In today’s lecture, we are going to talk about getting data from the web with R. Nowadays, the amount of data online increases exponentially everyday. How to get such data and analyze them to gain knowledge is critical. We will briefly talk about the scenarios that we can get data from online. I won’t even try to cover most of the things since this topic can be a whole course by itself. Before we get into the lecture, here are some R books about this topic.
XML and Web Technologies for Data Sciences with R: classic book, but not free
Web Scraping with R: a free short book!
Some Acronyms
WWW: World Wide WebW3C: World Wide Web ConsortiumURL: Uniform Resource LocatorHTTP: HyperText Transfer ProtocolXML: eXtensible Markup LanguageHTML: HyperText Markup LanguageCSS: Cascade Style SheetsJSON: JavaScript Object NotationBased on Wikipedia:
Web scraping (web harvesting or web data extraction) is a computer software technique of extracting information from websites.
Web scraping focuses on the transformation of unstructured data on the web, typically in HTML format, into structured data that can be stored and analyzed in a central local database or spreadsheet.
First, let’s take a look at a simple XML file:
<?xml version="1.0"?>
<!DOCTYPE movies>
<movie mins="126" lang="en">
<!-- this is a comment -->
<title>Good Will Hunting</title>
<director>
<first_name>Gus</first_name>
<last_name>Van Sant</last_name>
</director>
<year>1998</year>
<genre>drama</genre>
</movie>HTML is an XML dialect:
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<title>Your Page Title</title>
<link rel="stylesheet" href="/css/style.css" />
</head>
<body>
<h1>A First-level Heading</h1>
<p>A paragraph.</p>
<img src="/images/foo.png" alt="A nice image" />
<ul>
<li>An item.</li>
<li>Another item.</li>
<li>Yet another item.</li>
</ul>
<script src="/js/bar.js"></script>
</body>
</html>Rcurl: low level wrapper for libcurl that
provides convenient functions to allow you to fetch URIs, get & post
forms; basically, it allows us to use R as a Web Client.httr: similar to Rcurl; provides a
user-friendly interface for executing HTTP methods and provides support
for modern web authentication protocols (OAuth 1.0, OAuth 2.0). It is a
wrapper around the curl packagervest: a higher level package mostly based on
httr. It is simpler to use for basic tasks.Rselenium: can be used to automate interactions and
extract page content from dynamically generated webpages (i.e., those
requiring user interaction to display results like clicking on
button)Task: to extract all titles of the Web Scrapping Wiki page
Open the website with Chrome, right click and select
Inspect and see what tags are used for
page/section/subsection titles.
Or install the Selectorgadget add-on for Chrome
It seems that we can just extract the table of content and we will get all what we need.
library(rvest)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionwiki = read_html("https://en.wikipedia.org/wiki/Web_scraping")
wiki %>%
html_elements(css = c("div#toc.toc")) # based on inspect## {xml_nodeset (1)}
## [1] <div id="toc" class="toc" role="navigation" aria-labelledby="mw-toc-headi ...wiki %>%
html_elements(css = c("#toc")) # based on selectorgadget## {xml_nodeset (1)}
## [1] <div id="toc" class="toc" role="navigation" aria-labelledby="mw-toc-headi ...toc = wiki %>%
html_elements(css = c("#toc")) %>%
html_text()
toc## [1] "Contents\n1 History\n2 Techniques\n2.1 Human copy-and-paste\n2.2 Text pattern matching\n2.3 HTTP programming\n2.4 HTML parsing\n2.5 DOM parsing\n2.6 Vertical aggregation\n2.7 Semantic annotation recognizing\n2.8 Computer vision web-page analysis\n\n3 Software\n4 Legal issues\n4.1 United States\n4.2 European Union\n4.3 Australia\n4.4 India\n\n5 Methods to prevent web scraping\n6 See also\n7 References\n"The texts are not in the format that we want, so we need to do some clean using what we learned in previous lecture.
(toc2 <- stringr::str_split(toc, pattern = "\n")[[1]])## [1] "Contents"
## [2] "1 History"
## [3] "2 Techniques"
## [4] "2.1 Human copy-and-paste"
## [5] "2.2 Text pattern matching"
## [6] "2.3 HTTP programming"
## [7] "2.4 HTML parsing"
## [8] "2.5 DOM parsing"
## [9] "2.6 Vertical aggregation"
## [10] "2.7 Semantic annotation recognizing"
## [11] "2.8 Computer vision web-page analysis"
## [12] ""
## [13] "3 Software"
## [14] "4 Legal issues"
## [15] "4.1 United States"
## [16] "4.2 European Union"
## [17] "4.3 Australia"
## [18] "4.4 India"
## [19] ""
## [20] "5 Methods to prevent web scraping"
## [21] "6 See also"
## [22] "7 References"
## [23] ""# it seems that we just need those have number(s)
(toc3 <- grep(pattern = "\\d", x = toc2, value = TRUE))## [1] "1 History"
## [2] "2 Techniques"
## [3] "2.1 Human copy-and-paste"
## [4] "2.2 Text pattern matching"
## [5] "2.3 HTTP programming"
## [6] "2.4 HTML parsing"
## [7] "2.5 DOM parsing"
## [8] "2.6 Vertical aggregation"
## [9] "2.7 Semantic annotation recognizing"
## [10] "2.8 Computer vision web-page analysis"
## [11] "3 Software"
## [12] "4 Legal issues"
## [13] "4.1 United States"
## [14] "4.2 European Union"
## [15] "4.3 Australia"
## [16] "4.4 India"
## [17] "5 Methods to prevent web scraping"
## [18] "6 See also"
## [19] "7 References"Challenge: create a data frame, with the first column to be the numbers in toc3 (i.e, 1, 2, 2.1, etc.) and the second column to be the text without leading space
library(rvest, warn.conflicts = FALSE)
library(RSelenium)
# to set up a server to run javascript
rs = RSelenium::rsDriver(browser = "firefox")
rsc = rs$client
rsc$navigate("https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8")
# now get the page source
ht = rsc$getPageSource()
url = rvest::read_html(ht[[1]])
lectures = html_elements(url, css = '#video-title') # show how to get this
lec_names = html_text2(lectures)
lec_links = html_attr(lectures, "href")
lec_links_full = paste0("https://www.youtube.com", lec_links)
# try one link
# does not work
url2 = read_html(lec_links_full[1])
x = html_elements(url2, css = "#info")
# need this
rsc$navigate(lec_links_full[1])
ht2 = rsc$getPageSource()
ok2 <- rvest::read_html(ht2[[1]])
# show how to get this
view = html_elements(ok2, css = ".ytd-video-view-count-renderer")
view_count = html_text(view[1])
view_count
as.numeric(gsub(",| views", "", view_count))
# put it as a function
get_view = function(link){
rsc$navigate(link)
url2 = rsc$getPageSource()
Sys.sleep(1)
url2 <- rvest::read_html(url2[[1]])
view = html_elements(url2, css = ".ytd-video-view-count-renderer")
view_count = html_text(view[1])
view_count = as.integer(gsub(",| views", "", view_count))
return(view_count)
}
# run it
view_counts = data.frame(names = lec_names, views = NA_integer_)
for(i in 1:length(lec_links_full)){
cat(lec_links_full[i], "\t")
view_count = get_view(lec_links_full[i])
# for some reason, sometimes it takes multiple tries
while(length(view_count) == 0)
view_count = get_view(lec_links_full[i])
view_counts$views[i] = view_count
}
# save results
write.csv(view_counts, "view.csv")
rs$server$stop() # close the serverwhile()
loop?Nowadays many companies, websites, sources, etc. use APIs as their primary means to share information and data. Many large websites like Reddit, Youtube, Twitter, and Facebook offer APIs so that data analysts and data scientists can access interesting data.
And having an API to share data has become a standard thing to have. In the context of biological data, many data repositories also have APIs to share data (e.g., figshare, dryad, dataone, GBIF, iNaturalist).
An API is a set of rules, protocols, and tools for building software and applications. It allows programmers to request data directly from a website. When a website like Facebook sets up an API, they are essentially setting up a computer that waits for data requests.
Most APIs don’t allow you to send too many requests at once (i.e. asynchronous requests). The main reason to limit the number of requests is to prevent users from overloading the API servers.
We will need to write code in R that creates the request and tells the computer running the API what we need. That computer will then read our code, process the request, and return nicely-formatted data that can be easily parsed by existing R libraries.
APIs have some key verbs:
| http Method | Description |
|---|---|
| GET | retrieves whatever information is identified by the Request-URI |
| POST | request with data enclosed in the request body |
| HEAD | identical to GET except that the server MUST NOT return a message-body in the response |
| PUT | requests that the enclosed entity be stored under the supplied Request-URI |
| DELETE | requests that the origin server delete the resource identified by the Request-URI |
| TRACE | invokes a remote, application-layer loop-back of the request message |
| CONNECT | for use with a proxy that can dynamically switch to being a tunnel |
There are several types of Web service APIs (e.g. XML-RPC, JSON-RPC and SOAP) but the most popular is Representational State Transfer or REST. RESTful APIs can return output as XML, JSON, CSV and several other data formats. Each API has documentation and specifications which determine how data can be transferred.
