Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = FALSE,
warning = FALSE
)
## -----------------------------------------------------------------------------
# library(faunabr)
# #Carregar dados
# bf <- load_faunabr(data_dir = my_dir, #Pasta onde foi salvo o arquivo com get_faunabr()
# data_version = "latest", #Versão mais recente
# type = "short") #Versão resumida
# #> Loading version 1.3
## -----------------------------------------------------------------------------
# #Obter as opções disponíveis para filtrar por forma de vida, habitat e origem
# fauna_at <- fauna_attributes(data = bf,
# attribute = c("lifeForm", "habitat", "origin"))
# head(fauna_at$lifeForm)
# #> lifeForm
# #> 1 colonial
# #> 2 comensal
# #> 3 ectoparasito
# #> 4 ectoparasitoide
# #> 5 endoparasito
# #> 6 endoparasitoide
#
# head(fauna_at$habitat)
# #> habitat
# #> 1 agua_doce
# #> 2 aguas_subterraneas
# #> 3 arboreo
# #> 4 cavernicola
# #> 5 fossorial
# #> 6 hiporreico
#
# head(fauna_at$origin)
# #> origin
# #> 1 criptogenica
# #> 2 exotica
# #> 3 nativa
## -----------------------------------------------------------------------------
# insects_rj <- select_fauna(data = bf, include_subspecies = FALSE,
# phylum = "all",
# class = "Insecta", #Insetos
# order = "all",
# family = "all",
# genus = "all",
# lifeForm = "all", filter_lifeForm = "in",
# habitat = "arboreo", filter_habitat = "in",
# states = "RJ", #Rio de Janeiro
# filter_states = "in", #Que ocorrem NO RJ
# country = "all", filter_country = "in",
# origin = "nativa",
# taxonomicStatus = "valido")
# nrow(insects_rj)
# #> [1] 114
## -----------------------------------------------------------------------------
# #Primeiros 7 valores únicos de Estados onde as espécies ocorrem
# unique(insects_rj$states)[1:7]
# #> [1] "AC;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PE;RJ;RN;RO;RR;SE;SP;TO"
# #> [2] "BA;MA;MG;MT;PR;RJ;RS;SC;SP"
# #> [3] "ES;MG;PE;PR;RJ;RS;SP"
# #> [4] "ES;PR;RJ;SP"
# #> [5] "RJ"
# #> [6] "RJ;SP"
# #> [7] "ES;MG;RJ;RS;SC;SP"
## -----------------------------------------------------------------------------
# insects_rj_only <- select_fauna(data = bf, include_subspecies = FALSE,
# phylum = "all",
# class = "Insecta", #Insetos
# order = "all",
# family = "all",
# genus = "all",
# lifeForm = "all", filter_lifeForm = "in",
# habitat = "arboreo", filter_habitat = "in",
# states = "RJ", #Rio de Janeiro
# filter_states = "only", #Com ocorrência APENAS no RJ
# country = "all", filter_country = "in",
# origin = "nativa",
# taxonomicStatus = "valido")
# nrow(insects_rj_only)
# #> [1] 22
# unique(insects_rj_only$states)
# #> [1] "RJ"
## -----------------------------------------------------------------------------
# insects_south <- select_fauna(data = bf, include_subspecies = FALSE,
# phylum = "all",
# class = "Insecta", #Insetos
# order = "all",
# family = "all",
# genus = "all",
# lifeForm = "all", filter_lifeForm = "in",
# habitat = "all", filter_habitat = "in",
# states = c("PR", "SC", "RS"), #Estados do Sul do Brasil
# filter_states = "in", #EM qualquer um dos estados
# country = "all", filter_country = "in",
# origin = "nativa",
# taxonomicStatus = "valido")
# nrow(insects_south)
# #> [1] 11461
#
# #Primeiros 10 valores únicos de Estados onde as espécies ocorrem
# unique(insects_south$states)[1:10]
# #> [1] "PR;SP"
# #> [2] "BA;MT;RJ;RS"
# #> [3] "RS"
# #> [4] "PR"
# #> [5] "PR;RS"
# #> [6] "GO;PA;RO;RR;SC"
# #> [7] "MG;PR;SP"
# #> [8] "GO;MG;PR;RS;SC"
# #> [9] "GO;RJ;SC"
# #> [10] "AC;AL;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PB;PE;PI;PR;RJ;RN;RO;RR;RS;SC;SE;SP;TO"
