcnd_stations <- ghcnd_stations %>% | ||
| dplyr::mutate(id_fips_code = | ||
| stringr::str_sub(string = id, start = 1, | ||
| end = 2), | ||
| id_network_code = | ||
| stringr::str_sub(string = id, start = 3, | ||
| end = 3), | ||
| id_station_numsys = | ||
| stringr::str_sub(string = id, start = 4, | ||
| end = 12)) %>% | ||
| dplyr::rename(state_code = state) %>% | ||
| dplyr::left_join(x = ., y = ghcnd_states, | ||
| by = c("state_code")) %>% | ||
| dplyr::left_join(x = ., y = ghcnd_countries, | ||
| by = c("id_fips_code")) %>% | ||
| dplyr::select(dplyr::starts_with("id"), | ||
| latitude, longitude, elevation, | ||
| state_code, state_name, country_name, | ||
| name, | ||
| dplyr::everything()) %>% | ||
| janitor::clean_names() | ||
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| base::return(ghcnd_stations) | ||
| } |
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| --- | ||
| title: "How to Extract NOAA GHCND stations metadata" | ||
| output: rmarkdown::html_vignette | ||
| vignette: > | ||
| %\VignetteIndexEntry{How to Extract NOAA GHCND stations metadata} | ||
| %\VignetteEngine{knitr::rmarkdown} | ||
| %\VignetteEncoding{UTF-8} | ||
| --- | ||
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| ```{r, include = FALSE} | ||
| knitr::opts_chunk$set( | ||
| collapse = TRUE, | ||
| comment = "#>" | ||
| ) | ||
| ``` | ||
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| We can easily get nicely transformed [NOAA Global Historical Climatology Network Daily (GHCN-D) station metadata](https://docs.opendata.aws/noaa-ghcn-pds/readme.html). This is | ||
| particularly useful for US/Canada related weather data. | ||
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| We can do this by simply running the following code: | ||
| ```{r setup, eval=FALSE} | ||
| library(backburner) | ||
| ghcnd_stations <- backburner::get_transform_ghcnd_stations() | ||
| ``` | ||
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| You can then use the `ghcnd_stations` tibble as required to get geospatial | ||
| metadata on the `GHCN-D` climate features. |