R has a few HTTP client packages: “crul”, “curl”, “httr”, and “RCurl”;
A simple example:
dj <- httr::GET('https://api.github.com/users/daijiang')
djInfo <- jsonlite::fromJSON(httr::content(dj, "text"), simplifyVector = T)
djInfo## $login
## [1] "daijiang"
##
## $id
## [1] 1696911
##
## $node_id
## [1] "MDQ6VXNlcjE2OTY5MTE="
##
## $avatar_url
## [1] "https://avatars.githubusercontent.com/u/1696911?v=4"
##
## $gravatar_id
## [1] ""
##
## $url
## [1] "https://api.github.com/users/daijiang"
##
## $html_url
## [1] "https://github.com/daijiang"
##
## $followers_url
## [1] "https://api.github.com/users/daijiang/followers"
##
## $following_url
## [1] "https://api.github.com/users/daijiang/following{/other_user}"
##
## $gists_url
## [1] "https://api.github.com/users/daijiang/gists{/gist_id}"
##
## $starred_url
## [1] "https://api.github.com/users/daijiang/starred{/owner}{/repo}"
##
## $subscriptions_url
## [1] "https://api.github.com/users/daijiang/subscriptions"
##
## $organizations_url
## [1] "https://api.github.com/users/daijiang/orgs"
##
## $repos_url
## [1] "https://api.github.com/users/daijiang/repos"
##
## $events_url
## [1] "https://api.github.com/users/daijiang/events{/privacy}"
##
## $received_events_url
## [1] "https://api.github.com/users/daijiang/received_events"
##
## $type
## [1] "User"
##
## $site_admin
## [1] FALSE
##
## $name
## [1] "Daijiang Li"
##
## $company
## NULL
##
## $blog
## [1] "https://www.dlilab.com"
##
## $location
## [1] "Baton Rouge, LA"
##
## $email
## NULL
##
## $hireable
## [1] TRUE
##
## $bio
## NULL
##
## $twitter_username
## NULL
##
## $public_repos
## [1] 81
##
## $public_gists
## [1] 7
##
## $followers
## [1] 119
##
## $following
## [1] 22
##
## $created_at
## [1] "2012-05-01T22:20:20Z"
##
## $updated_at
## [1] "2022-09-25T19:36:20Z"gbif_country <- httr::GET('https://api.gbif.org/v1/enumeration/country')
jsonlite::fromJSON(httr::content(gbif_country, "text"))## No encoding supplied: defaulting to UTF-8.## iso2 iso3 isoNumerical title
## 1 AF AFG 4 Afghanistan
## 2 AX ALA 248 Åland Islands
## 3 AL ALB 8 Albania
## 4 DZ DZA 12 Algeria
## 5 AS ASM 16 American Samoa
## 6 AD AND 20 Andorra
## 7 AO AGO 24 Angola
## 8 AI AIA 660 Anguilla
## 9 AQ ATA 10 Antarctica
## 10 AG ATG 28 Antigua and Barbuda
## 11 AR ARG 32 Argentina
## 12 AM ARM 51 Armenia
## 13 AW ABW 533 Aruba
## 14 AU AUS 36 Australia
## 15 AT AUT 40 Austria
## 16 AZ AZE 31 Azerbaijan
## 17 BS BHS 44 Bahamas
## 18 BH BHR 48 Bahrain
## 19 BD BGD 50 Bangladesh
## 20 BB BRB 52 Barbados
## 21 BY BLR 112 Belarus
## 22 BE BEL 56 Belgium
## 23 BZ BLZ 84 Belize
## 24 BJ BEN 204 Benin
## 25 BM BMU 60 Bermuda
## 26 BT BTN 64 Bhutan
## 27 BO BOL 68 Bolivia (Plurinational State of)
## 28 BQ BES 535 Bonaire, Sint Eustatius and Saba
## 29 BA BIH 70 Bosnia and Herzegovina
## 30 BW BWA 72 Botswana
## 31 BV BVT 74 Bouvet Island
## 32 BR BRA 76 Brazil
## 33 IO IOT 86 British Indian Ocean Territory
## 34 BN BRN 96 Brunei Darussalam
## 35 BG BGR 100 Bulgaria
## 36 BF BFA 854 Burkina Faso
## 37 BI BDI 108 Burundi
## 38 KH KHM 116 Cambodia
## 39 CM CMR 120 Cameroon
## 40 CA CAN 124 Canada
## 41 CV CPV 132 Cabo Verde
## 42 KY CYM 136 Cayman Islands
## 43 CF CAF 140 Central African Republic
## 44 TD TCD 148 Chad
## 45 CL CHL 152 Chile
## 46 CN CHN 156 China
## 47 CX CXR 162 Christmas Island
## 48 CC CCK 166 Cocos (Keeling) Islands
## 49 CO COL 170 Colombia
## 50 KM COM 174 Comoros
## 51 CD COD 180 Congo, Democratic Republic of the
## 52 CG COG 178 Congo
## 53 CK COK 184 Cook Islands
## 54 CR CRI 188 Costa Rica
## 55 CI CIV 384 Côte d’Ivoire
## 56 HR HRV 191 Croatia
## 57 CU CUB 192 Cuba
## 58 CW CUW 531 Curaçao
## 59 CY CYP 196 Cyprus
## 60 CZ CZE 203 Czechia
## 61 DK DNK 208 Denmark
## 62 DJ DJI 262 Djibouti
## 63 DM DMA 212 Dominica
## 64 DO DOM 214 Dominican Republic
## 65 EC ECU 218 Ecuador
## 66 EG EGY 818 Egypt
## 67 SV SLV 222 El Salvador
## 68 GQ GNQ 226 Equatorial Guinea
## 69 ER ERI 232 Eritrea
## 70 EE EST 233 Estonia
## 71 ET ETH 231 Ethiopia
## 72 FK FLK 238 Falkland Islands (Malvinas)
## 73 FO FRO 234 Faroe Islands
## 74 FJ FJI 242 Fiji
## 75 FI FIN 246 Finland
## 76 FR FRA 250 France
## 77 GF GUF 254 French Guiana
## 78 PF PYF 258 French Polynesia
## 79 TF ATF 260 French Southern Territories
## 80 GA GAB 266 Gabon
## 81 GM GMB 270 Gambia
## 82 GE GEO 268 Georgia
## 83 DE DEU 276 Germany
## 84 GH GHA 288 Ghana
## 85 GI GIB 292 Gibraltar
## 86 GR GRC 300 Greece
## 87 GL GRL 304 Greenland
## 88 GD GRD 308 Grenada
## 89 GP GLP 312 Guadeloupe
## 90 GU GUM 316 Guam
## 91 GT GTM 320 Guatemala
## 92 GG GGY 831 Guernsey
## 93 GN GIN 324 Guinea
## 94 GW GNB 624 Guinea-Bissau
## 95 GY GUY 328 Guyana
## 96 HT HTI 332 Haiti
## 97 HM HMD 334 Heard Island and McDonald Islands
## 98 VA VAT 336 Holy See
## 99 HN HND 340 Honduras
## 100 HK HKG 344 Hong Kong
## 101 HU HUN 348 Hungary
## 102 IS ISL 352 Iceland
## 103 IN IND 356 India
## 104 ID IDN 360 Indonesia
## 105 IR IRN 364 Iran (Islamic Republic of)
## 106 IQ IRQ 368 Iraq
## 107 IE IRL 372 Ireland
## 108 IM IMN 833 Isle of Man
## 109 IL ISR 376 Israel
## 110 IT ITA 380 Italy
## 111 JM JAM 388 Jamaica
## 112 JP JPN 392 Japan
## 113 JE JEY 832 Jersey
## 114 JO JOR 400 Jordan
## 115 KZ KAZ 398 Kazakhstan
## 116 KE KEN 404 Kenya
## 117 KI KIR 296 Kiribati
## 118 KP PRK 408 Korea (Democratic People’s Republic of)
## 119 KR KOR 410 Korea, Republic of
## 120 KW KWT 414 Kuwait
## 121 KG KGZ 417 Kyrgyzstan
## 122 LA LAO 418 Lao People’s Democratic Republic
## 123 LV LVA 428 Latvia
## 124 LB LBN 422 Lebanon
## 125 LS LSO 426 Lesotho
## 126 LR LBR 430 Liberia
## 127 LY LBY 434 Libya
## 128 LI LIE 438 Liechtenstein
## 129 LT LTU 440 Lithuania
## 130 LU LUX 442 Luxembourg
## 131 MO MAC 446 Macao
## 132 MK MKD 807 North Macedonia
## 133 MG MDG 450 Madagascar
## 134 MW MWI 454 Malawi
## 135 MY MYS 458 Malaysia
## 136 MV MDV 462 Maldives
## 137 ML MLI 466 Mali
## 138 MT MLT 470 Malta
## 139 MH MHL 584 Marshall Islands
## 140 MQ MTQ 474 Martinique
## 141 MR MRT 478 Mauritania
## 142 MU MUS 480 Mauritius
## 143 YT MYT 175 