## -----------------------------------------------------------------------------
# insects_south_and <- select_fauna(data = bf, include_subspecies = FALSE,
# phylum = "all",
# class = "Insecta", #Insetos
# order = "all",
# family = "all",
# genus = "all",
# lifeForm = "all", filter_lifeForm = "in",
# habitat = "all", filter_habitat = "in",
# states = c("PR", "SC", "RS"),
# filter_states = "and", #PR & SC & RS
# country = "all", filter_country = "in",
# origin = "nativa",
# taxonomicStatus = "valido")
# nrow(insects_south_and)
# #> [1] 1924
#
# #Primeiros 10 valores únicos de Estados onde as espécies ocorrem
# unique(insects_south_and$states)[1:10]
# #> [1] "GO;MG;PR;RS;SC"
# #> [2] "AC;AL;AM;AP;BA;CE;DF;ES;GO;MA;MG;MS;MT;PA;PB;PE;PI;PR;RJ;RN;RO;RR;RS;SC;SE;SP;TO"
# #> [3] "AC;AM;MG;MS;MT;PA;PE;PR;RO;RS;SC;SP"
# #> [4] "AM;BA;CE;DF;ES;GO;MG;MS;MT;PA;PE;PR;RJ;RS;SC;SP"
# #> [5] "AC;AM;AP;BA;CE;DF;ES;GO;MG;MS;MT;PA;PE;PR;RJ;RO;RR;RS;SC;SE;SP;TO"
# #> [6] "BA;ES;MG;PR;RJ;RS;SC;SP"
# #> [7] "AM;DF;ES;GO;PR;RJ;RR;RS;SC;SP"
# #> [8] "ES;GO;MG;PR;RJ;RS;SC;SP"
# #> [9] "AC;AM;AP;BA;CE;ES;GO;MA;MG;MT;PA;PR;RJ;RO;RS;SC;SP;TO"
# #> [10] "GO;MG;MS;PR;RO;RS;SC;SP"
## -----------------------------------------------------------------------------
# insects_south_only <- select_fauna(data = bf, include_subspecies = FALSE,
# phylum = "all",
# class = "Insecta", #Insetos
# order = "all",
# family = "all",
# genus = "all",
# lifeForm = "all", filter_lifeForm = "in",
# habitat = "all", filter_habitat = "in",
# states = c("PR", "SC", "RS"),
# filter_states = "only", #Apenas no PR & SC & RS
# country = "all", filter_country = "in",
# origin = "nativa",
# taxonomicStatus = "valido")
# nrow(insects_south_only)
# #> [1] 134
#
# #Valor único de Estados onde as espécies ocorrem
# unique(insects_south_only$states)
# #> [1] "PR;RS;SC"
## -----------------------------------------------------------------------------
# complete_names <- c("Pantera onca (Linnaeus, 1758)",
# "Zonotrichia capensis subtorquata Swainson, 1837",
# "Mazama bororo Duarte, 1996",
# "Mazama jucunda Thomas, 1913",
# "Arrenurus tumulosus intercursor",
# "Araucaria angustifolia")
# #Panthera onca com erros de digitação para ilustrar como a próxima função os corrige
# #Araucaria angustifolia (uma planta) foi usada apenas como um exemplo que será utilizado para ilustrar a próxima função
# binomial_names <- extract_binomial(species_names = complete_names)
# binomial_names
# #> [1] "Pantera onca" "Zonotrichia capensis"
# #> [3] "Mazama bororo" "Mazama jucunda"
# #> [5] "Arrenurus tumulosus" "Araucaria angustifolia"
## -----------------------------------------------------------------------------
# #Checar nomes
# checked_names <- check_fauna_names(data = bf,
# species = binomial_names,
# include_subspecies = FALSE,
# max_distance = 0.1)
# tibble::tibble(checked_names) #Exibir tabela como tibble
# #> # A tibble: 6 x 9
# #> input_name Spelling Suggested_name Distance taxonomicStatus nomenclaturalStatus validName family matches
# #> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr>
# #> 1 "Zonotrichia capensis" Correct Zonotrichia capensis 0 valido NA NA Passerellidae single
# #> 2 "Mazama bororo" Correct Mazama bororo 0 sinonimo NA Mazama jucunda Cervidae single
# #> 3 "Mazama jucunda" Correct Mazama jucunda 0 valido NA NA Cervidae single
# #> 4 "Arrenurus tumulosus" Correct Arrenurus tumulosus 0 valido NA NA Arrenuridae single
# #> 5 "Pantera onca" Probably_incorrect Panthera onca 2 