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# Finding species that are only a single dataset and nowhere else: human | |
# observations edition | |
if(file.exists("query_results/0024071-251009101135966.zip")) { | |
species_per_dataset <- | |
readr::read_delim("query_results/0024071-251009101135966.zip") | |
} else { | |
species_per_dataset <- | |
rgbif::occ_download_get("0024071-251009101135966") |> | |
rgbif::occ_download_import() |
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# Passerines in South America | |
# Data read from GBIF occurrence download (SQL QUERY) | |
pas_sa <- | |
rgbif::occ_download_get("0028483-251009101135966") |> | |
rgbif::occ_download_import() |> | |
dplyr::filter(!is.na(month)) | |
# Identify the 3 most common genera ------------------------------------- | |
common_genera <- pas_sa |> |
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# Get all rato data as a flat csv | |
if(!rlang::is_installed("ratatouille", version = "1.0.4")){ | |
pak::pak("inbo/ratatouille") | |
} | |
library(ratatouille) | |
# To run this function you need to store your RATO database credentials as env variables, as RATO_USER and RATO_PWD, otherwise you'll get an error. | |
all_rato_data <- ratatouille() |
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return_default <- function(my_param = 50){ | |
rlang::eval_bare(formals(rlang::caller_fn(0))[["my_param"]]) | |
} |
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object_name_message <- function(x){ | |
cli::cli_inform("The object you passed is called {substitute(x)}") | |
} | |
object_name_message(letters) |
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repo <- "my_org/my_repo" | |
zenodo_token <- "token from url in webhook page of repo" | |
repo_response <- | |
httr2::request("https://api.github.com/repos") %>% | |
httr2::req_url_path_append(repo) %>% | |
httr2::req_perform() %>% | |
httr2::resp_body_json() | |
release_response <- |
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ripple_shuffle <- function(object) { | |
purrr::map( | |
seq(1, length(object) / 2), | |
~ c( | |
purrr::chuck(object, .x), | |
purrr::chuck(object, length(object) - .x + 1) | |
) | |
) %>% | |
unlist() | |
} |
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get_inat_obs_radius <- function(taxon_id, lat, lng, radius) { | |
api_response <- httr2::request( | |
"https://api.inaturalist.org/v1/observations/" | |
) %>% | |
httr2::req_url_query( | |
taxon_id = taxon_id, | |
lat = lat, | |
lng = lng, | |
radius = radius | |
) %>% |
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library(dplyr) | |
# Ensure ETN API-beta version | |
remotes::install_github("inbo/[email protected]") | |
library(etn) | |
# Get number of detections, species and animals for lifewatch presentation | |
project_codes_to_investigate <- c( | |
"2010_PHD_REUBENS", | |
"2011_RIVIERPRIK", | |
"2012_LEOPOLDKANAAL", |
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# We are trying to find the closest allele per gene | |
## You could possibly do this with this package as well: | |
## https://bioconductor.org/packages/release/bioc/vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.html#finding-the-nearest-genomic-position-in-granges-objects | |
library(dplyr) # A Grammar of Data Manipulation | |
library(assertthat) # Easy Pre and Post Assertions | |
# Some example data |
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