Mayotte
## 144 MX MEX 484 Mexico
## 145 FM FSM 583 Micronesia (Federated States of)
## 146 MD MDA 498 Moldova, Republic of
## 147 MC MCO 492 Monaco
## 148 MN MNG 496 Mongolia
## 149 ME MNE 499 Montenegro
## 150 MS MSR 500 Montserrat
## 151 MA MAR 504 Morocco
## 152 MZ MOZ 508 Mozambique
## 153 MM MMR 104 Myanmar
## 154 NA NAM 516 Namibia
## 155 NR NRU 520 Nauru
## 156 NP NPL 524 Nepal
## 157 NL NLD 528 Netherlands
## 158 NC NCL 540 New Caledonia
## 159 NZ NZL 554 New Zealand
## 160 NI NIC 558 Nicaragua
## 161 NE NER 562 Niger
## 162 NG NGA 566 Nigeria
## 163 NU NIU 570 Niue
## 164 NF NFK 574 Norfolk Island
## 165 MP MNP 580 Northern Mariana Islands
## 166 NO NOR 578 Norway
## 167 OM OMN 512 Oman
## 168 PK PAK 586 Pakistan
## 169 PW PLW 585 Palau
## 170 PS PSE 275 Palestine, State of
## 171 PA PAN 591 Panama
## 172 PG PNG 598 Papua New Guinea
## 173 PY PRY 600 Paraguay
## 174 PE PER 604 Peru
## 175 PH PHL 608 Philippines
## 176 PN PCN 612 Pitcairn
## 177 PL POL 616 Poland
## 178 PT PRT 620 Portugal
## 179 PR PRI 630 Puerto Rico
## 180 QA QAT 634 Qatar
## 181 RE REU 638 Réunion
## 182 RO ROU 642 Romania
## 183 RU RUS 643 Russian Federation
## 184 RW RWA 646 Rwanda
## 185 BL BLM 652 Saint Barthélemy
## 186 SH SHN 654 Saint Helena, Ascension and Tristan da Cunha
## 187 KN KNA 659 Saint Kitts and Nevis
## 188 LC LCA 662 Saint Lucia
## 189 MF MAF 663 Saint Martin (French part)
## 190 PM SPM 666 Saint Pierre and Miquelon
## 191 VC VCT 670 Saint Vincent and the Grenadines
## 192 WS WSM 882 Samoa
## 193 SM SMR 674 San Marino
## 194 ST STP 678 Sao Tome and Principe
## 195 SA SAU 682 Saudi Arabia
## 196 SN SEN 686 Senegal
## 197 RS SRB 688 Serbia
## 198 SC SYC 690 Seychelles
## 199 SL SLE 694 Sierra Leone
## 200 SG SGP 702 Singapore
## 201 SX SXM 534 Sint Maarten (Dutch part)
## 202 SK SVK 703 Slovakia
## 203 SI SVN 705 Slovenia
## 204 SB SLB 90 Solomon Islands
## 205 SO SOM 706 Somalia
## 206 ZA ZAF 710 South Africa
## 207 GS SGS 239 South Georgia and the South Sandwich Islands
## 208 SS SSD 728 South Sudan
## 209 ES ESP 724 Spain
## 210 LK LKA 144 Sri Lanka
## 211 SD SDN 729 Sudan
## 212 SR SUR 740 Suriname
## 213 SJ SJM 744 Svalbard and Jan Mayen
## 214 SZ SWZ 748 Eswatini
## 215 SE SWE 752 Sweden
## 216 CH CHE 756 Switzerland
## 217 SY SYR 760 Syrian Arab Republic
## 218 TW TWN 158 Chinese Taipei
## 219 TJ TJK 762 Tajikistan
## 220 TZ TZA 834 Tanzania, United Republic of
## 221 TH THA 764 Thailand
## 222 TL TLS 626 Timor-Leste
## 223 TG TGO 768 Togo
## 224 TK TKL 772 Tokelau
## 225 TO TON 776 Tonga
## 226 TT TTO 780 Trinidad and Tobago
## 227 TN TUN 788 Tunisia
## 228 TR TUR 792 Türkiye
## 229 TM TKM 795 Turkmenistan
## 230 TC TCA 796 Turks and Caicos Islands
## 231 TV TUV 798 Tuvalu
## 232 UG UGA 800 Uganda
## 233 UA UKR 804 Ukraine
## 234 AE ARE 784 United Arab Emirates
## 235 GB GBR 826 United Kingdom of Great Britain and Northern Ireland
## 236 US USA 840 United States of America
## 237 UM UMI 581 United States Minor Outlying Islands
## 238 UY URY 858 Uruguay
## 239 UZ UZB 860 Uzbekistan
## 240 VU VUT 548 Vanuatu
## 241 VE VEN 862 Venezuela (Bolivarian Republic of)
## 242 VN VNM 704 Viet Nam
## 243 VG VGB 92 Virgin Islands (British)
## 244 VI VIR 850 Virgin Islands (U.S.)
## 245 WF WLF 876 Wallis and Futuna
## 246 EH ESH 732 Western Sahara
## 247 YE YEM 887 Yemen
## 248 ZM ZMB 894 Zambia
## 249 ZW ZWE 716 Zimbabwe
## gbifRegion enumName
## 1 ASIA AFGHANISTAN
## 2 EUROPE ALAND_ISLANDS
## 3 EUROPE ALBANIA
## 4 AFRICA ALGERIA
## 5 OCEANIA AMERICAN_SAMOA
## 6 EUROPE ANDORRA
## 7 AFRICA ANGOLA
## 8 LATIN_AMERICA ANGUILLA
## 9 ANTARCTICA ANTARCTICA
## 10 LATIN_AMERICA ANTIGUA_BARBUDA
## 11 LATIN_AMERICA ARGENTINA
## 12 EUROPE ARMENIA
## 13 LATIN_AMERICA ARUBA
## 14 OCEANIA AUSTRALIA
## 15 EUROPE AUSTRIA
## 16 EUROPE AZERBAIJAN
## 17 LATIN_AMERICA BAHAMAS
## 18 ASIA BAHRAIN
## 19 ASIA BANGLADESH
## 20 LATIN_AMERICA BARBADOS
## 21 EUROPE BELARUS
## 22 EUROPE BELGIUM
## 23 LATIN_AMERICA BELIZE
## 24 AFRICA BENIN
## 25 LATIN_AMERICA BERMUDA
## 26 ASIA BHUTAN
## 27 LATIN_AMERICA BOLIVIA
## 28 LATIN_AMERICA BONAIRE_SINT_EUSTATIUS_SABA
## 29 EUROPE BOSNIA_HERZEGOVINA
## 30 AFRICA BOTSWANA
## 31 ANTARCTICA BOUVET_ISLAND
## 32 LATIN_AMERICA BRAZIL
## 33 ASIA BRITISH_INDIAN_OCEAN_TERRITORY
## 34 ASIA BRUNEI_DARUSSALAM
## 35 EUROPE BULGARIA
## 36 AFRICA BURKINA_FASO
## 37 AFRICA BURUNDI
## 38 ASIA CAMBODIA
## 39 AFRICA CAMEROON
## 40 NORTH_AMERICA CANADA
## 41 AFRICA CAPE_VERDE
## 42 LATIN_AMERICA CAYMAN_ISLANDS
## 43 AFRICA CENTRAL_AFRICAN_REPUBLIC
## 44 AFRICA CHAD
## 45 LATIN_AMERICA CHILE
## 46 ASIA CHINA
## 47 ASIA CHRISTMAS_ISLAND
## 48 ASIA COCOS_ISLANDS
## 49 LATIN_AMERICA COLOMBIA
## 50 AFRICA COMOROS
## 51 AFRICA CONGO_DEMOCRATIC_REPUBLIC
## 52 AFRICA CONGO
## 53 OCEANIA COOK_ISLANDS
## 54 LATIN_AMERICA COSTA_RICA
## 55 AFRICA CÔTE_DIVOIRE
## 56 EUROPE CROATIA
## 57 LATIN_AMERICA CUBA
## 58 LATIN_AMERICA CURAÇAO
## 59 EUROPE CYPRUS
## 60 EUROPE CZECH_REPUBLIC
## 61 EUROPE DENMARK
## 62 AFRICA DJIBOUTI
## 63 LATIN_AMERICA DOMINICA
## 64 LATIN_AMERICA DOMINICAN_REPUBLIC
## 65 LATIN_AMERICA ECUADOR
## 66 AFRICA EGYPT
## 67 LATIN_AMERICA EL_SALVADOR
## 68 AFRICA EQUATORIAL_GUINEA
## 69 AFRICA ERITREA
## 70 EUROPE ESTONIA
## 71 AFRICA ETHIOPIA
## 72 LATIN_AMERICA FALKLAND_ISLANDS
## 73 EUROPE FAROE_ISLANDS
## 74 OCEANIA FIJI
## 75 EUROPE FINLAND
## 76 EUROPE FRANCE
## 77 LATIN_AMERICA FRENCH_GUIANA
## 78 OCEANIA FRENCH_POLYNESIA
## 79 ANTARCTICA FRENCH_SOUTHERN_TERRITORIES
## 80 AFRICA GABON
## 81 AFRICA GAMBIA
## 82 EUROPE GEORGIA
## 83 EUROPE GERMANY
## 84 AFRICA GHANA
## 85 EUROPE GIBRALTAR
## 86 EUROPE GREECE
## 87 NORTH_AMERICA GREENLAND
## 88 LATIN_AMERICA GRENADA
## 89 LATIN_AMERICA GUADELOUPE
## 90 OCEANIA GUAM
## 91 LATIN_AMERICA GUATEMALA
## 92 EUROPE GUERNSEY
## 93 AFRICA GUINEA
## 94 AFRICA GUINEA_BISSAU
## 95 LATIN_AMERICA GUYANA
## 96 LATIN_AMERICA HAITI
## 97 ANTARCTICA HEARD_MCDONALD_ISLANDS
## 98 EUROPE VATICAN
## 99 LATIN_AMERICA HONDURAS
## 100 ASIA HONG_KONG
## 101 EUROPE HUNGARY
## 102 EUROPE ICELAND
## 103 