valido NA NA Felidae single
# #> 6 "Araucaria angustifolia" Not_found NA NA NA NA NA NA none
## -----------------------------------------------------------------------------
# #Obter apenas nomes validos
# valids <- unique(checked_names$validName)
# valids <- na.omit(valids) #Remove NAs
#
# #Subselecionar especies
# my_sp <- subset_fauna(data = bf, species = valids,
# include_subspecies = FALSE)
# tibble::tibble(my_sp)
# # A tibble: 4 x 21
# #> species subspecies scientificName validName kingdom phylum class order family genus lifeForm habitat states countryCode origin
# #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
# #> 1 Panthera onca NA Panthera onca~ NA Animal~ Chord~ Mamm~ Carn~ Felid~ Pant~ "vida_l~ "terre~ AC;AM~ AR;BO;BR;B~ nativa
# #> 2 Arrenurus tumulo~ NA Arrenurus (In~ NA Animal~ Arthr~ Arac~ Trom~ Arren~ Arre~ "" "" NA NA NA
# #> 3 Mazama jucunda NA Mazama jucund~ NA Animal~ Chord~ Mamm~ Arti~ Cervi~ Maza~ "herbiv~ "terre~ BA;ES~ BR nativa
# #> 4 Zonotrichia cape~ NA Zonotrichia c~ NA Animal~ Chord~ Aves Pass~ Passe~ Zono~ "" "" NA NA nativa
# # i 5 more variables: nomenclaturalStatus <chr>, vernacularName <chr>, taxonRank <chr>, id <int>, language <chr>
## -----------------------------------------------------------------------------
# my_sp2 <- subset_fauna(data = bf, species = valids,
# include_subspecies = TRUE)
# tibble::tibble(my_sp2) #print data.frame as tibble
# #> # A tibble: 14 × 19
# #> species subspecies scientificName validName kingdom phylum class order family genus lifeForm habitat states countryCode #> origin
# #> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> #> <chr>
# #> 1 Panthera on… "" Panthera onca… "" Animal… Chord… Mamm… Carn… Felid… Pant… "free_l… "terre… AC;AM… argentina;… #> "nati…
# #> 2 Arrenurus (… "" Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #>
# #> 3 Arrenurus (… "Arrenuru… Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #>
# #> 4 Arrenurus (… "Arrenuru… Arrenurus (In… "" Animal… Arthr… Arac… Trom… Arren… Arre… "" "" NA brazil "" #>
# #> 5 Mazama jucu… "" Mazama jucund… "" Animal… Chord… Mamm… Arti… Cervi… Maza… "herbiv… "terre… BA;ES… brazil #> "nati…
# #> 6 Zonotrichia… "" Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AL;AP… brazil #> "nati…
# #> 7 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AP brazil #> "nati…
# #> 8 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" RR brazil #> "nati…
# #> 9 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" RR brazil #> "nati…
# #> 10 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" BA;MA… brazil #> "nati…
# #> 11 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" PA brazil #> "nati…
# #> 12 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" AP;PA… brazil #> "nati…
# #> 13 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" ES;MG… brazil #> "nati…
# #> 14 Zonotrichia… "Zonotric… Zonotrichia c… "" Animal… Chord… Aves Pass… Passe… Zono… "free_l… "" TO brazil #> "nati…
# #> # ℹ 4 more variables: taxonomicStatus <chr>, nomenclaturalStatus <chr>, vernacularName <chr>, taxonRank <chr>
# #>
## -----------------------------------------------------------------------------
# spp <- c("Panthera onca", "Mazama jucunda", "Subulo gouzoubira")
# spp_syn <- fauna_synonym(data = bf, species = spp)
# spp_syn
# #> validName synonym taxonomicStatus
# #> 49343 Panthera onca <NA> valido
# #> 60523 Mazama jucunda Mazama bororo sinonimo
# #> 61168 Subulo gouzoubira Mazama gouazoubira sinonimo
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