ASIA INDIA
## 104 ASIA INDONESIA
## 105 ASIA IRAN
## 106 ASIA IRAQ
## 107 EUROPE IRELAND
## 108 EUROPE ISLE_OF_MAN
## 109 EUROPE ISRAEL
## 110 EUROPE ITALY
## 111 LATIN_AMERICA JAMAICA
## 112 ASIA JAPAN
## 113 EUROPE JERSEY
## 114 ASIA JORDAN
## 115 EUROPE KAZAKHSTAN
## 116 AFRICA KENYA
## 117 OCEANIA KIRIBATI
## 118 ASIA KOREA_NORTH
## 119 ASIA KOREA_SOUTH
## 120 ASIA KUWAIT
## 121 EUROPE KYRGYZSTAN
## 122 ASIA LAO
## 123 EUROPE LATVIA
## 124 ASIA LEBANON
## 125 AFRICA LESOTHO
## 126 AFRICA LIBERIA
## 127 AFRICA LIBYA
## 128 EUROPE LIECHTENSTEIN
## 129 EUROPE LITHUANIA
## 130 EUROPE LUXEMBOURG
## 131 ASIA MACAO
## 132 EUROPE MACEDONIA
## 133 AFRICA MADAGASCAR
## 134 AFRICA MALAWI
## 135 ASIA MALAYSIA
## 136 ASIA MALDIVES
## 137 AFRICA MALI
## 138 EUROPE MALTA
## 139 OCEANIA MARSHALL_ISLANDS
## 140 LATIN_AMERICA MARTINIQUE
## 141 AFRICA MAURITANIA
## 142 AFRICA MAURITIUS
## 143 AFRICA MAYOTTE
## 144 LATIN_AMERICA MEXICO
## 145 OCEANIA MICRONESIA
## 146 EUROPE MOLDOVA
## 147 EUROPE MONACO
## 148 ASIA MONGOLIA
## 149 EUROPE MONTENEGRO
## 150 LATIN_AMERICA MONTSERRAT
## 151 AFRICA MOROCCO
## 152 AFRICA MOZAMBIQUE
## 153 ASIA MYANMAR
## 154 AFRICA NAMIBIA
## 155 OCEANIA NAURU
## 156 ASIA NEPAL
## 157 EUROPE NETHERLANDS
## 158 OCEANIA NEW_CALEDONIA
## 159 OCEANIA NEW_ZEALAND
## 160 LATIN_AMERICA NICARAGUA
## 161 AFRICA NIGER
## 162 AFRICA NIGERIA
## 163 OCEANIA NIUE
## 164 OCEANIA NORFOLK_ISLAND
## 165 OCEANIA NORTHERN_MARIANA_ISLANDS
## 166 EUROPE NORWAY
## 167 ASIA OMAN
## 168 ASIA PAKISTAN
## 169 OCEANIA PALAU
## 170 ASIA PALESTINIAN_TERRITORY
## 171 LATIN_AMERICA PANAMA
## 172 OCEANIA PAPUA_NEW_GUINEA
## 173 LATIN_AMERICA PARAGUAY
## 174 LATIN_AMERICA PERU
## 175 ASIA PHILIPPINES
## 176 OCEANIA PITCAIRN
## 177 EUROPE POLAND
## 178 EUROPE PORTUGAL
## 179 LATIN_AMERICA PUERTO_RICO
## 180 ASIA QATAR
## 181 AFRICA RÉUNION
## 182 EUROPE ROMANIA
## 183 EUROPE RUSSIAN_FEDERATION
## 184 AFRICA RWANDA
## 185 LATIN_AMERICA SAINT_BARTHÉLEMY
## 186 AFRICA SAINT_HELENA_ASCENSION_TRISTAN_DA_CUNHA
## 187 LATIN_AMERICA SAINT_KITTS_NEVIS
## 188 LATIN_AMERICA SAINT_LUCIA
## 189 LATIN_AMERICA SAINT_MARTIN_FRENCH
## 190 NORTH_AMERICA SAINT_PIERRE_MIQUELON
## 191 LATIN_AMERICA SAINT_VINCENT_GRENADINES
## 192 OCEANIA SAMOA
## 193 EUROPE SAN_MARINO
## 194 AFRICA SAO_TOME_PRINCIPE
## 195 ASIA SAUDI_ARABIA
## 196 AFRICA SENEGAL
## 197 EUROPE SERBIA
## 198 AFRICA SEYCHELLES
## 199 AFRICA SIERRA_LEONE
## 200 ASIA SINGAPORE
## 201 LATIN_AMERICA SINT_MAARTEN
## 202 EUROPE SLOVAKIA
## 203 EUROPE SLOVENIA
## 204 OCEANIA SOLOMON_ISLANDS
## 205 AFRICA SOMALIA
## 206 AFRICA SOUTH_AFRICA
## 207 ANTARCTICA SOUTH_GEORGIA_SANDWICH_ISLANDS
## 208 AFRICA SOUTH_SUDAN
## 209 EUROPE SPAIN
## 210 ASIA SRI_LANKA
## 211 AFRICA SUDAN
## 212 LATIN_AMERICA SURINAME
## 213 EUROPE SVALBARD_JAN_MAYEN
## 214 AFRICA SWAZILAND
## 215 EUROPE SWEDEN
## 216 EUROPE SWITZERLAND
## 217 ASIA SYRIA
## 218 ASIA TAIWAN
## 219 EUROPE TAJIKISTAN
## 220 AFRICA TANZANIA
## 221 ASIA THAILAND
## 222 ASIA TIMOR_LESTE
## 223 AFRICA TOGO
## 224 OCEANIA TOKELAU
## 225 OCEANIA TONGA
## 226 LATIN_AMERICA TRINIDAD_TOBAGO
## 227 AFRICA TUNISIA
## 228 EUROPE TURKEY
## 229 EUROPE TURKMENISTAN
## 230 LATIN_AMERICA TURKS_CAICOS_ISLANDS
## 231 OCEANIA TUVALU
## 232 AFRICA UGANDA
## 233 EUROPE UKRAINE
## 234 ASIA UNITED_ARAB_EMIRATES
## 235 EUROPE UNITED_KINGDOM
## 236 NORTH_AMERICA UNITED_STATES
## 237 OCEANIA UNITED_STATES_OUTLYING_ISLANDS
## 238 LATIN_AMERICA URUGUAY
## 239 EUROPE UZBEKISTAN
## 240 OCEANIA VANUATU
## 241 LATIN_AMERICA VENEZUELA
## 242 ASIA VIETNAM
## 243 LATIN_AMERICA VIRGIN_ISLANDS_BRITISH
## 244 LATIN_AMERICA VIRGIN_ISLANDS
## 245 OCEANIA WALLIS_FUTUNA
## 246 AFRICA WESTERN_SAHARA
## 247 ASIA YEMEN
## 248 AFRICA ZAMBIA
## 249 AFRICA ZIMBABWEgbif_example <- httr::GET('https://api.gbif.org/v1/occurrence/search?year=1998,1999&country=US')
jsonlite::fromJSON(httr::content(gbif_example, "text"))## No encoding supplied: defaulting to UTF-8.## $offset
## [1] 0
##
## $limit
## [1] 20
##
## $endOfRecords
## [1] FALSE
##
## $count
## [1] 6650798
##
## $results
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## publishingOrgKey networkKeys
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## 20 90cc71b0-055b-11d8-b84e-b8a03c50a862 99d66b6c-9087-452f-a9d4-f15f2c2d0e7e
## installationKey publishingCountry protocol
## 1 60454014-f762-11e1-a439-00145eb45e9a DE BIOCASE
## 2 60454014-f762-11e1-a439-00145eb45e9a DE BIOCASE
## 3 a957a663-2f17-415f-b1c8-5cf6398df8ed US DWC_ARCHIVE
## 4 a957a663-2f17-415f-b1c8-5cf6398df8ed US DWC_ARCHIVE
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## 19 a957a663-2f17-415f-b1c8-5cf6398df8ed US DWC_ARCHIVE
## 20 a957a663-2f17-415f-b1c8-5cf6398df8ed US DWC_ARCHIVE
## lastCrawled lastParsed crawlId
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## hostingOrganizationKey basisOfRecord occurrenceStatus
## 1 57254bd0-8256-11d8-b7ed-b8a03c50a862 PRESERVED_SPECIMEN PRESENT
## 2 57254bd0-8256-11d8-b7ed-b8a03c50a862 PRESERVED_SPECIMEN PRESENT
## 3 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 4 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 5 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 6 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 7 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 8 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 9 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 10 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 11 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 12 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 13 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 14 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 15 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 16 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 17 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 18 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 19 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## 20 2053a639-84c3-4be5-b8bc-96b6d88a976c PRESERVED_SPECIMEN PRESENT
## taxonKey kingdomKey
## 1 0 0
## 2 0 0
## 3 2979014 6
## 4 2685008 6
## 5 5288819 6
## 6 5407100 6
## 7 5415104 6
## 8 2705848 6
## 9 7323035 6
## 10 2985943 6
## 11 3818122 6
## 12 2925396 6
## 13 3033943 6
## 14 3025572 6
## 15 3025707 6
## 16 5289938 6
## 17 2945830 6
## 18 5361914 6
## 19 2769796 6
## 20 6712760 6
## scientificName
## 1 incertae sedis
## 2 incertae sedis
## 3 Acacia podalyriifolia A.Cunn. ex G.Don
## 4 Agathis Salisb.
## 5 Ananas comosus (L.) Merr.
## 6 Annona glabra L.
## 7 Bontia daphnoides L.
## 8 Urochloa mutica (Forssk.) T.Q.Nguyen
## 9 Brachychiton populneus (Schott & Endl.) R.Br.
## 10 Kalanchoe tubiflora (Harv.) Raym.-Hamet
## 11 Chirita moonii Gardner
## 12 Citharexylum spinosum L.
## 13 Cocculus orbiculatus (L.) DC.
## 14 Cotoneaster pannosus Franch.
## 15 Cotoneaster harrovianus Wilson
## 16 Digitaria insularis (L.) Mez ex Ekman
## 17 Erythrina L.
## 18 Ficus drupacea Thunb.
## 19 Furcraea foetida (L.) Haw.
## 20 Hibiscus campylosiphon var. glabrescens (Warb. ex Perkins) Borss.Waalk.
## kingdom taxonRank year month day eventDate typeStatus
## 1 incertae sedis KINGDOM 1999 1 1 1999-01-01T00:00:00 PARATYPE
## 2 incertae sedis KINGDOM 1999 1 1 1999-01-01T00:00:00 PARATYPE
## 3 Plantae SPECIES 1999 1 7 1999-01-07T00:00:00 <NA>
## 4 Plantae GENUS 1999 1 13 1999-01-13T00:00:00 <NA>
## 5 Plantae SPECIES 1999 1 13 1999-01-13T00:00:00 <NA>
## 6 Plantae SPECIES 1999 1 12 1999-01-12T00:00:00 <NA>
## 7 Plantae SPECIES 1999 1 2 1999-01-02T00:00:00 <NA>
## 8 Plantae SPECIES 1999 1 9 1999-01-09T00:00:00 <NA>
## 9 Plantae SPECIES 1999 1 12 1999-01-12T00:00:00 <NA>
## 10 Plantae SPECIES 1999 1 13 1999-01-13T00:00:00 <NA>
## 11 Plantae SPECIES 1999 1 26 1999-01-26T00:00:00 <NA>
## 12 Plantae SPECIES 1999 1 5 1999-01-05T00:00:00 <NA>
## 13 Plantae SPECIES 1999 1 12 1999-01-12T00:00:00 <NA>
## 14 Plantae SPECIES 1999 1 7 1999-01-07T00:00:00 <NA>
## 15 Plantae SPECIES 1999 1 7 1999-01-07T00:00:00 <NA>
## 16 Plantae SPECIES 1999 1 13 1999-01-13T00:00:00 <NA>
## 17 Plantae GENUS 1999 1 12 1999-01-12T00:00:00 <NA>
## 18 Plantae SPECIES 1999 1 12 1999-01-12T00:00:00 <NA>
## 19 Plantae SPECIES 1999 1 14 1999-01-14T00:00:00 <NA>
## 20 Plantae VARIETY 1999 1 12 1999-01-12T00:00:00 <NA>
## typifiedName
## 1 Cryptoperidinopsis brodyi Steid., Landsberg, P. L. Mason, Vogelbein, Tester & Litaker
## 2 Cryptoperidinopsis brodyi Steid., Landsberg, P. L. Mason, Vogelbein, Tester & Litaker
## 3 <NA>
## 4 <NA>
## 5 <NA>
## 6 <NA>
## 7 <NA>
## 8 <NA>
## 9 <NA>
## 10 <NA>
## 11 <NA>
## 12 <NA>
## 13 <NA>
## 14 <NA>
## 15 <NA>
## 16 <NA>
## 17 <NA>
## 18 <NA>
## 19 <NA>
## 20 <NA>
## issues
## 1 TAXON_MATCH_NONE, INSTITUTION_MATCH_NONE
## 2 TAXON_MATCH_NONE, INSTITUTION_MATCH_NONE
## 3 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 4 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 5 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 6 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 7 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 8 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 9 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 10 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 11 INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 12 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 13 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 14 GEODETIC_DATUM_ASSUMED_WGS84, TAXON_MATCH_FUZZY, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 15 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 16 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 17 TAXON_MATCH_HIGHERRANK, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 18 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 19 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## 20 GEODETIC_DATUM_ASSUMED_WGS84, INSTITUTION_MATCH_FUZZY, COLLECTION_MATCH_FUZZY
## lastInterpreted
## 1 2022-10-11T21:16:32.173+00:00
## 2 2022-10-11T21:16:32.174+00:00
## 3 2022-09-09T02:30:13.216+00:00
## 4 2022-09-09T02:30:06.501+00:00
## 5 2022-09-09T02:30:12.115+00:00
## 6 2022-09-09T02:30:13.662+00:00
## 7 2022-09-09T02:30:09.660+00:00
## 8 2022-09-09T02:30:12.200+00:00
## 9 2022-09-09T02:30:03.328+00:00
## 10 2022-09-09T02:30:11.399+00:00
## 11 2022-09-09T02:30:09.368+00:00
## 12 2022-09-09T02:30:12.880+00:00
## 13 2022-09-09T02:30:14.276+00:00
## 14 2022-09-09T02:30:11.545+00:00
## 15 2022-09-09T02:30:11.628+00:00
## 16 2022-09-09T02:30:11.266+00:00
## 17 2022-09-09T02:30:02.532+00:00
## 18 2022-09-09T02:30:10.199+00:00
## 19 2022-09-09T02:30:04.332+00:00
## 20 2022-09-09T02:30:10.054+00:00
## license identifiers media
## 1 http://creativecommons.org/licenses/by/4.0/legalcode NULL NULL
## 2 http://creativecommons.org/licenses/by/4.0/legalcode NULL NULL
## 3 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 4 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 5 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 6 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 7 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 8 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 9 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 10 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
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## 12 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
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## 14 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 15 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 16 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 17 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 18 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 19 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## 20 http://creativecommons.org/publicdomain/zero/1.0/legalcode NULL NULL
## facts relations gadm.level0.gid gadm.level0.name gadm.level1.gid
## 1 NULL NULL <NA> <NA> <NA>
## 2 NULL NULL <NA> <NA> <NA>
## 3 NULL NULL USA United States USA.12_1
## 4 NULL NULL USA United States USA.12_1
## 5 NULL NULL USA United States USA.12_1
## 6 NULL NULL USA United States USA.12_1
## 7 NULL NULL USA United States USA.12_1
## 8 NULL NULL USA United States USA.12_1
## 9 NULL NULL USA United States USA.12_1
## 10 NULL NULL USA United States USA.12_1
## 11 NULL NULL <NA> <NA> <NA>
## 12 NULL NULL USA United States USA.12_1
## 13 NULL NULL USA United States USA.12_1
## 14 NULL NULL USA United States USA.12_1
## 15 NULL NULL USA United States USA.12_1
## 16 NULL NULL USA United States USA.12_1
## 17 NULL NULL <NA> <NA> <NA>
## 18 NULL NULL USA United States USA.12_1
## 19 NULL NULL USA United States USA.12_1
## 20 NULL NULL USA United States USA.12_1
## gadm.level1.name gadm.level2.gid gadm.level2.name isInCluster countryCode
## 1 <NA> <NA> <NA> FALSE US
## 2 <NA> <NA> <NA> FALSE US
## 3 Hawaii USA.12.5_1 Maui FALSE US
## 4 Hawaii USA.12.5_1 Maui FALSE US
## 5 Hawaii USA.12.5_1 Maui FALSE US
## 6 Hawaii USA.12.5_1 Maui FALSE US
## 7 Hawaii USA.12.5_1 Maui FALSE US
## 8 Hawaii USA.12.2_1 Honolulu FALSE US
## 9 Hawaii USA.12.5_1 Maui FALSE US
## 10 Hawaii USA.12.5_1 Maui FALSE US
## 11 <NA> <NA> <NA> FALSE US
## 12 Hawaii USA.12.5_1 Maui FALSE US
## 13 Hawaii USA.12.5_1 Maui FALSE US
## 14 Hawaii USA.12.5_1 Maui FALSE US
## 15 Hawaii USA.12.5_1 Maui FALSE US
## 16 Hawaii USA.12.5_1 Maui FALSE US
## 17 <NA> <NA> <NA> FALSE US
## 18 Hawaii USA.12.5_1 Maui FALSE US
## 19 Hawaii USA.12.5_1 Maui FALSE US
## 20 Hawaii USA.12.5_1 Maui FALSE US
## recordedByIDs identifiedByIDs country catalogNumber
## 1 NULL NULL United States of America 6612
## 2 NULL NULL United States of America 6613
## 3 NULL NULL United States of America 661863
## 4 NULL NULL United States of America 660353
## 5 NULL NULL United States of America 660354
## 6 NULL NULL United States of America 660358
## 7 NULL NULL United States of America 661856
## 8 NULL NULL United States of America 660363
## 9 NULL NULL United States of America 660361
## 10 NULL NULL United States of America 660351
## 11 NULL NULL United States of America 666261
## 12 NULL NULL United States of America 661850
## 13 NULL NULL United States of America 660357
## 14 NULL NULL United States of America 661874
## 15 NULL NULL United States of America 661875
## 16 NULL NULL United States of America 660355
## 17 NULL NULL United States of America 637088
## 18 NULL NULL United States of America 660359
## 19 NULL NULL United States of America 660349
## 20 NULL NULL United States of America 660360
## institutionCode
## 1 BGBM
## 2 BGBM
## 3 BPBM
## 4 BPBM
## 5 BPBM
## 6 BPBM
## 7 BPBM
## 8 BPBM
## 9 BPBM
## 10 BPBM
## 11 BPBM
## 12 BPBM
## 13 BPBM
## 14 BPBM
## 15 BPBM
## 16 BPBM
## 17 BPBM
## 18 BPBM
## 19 BPBM
## 20 BPBM
## locality
## 1 Neuse River estuary, North Carolina, USA (1999)
## 2 Neuse River estuary, North Carolina, USA (1999)
## 3 East Maui, Kula, in garden at 280 Waipoli Road, on W side of road
## 4 W Maui Mountain, Maunalei Arboreum
## 5 W Maui, Maui Land & Pineapple Company
## 6 W Maui, West Maui Mt., Maunalei Arboretum
## 7 W Maui, Kapalua, Fleming's Beach
## 8 4050 Tantalus Drive at Puu Ohia trailhead
## 9 W Maui, West Maui Mt. Maunalei Arboretum
## 10 W Maui, S of Napili Honokowai, S of Kahana Stream
## 11 Koloa District, NTBG in Lawai Valley, pump 6, nursery area (world collection)
## 12 East Maui, Makawao District, Kula, at intersection of Puanani and Kekaulike Ave. (Puiehuiki)
## 13 S of Honokahua Bay, 0.25 km S of RT. 30, on side road. Roadside
## 14 East Maui, Polipoli State Park
## 15 East Maui, Polipoli State Park campground
## 16 W Maui, Maui Land & Pineapple Company
## 17 Koloa Distr., Lawai Valley, National Tropical Botanical Garden, Medicinal Area
## 18 W Maui, West Maui Mt. Maunalei Arboretum
## 19 W Maui, S of Napili Honokowai, N of Kahana Stream
## 20 W Maui, West Maui Mt. Maunalei Arboretum
## collectionCode gbifID phylumKey classKey orderKey familyKey genusKey
## 1 Algaterra Types 15140753 NA NA NA NA NA
## 2 Algaterra Types 15140757 NA NA NA NA NA
## 3 BISH 34593294 7707728 220 1370 5386 2978223
## 4 BISH 34815390 7707728 194 640 3924 2685008
## 5 BISH 35071275 7707728 196 1369 3740 2699430
## 6 BISH 35091290 7707728 220 718 9291 3155252
## 7 BISH 35573844 7707728 220 408 2390 2925376
## 8 BISH 35586154 7707728 196 1369 3073 2704067
## 9 BISH 35589638 7707728 220 941 6685 3152191
## 10 BISH 35623021 7707728 220 7219248 2406 2985928
## 11 BISH 35953390 7707728 220 408 6654 6365598
## 12 BISH 36028735 7707728 220 408 6689 7853269
## 13 BISH 36074249 7707728 220 399 2411 3033940
## 14 BISH 36177253 7707728 220 691 5015 3025563
## 15 BISH 36179001 7707728 220 691 5015 3025563
## 16 BISH 36504748 7707728 196 1369 3073 2704525
## 17 BISH 36765490 7707728 220 1370 5386 2945830
## 18 BISH 36847777 7707728 220 691 6640 2984588
## 19 BISH 36889299 7707728 196 1169 7683 2766202
## 20 BISH 37179686 7707728 220 941 6685 3152542
## speciesKey acceptedTaxonKey
## 1 NA NA
## 2 NA NA
## 3 2979014 2979014
## 4 NA 2685008
## 5 5288819 5288819
## 6 5407100 5407100
## 7 5415104 5415104
## 8 2705851 2705851
## 9 7323035 7323035
## 10 2985940 2985940
## 11 8199564 8199564
## 12 2925396 2925396
## 13 3033943 3033943
## 14 3025572 3025572
## 15 3025707 3025707
## 16 5289938 5289938
## 17 NA 2945830
## 18 5361914 5361914
## 19 2769796 2769796
## 20 3938833 6712760
## acceptedScientificName
## 1 <NA>
## 2 <NA>
## 3 Acacia podalyriifolia A.Cunn. ex G.Don
## 4 Agathis Salisb.
## 5 Ananas comosus (L.) Merr.
## 6 Annona glabra L.
## 7 Bontia daphnoides L.
## 8 Brachiaria mutica (Forssk.) Stapf
## 9 Brachychiton populneus (Schott & Endl.) R.Br.
## 10 Kalanchoe delagoensis Eckl. & Zeyh.
## 11 Henckelia moonii (Gardner) D.J.Middleton & Mich.Möller
## 12 Citharexylum spinosum L.
## 13 Cocculus orbiculatus (L.) DC.
## 14 Cotoneaster pannosus Franch.
## 15 Cotoneaster harrovianus Wilson
## 16 Digitaria insularis (L.) Mez ex Ekman
## 17 Erythrina L.
## 18 Ficus drupacea Thunb.
## 19 Furcraea foetida (L.) Haw.
## 20 Hibiscus campylosiphon var. glabrescens (Warb. ex Perkins) Borss.Waalk.
## phylum order family genus
## 1 <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA>
## 3 Tracheophyta Fabales Fabaceae Acacia
## 4 Tracheophyta Pinales Araucariaceae Agathis
## 5 Tracheophyta Poales Bromeliaceae Ananas
## 6 Tracheophyta Magnoliales Annonaceae Annona
## 7 Tracheophyta Lamiales Scrophulariaceae Bontia
## 8 Tracheophyta Poales Poaceae Brachiaria
## 9 Tracheophyta Malvales Malvaceae Brachychiton
## 10 Tracheophyta Saxifragales Crassulaceae Kalanchoe
## 11 Tracheophyta Lamiales Gesneriaceae Henckelia
## 12 Tracheophyta Lamiales Verbenaceae Citharexylum
## 13 Tracheophyta Ranunculales Menispermaceae Cocculus
## 14 Tracheophyta Rosales Rosaceae Cotoneaster
## 15 Tracheophyta Rosales Rosaceae Cotoneaster
## 16 Tracheophyta Poales Poaceae Digitaria
## 17 Tracheophyta Fabales Fabaceae Erythrina
## 18 Tracheophyta Rosales Moraceae Ficus
## 19 Tracheophyta Asparagales Asparagaceae Furcraea
## 20 Tracheophyta Malvales Malvaceae Hibiscus
## species genericName specificEpithet taxonomicStatus
## 1 <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA>
## 3 Acacia podalyriifolia Acacia podalyriifolia ACCEPTED
## 4 <NA> Agathis <NA> ACCEPTED
## 5 Ananas comosus Ananas comosus ACCEPTED
## 6 Annona glabra Annona glabra ACCEPTED
## 7 Bontia daphnoides Bontia daphnoides ACCEPTED
## 8 Brachiaria mutica Urochloa mutica SYNONYM
## 9 Brachychiton populneus Brachychiton populneus ACCEPTED
## 10 Kalanchoe delagoensis Kalanchoe tubiflora SYNONYM
## 11 Henckelia moonii Chirita moonii SYNONYM
## 12 Citharexylum spinosum Citharexylum spinosum ACCEPTED
## 13 Cocculus orbiculatus Cocculus orbiculatus ACCEPTED
## 14 Cotoneaster pannosus Cotoneaster pannosus ACCEPTED
## 15 Cotoneaster harrovianus Cotoneaster harrovianus ACCEPTED
## 16 Digitaria insularis Digitaria insularis ACCEPTED
## 17 <NA> Erythrina <NA> ACCEPTED
## 18 Ficus drupacea Ficus drupacea ACCEPTED
## 19 Furcraea foetida Furcraea foetida ACCEPTED
## 20 Hibiscus campylosiphon Hibiscus campylosiphon ACCEPTED
## iucnRedListCategory decimalLongitude decimalLatitude stateProvince
## 1 <NA> NA NA <NA>
## 2 <NA> NA NA <NA>
## 3 LC -156.317 20.7333 Hawaii
## 4 NE -156.617 20.9667 Hawaii
## 5 NE -156.617 21.0000 Hawaii
## 6 LC -156.617 20.9667 Hawaii
## 7 NE -156.650 21.0000 Hawaii
## 8 LC -157.800 21.3167 Hawaii
## 9 NE -156.617 20.9667 Hawaii
## 10 NE -156.667 20.9667 Hawaii
## 11 NE NA NA Hawaii
## 12 LC -156.300 20.7667 Hawaii
## 13 NE -156.633 21.0000 Hawaii
## 14 NE -156.317 20.6667 Hawaii
## 15 NE -156.317 20.6667 Hawaii
## 16 LC -156.617 21.0000 Hawaii
## 17 NE NA NA Hawaii
## 18 LC -156.617 20.9667 Hawaii
## 19 NE -156.667 20.9667 Hawaii
## 20 <NA> -156.617 20.9667 Hawaii
## waterBody modified
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 Pacific Ocean 2001-11-26T00:00:00.000+00:00
## 4 Pacific Ocean 2011-12-22T13:05:10.000+00:00
## 5 Pacific Ocean 2014-02-01T15:52:57.000+00:00
## 6 Pacific Ocean 2002-10-23T17:24:10.000+00:00
## 7 Pacific Ocean 2000-04-26T00:00:00.000+00:00
## 8 Pacific Ocean 2014-05-04T13:55:33.000+00:00
## 9 Pacific Ocean 2002-10-23T17:24:14.000+00:00
## 10 Pacific Ocean 2002-10-23T17:23:56.000+00:00
## 11 Pacific Ocean 2001-01-25T00:00:00.000+00:00
## 12 Pacific Ocean 2000-04-26T00:00:00.000+00:00
## 13 Pacific Ocean 2003-04-08T16:40:31.000+00:00
## 14 Pacific Ocean 2000-04-25T00:00:00.000+00:00
## 15 Pacific Ocean 2000-04-25T00:00:00.000+00:00
## 16 Pacific Ocean 2014-03-15T15:28:14.000+00:00
## 17 Pacific Ocean 1999-12-07T00:00:00.000+00:00
## 18 Pacific Ocean 2002-10-23T17:24:11.000+00:00
## 19 Pacific Ocean 2002-10-23T17:23:50.000+00:00
## 20 Pacific Ocean 2002-10-23T17:24:12.000+00:00
## institutionKey collectionKey
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 4 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 5 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 6 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 7 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
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## 11 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 12 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 13 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 14 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 15 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 16 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 17 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 18 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 19 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## 20 fdee1b94-e933-4a6e-9a85-05cc39a085a6 a421a197-9584-4564-9d59-767d61a52a0c
## datasetName
## 1 <NA>
## 2 <NA>
## 3 Herbarium Pacificum Hawaiian Islands Specimens
## 4 Herbarium Pacificum Hawaiian Islands Specimens
## 5 Herbarium Pacificum Hawaiian Islands Specimens
## 6 Herbarium Pacificum Hawaiian Islands Specimens
## 7 Herbarium Pacificum Hawaiian Islands Specimens
## 8 Herbarium Pacificum Hawaiian Islands Specimens
## 9 Herbarium Pacificum Hawaiian Islands Specimens
## 10 Herbarium Pacificum Hawaiian Islands Specimens
## 11 Herbarium Pacificum Hawaiian Islands Specimens
## 12 Herbarium Pacificum Hawaiian Islands Specimens
## 13 Herbarium Pacificum Hawaiian Islands Specimens
## 14 Herbarium Pacificum Hawaiian Islands Specimens
## 15 Herbarium Pacificum Hawaiian Islands Specimens
## 16 Herbarium Pacificum Hawaiian Islands Specimens
## 17 Herbarium Pacificum Hawaiian Islands Specimens
## 18 Herbarium Pacificum Hawaiian Islands Specimens
## 19 Herbarium Pacificum Hawaiian Islands Specimens
## 20 Herbarium Pacificum Hawaiian Islands Specimens
## recordedBy identifiedBy geodeticDatum
## 1 <NA> <NA> <NA>
## 2 <NA> <NA> <NA>
## 3 Starr, F. Martz, K. G.P.Lewis WGS84
## 4 Annable, C.R. Oppenheimer, H. Staples, G.W. WGS84
## 5 Annable, C.R. Meidell, S.; Oppenheimer, H. C.R.Annable WGS84
## 6 Annable, C.R. Oppenheimer, H. C.R.Annable WGS84
## 7 Starr, F. Martz, K. G.W.Staples; G.Carr WGS84
## 8 Annable, C.R. Nom. rev. C.Imada WGS84
## 9 Annable, C.R. Oppenheimer, H. C.R.Annable WGS84
## 10 Annable, C.R. Oppenheimer, H. Nom. rev. C.Imada WGS84
## 11 Lorence, D.H. Staples, G.W. <NA>
## 12 Starr, F. Martz, K. Staples, G.W. WGS84
## 13 Annable, C.R. Oppenheimer, H. Staples, G.W. WGS84
## 14 Starr, F. Martz, K. Staples, G.W. WGS84
## 15 Starr, F. Martz, K. Staples, G.W. WGS84
## 16 Annable, C.R. Meidell, S.; Oppenheimer, H. C.R.Annable WGS84
## 17 Flynn, T. Staples, G.W. <NA>
## 18 Annable, C.R. Oppenheimer, H. C.R.Annable WGS84
## 19 Annable, C.R. Oppenheimer, H. C.R.Annable WGS84
## 20 Annable, C.R. Oppenheimer, H. Fryxell, P.A. WGS84
## class rightsHolder
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 Magnoliopsida Bernice Pauahi Bishop Museum
## 4 Pinopsida Bernice Pauahi Bishop Museum
## 5 Liliopsida Bernice Pauahi Bishop Museum
## 6 Magnoliopsida Bernice Pauahi Bishop Museum
## 7 Magnoliopsida Bernice Pauahi Bishop Museum
## 8 Liliopsida Bernice Pauahi Bishop Museum
## 9 Magnoliopsida Bernice Pauahi Bishop Museum
## 10 Magnoliopsida Bernice Pauahi Bishop Museum
## 11 Magnoliopsida Bernice Pauahi Bishop Museum
## 12 Magnoliopsida Bernice Pauahi Bishop Museum
## 13 Magnoliopsida Bernice Pauahi Bishop Museum
## 14 Magnoliopsida Bernice Pauahi Bishop Museum
## 15 Magnoliopsida Bernice Pauahi Bishop Museum
## 16 Liliopsida Bernice Pauahi Bishop Museum
## 17 Magnoliopsida Bernice Pauahi Bishop Museum
## 18 Magnoliopsida Bernice Pauahi Bishop Museum
## 19 Liliopsida Bernice Pauahi Bishop Museum
## 20 Magnoliopsida Bernice Pauahi Bishop Museum
## habitat islandGroup
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 Cultivated, planted near road. Main Hawaiian Islands
## 4 <NA> Main Hawaiian Islands
## 5 In field Main Hawaiian Islands
## 6 <NA> Main Hawaiian Islands
## 7 Planted as a hedge. Main Hawaiian Islands
## 8 Mixed mesic introduced forest. Main Hawaiian Islands
## 9 <NA> Main Hawaiian Islands
## 10 disturbed roadside Main Hawaiian Islands
## 11 <NA> Main Hawaiian Islands
## 12 Cultivated, not yet naturalized here. Main Hawaiian Islands
## 13 Roadside Main Hawaiian Islands
## 14 Growing in open shrubland on SE rift of Maui. Main Hawaiian Islands
## 15 Presumably planted. No signs of regeneration noted. Main Hawaiian Islands
## 16 Weed in pineapple field. Main Hawaiian Islands
## 17 NTBG accession 900217001 (cutting from #820697001). Main Hawaiian Islands
## 18 <NA> Main Hawaiian Islands
## 19 Disturbed area next to pineapple field. Main Hawaiian Islands
## 20 <NA> Main Hawaiian Islands
## language type recordNumber
## 1 <NA> <NA> <NA>
## 2 <NA> <NA> <NA>
## 3 en PhysicalObject Collector Number: 990107-3
## 4 en PhysicalObject Collector Number: 3880
## 5 en PhysicalObject Collector Number: 3879
## 6 en PhysicalObject Collector Number: 3875
## 7 en PhysicalObject Collector Number: 990102-1
## 8 en PhysicalObject Collector Number: 3870
## 9 en PhysicalObject Collector Number: 3872
## 10 en PhysicalObject Collector Number: 3883
## 11 en PhysicalObject Collector Number: 8393
## 12 en PhysicalObject Collector Number: 990105-3
## 13 en PhysicalObject Collector Number: 3876
## 14 en PhysicalObject Collector Number: 990107-6
## 15 en PhysicalObject Collector Number: 990107-8
## 16 en PhysicalObject Collector Number: 3878
## 17 en PhysicalObject Collector Number: 5500
## 18 en PhysicalObject Collector Number: 3874
## 19 en PhysicalObject Collector Number: 3885
## 20 en PhysicalObject Collector Number: 3873
## identifier
## 1 <NA>
## 2 <NA>
## 3 c916d4b6-2331-46a3-a2ae-4b0d30b623d5
## 4 dcac7bf1-4341-4769-ae5d-e89d9d3fe1a5
## 5 8d2d8252-17f6-4f2b-803b-287d596d16ab
## 6 e46d923c-b87c-46ea-9dff-ee6e5d65e28a
## 7 443cd5a4-bda1-46ba-bda6-cfd827dce066
## 8 bebe339b-118e-4950-bcab-027833ae69a1
## 9 6c12db4c-b883-4b7a-aaa3-f4a8ea0affcd
## 10 94f78e1c-a3fd-4171-beec-466225967978
## 11 13bf9f39-e621-4ba2-86f5-320fea3b827b
## 12 bac17f4d-8db8-479a-82fd-3c28891dc914
## 13 f826506e-8b17-4b8c-a4e3-59e6beaa0b18
## 14 9d2463d2-8d6a-4eb7-b5f0-9e8cbd41ff39
## 15 70291a82-d428-45cb-b9bb-c8516fac95d5
## 16 60cbbeaa-750d-4c6a-86e4-35daa832e6cb
## 17 5674097a-c292-4c8c-a36c-f8e155007099
## 18 5ea11d07-52c6-4070-baa2-463c028508c3
## 19 98bbcebb-3b80-489b-a4e2-e9b0a72b2bac
## 20 4a5921b6-6ef4-4e8d-9010-2b86c7faf880
## higherGeography
## 1 <NA>
## 2 <NA>
## 3 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 4 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 5 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 6 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 7 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 8 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 9 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 10 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 11 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 12 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 13 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 14 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 15 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 16 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 17 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 18 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 19 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## 20 Pacific Ocean; Northern Polynesia; USA; Main Hawaiian Islands;
## verbatimEventDate nomenclaturalCode island endDayOfYear
## 1 <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA>
## 3 07 Jan 1999 ICNafp Maui 7
## 4 13 Jan 1999 ICNafp Maui 13
## 5 13 Jan 1999 ICNafp Maui 13
## 6 12 Jan 1999 ICNafp Maui 12
## 7 02 Jan 1999 ICNafp Maui 2
## 8 09 Jan 1999 ICNafp Oahu 9
## 9 12 Jan 1999 ICNafp Maui 12
## 10 13 Jan 1999 ICNafp Maui 13
## 11 26 Jan 1999 ICNafp Kauai 26
## 12 05 Jan 1999 ICNafp Maui 5
## 13 12 Jan 1999 ICNafp Maui 12
## 14 07 Jan 1999 ICNafp Maui 7
## 15 07 Jan 1999 ICNafp Maui 7
## 16 13 Jan 1999 ICNafp Maui 13
## 17 12 Jan 1999 ICNafp Kauai 12
## 18 12 Jan 1999 ICNafp Maui 12
## 19 14 Jan 1999 ICNafp Maui 14
## 20 12 Jan 1999 ICNafp Maui 12
## verbatimCoordinateSystem
## 1 <NA>
## 2 <NA>
## 3 degrees minutes seconds
## 4 degrees minutes seconds
## 5 degrees minutes seconds
## 6 degrees minutes seconds
## 7 degrees minutes seconds
## 8 degrees minutes seconds
## 9 degrees minutes seconds
## 10 degrees minutes seconds
## 11 <NA>
## 12 degrees minutes seconds
## 13 degrees minutes seconds
## 14 degrees minutes seconds
## 15 degrees minutes seconds
## 16 degrees minutes seconds
## 17 <NA>
## 18 degrees minutes seconds
## 19 degrees minutes seconds
## 20 degrees minutes seconds
## verbatimLocality
## 1 <NA>
## 2 <NA>
## 3 [Hawaiian Islands; U.S.A.; Maui; East Maui, Kula, in garden at 280 Waipoli Road, on west side of road]
## 4 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui Mountain. Maunalei Arboreum.]
## 5 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; Maui Land & Pineapple Company.]
## 6 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, West Maui Mt., Maunalei Arboretum.]
## 7 [Hawaiian Islands; U.S.A.; Maui; West Maui, Kapalua, Fleming's Beach]
## 8 [Hawaiian Islands; U.S.A.; O`ahu; Hawai`i; 4050 Tantalus Drive at Puu Ohia trailhead.]
## 9 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, West Maui Mt. Maunalei Arboretum.]
## 10 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, south of Napili Honokowai, north of Kahana Stream.]
## 11 [Hawaiian Islands; U.S.A.; Kaua`i; Hawai`i; Koloa District, NTBG in Lawai Valley, pump 6, nursery area (world collection).]
## 12 [Hawaiian Islands; U.S.A.; Maui; East Maui, Kula, at intersection of Puanani and Kekaulike Ave. (Puiehuiki)]
## 13 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; Maui, South of Honokahua Bay, 0.25 km south of RT. 30, on side road.]
## 14 [Hawaiian Islands; U.S.A.; Maui; East Maui, Polipoli State Park]
## 15 [Hawaiian Islands; U.S.A.; Maui; East Maui, Polipoli State Park campground]
## 16 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; Maui Land & Pineapple Company.]
## 17 [Hawaiian Islands; U.S.A.; Kaua`i; Hawai`i; Koloa Distr., Lawai Valley, National Tropical Botanical Garden, Medicinal Area]
## 18 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, West Maui Mt. Maunalei Arboretum.]
## 19 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, south of Napili Honokowai, north of Kahana Stream.]
## 20 [Hawaiian Islands; U.S.A.; Maui; Hawai`i; West Maui, West Maui Mt. Maunalei Arboretum.]
## occurrenceID disposition ownerInstitutionCode
## 1 <NA> <NA> <NA>
## 2 <NA> <NA> <NA>
## 3 c916d4b6-2331-46a3-a2ae-4b0d30b623d5 in collection BPBM
## 4 dcac7bf1-4341-4769-ae5d-e89d9d3fe1a5 in collection BPBM
## 5 8d2d8252-17f6-4f2b-803b-287d596d16ab in collection BPBM
## 6 e46d923c-b87c-46ea-9dff-ee6e5d65e28a in collection BPBM
## 7 443cd5a4-bda1-46ba-bda6-cfd827dce066 in collection BPBM
## 8 bebe339b-118e-4950-bcab-027833ae69a1 in collection BPBM
## 9 6c12db4c-b883-4b7a-aaa3-f4a8ea0affcd in collection BPBM
## 10 94f78e1c-a3fd-4171-beec-466225967978 in collection BPBM
## 11 13bf9f39-e621-4ba2-86f5-320fea3b827b in collection BPBM
## 12 bac17f4d-8db8-479a-82fd-3c28891dc914 in collection BPBM
## 13 f826506e-8b17-4b8c-a4e3-59e6beaa0b18 in collection BPBM
## 14 9d2463d2-8d6a-4eb7-b5f0-9e8cbd41ff39 in collection BPBM
## 15 70291a82-d428-45cb-b9bb-c8516fac95d5 in collection BPBM
## 16 60cbbeaa-750d-4c6a-86e4-35daa832e6cb in collection BPBM
## 17 5674097a-c292-4c8c-a36c-f8e155007099 in collection BPBM
## 18 5ea11d07-52c6-4070-baa2-463c028508c3 in collection BPBM
## 19 98bbcebb-3b80-489b-a4e2-e9b0a72b2bac in collection BPBM
## 20 4a5921b6-6ef4-4e8d-9010-2b86c7faf880 in collection BPBM
## startDayOfYear accessRights verbatimTaxonRank
## 1 <NA> <NA> <NA>
## 2 <NA> <NA> <NA>
## 3 7 http://www.vertnet.org/resources/norms.html Species
## 4 13 http://www.vertnet.org/resources/norms.html Genus
## 5 13 http://www.vertnet.org/resources/norms.html Species
## 6 12 http://www.vertnet.org/resources/norms.html Species
## 7 2 http://www.vertnet.org/resources/norms.html Species
## 8 9 http://www.vertnet.org/resources/norms.html Species
## 9 12 http://www.vertnet.org/resources/norms.html Species
## 10 13 http://www.vertnet.org/resources/norms.html Species
## 11 26 http://www.vertnet.org/resources/norms.html Species
## 12 5 http://www.vertnet.org/resources/norms.html Species
## 13 12 http://www.vertnet.org/resources/norms.html Species
## 14 7 http://www.vertnet.org/resources/norms.html Species
## 15 7 http://www.vertnet.org/resources/norms.html Species
## 16 13 http://www.vertnet.org/resources/norms.html Species
## 17 12 http://www.vertnet.org/resources/norms.html Nothospecies
## 18 12 http://www.vertnet.org/resources/norms.html Species
## 19 14 http://www.vertnet.org/resources/norms.html Species
## 20 12 http://www.vertnet.org/resources/norms.html Variety
## otherCatalogNumbers verbatimElevation
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 <NA> <NA>
## 4 Barcode: BISH1011056 350 m
## 5 Barcode: BISH1034592 80 m
## 6 <NA> 350 m
## 7 <NA> <NA>
## 8 Barcode: BISH1050972 500 m
## 9 <NA> 350 m
## 10 <NA> <NA>
## 11 <NA> 10 m
## 12 <NA> 3450 ft
## 13 <NA> <NA>
## 14 <NA> 6600 ft
## 15 <NA> <NA>
## 16 Barcode: BISH1046760 80 m
## 17 <NA> <NA>
## 18 <NA> 350 m
## 19 Barcode: BISH1035431 <NA>
## 20 <NA> 350 m
## occurrenceRemarks
## 1 <NA>
## 2 <NA>
## 3 <NA>
## 4 Tree to 35m; bark smooth on old trees, corky on young trees.
## 5 <NA>
## 6 tree to 4m; fruit skin green, pulp orange.
## 7 Looks like naio (false sandalwood) from afar. No reproduction noted.
## 8 Perennial grass to 1m
## 9 tree to 5 m
## 10 perennial to 1m
## 11 Perennial herb 1.2m ht, stems fleshy, lvs discolorous, silvery-sericeous above. Flowers not fragrant, calyx lobes grn, corolla tube pale violet, lobes dk violet within, with yellow stripe.
## 12 Trees turn color at different time than trees in lower elevations (this may be elevational maximum for the species).
## 13 Vine; flowers white
## 14 Very abundant; naturalized (confirms naturalized status in this park).
## 15 Large tree overhanging campground.
## 16 <NA>
## 17 Tree 6 ft tall; leaves glossy dark green above, dullpaler below; peduncle green with purplish brown overlay; pedicel pale green; calyx glossy red over pale green; corolla bright velvety red fading to wine; not setting fruit.
## 18 Tree to 20m; covers an area greater than 100 sq. meters, with many trunks and prop. roots.
## 19 <NA>
## 20 Tree to 10m; flowers white, with pink center.
## dateIdentified infraspecificEpithet
## 1 <NA> <NA>
## 2 <NA> <NA>
## 3 <NA> <NA>
## 4 <NA> <NA>
## 5 1999-01-01T00:00:00 <NA>
## 6 1999-01-01T00:00:00 <NA>
## 7 <NA> <NA>
## 8 <NA> <NA>
## 9 1999-01-01T00:00:00 <NA>
## 10 <NA> <NA>
## 11 <NA> <NA>
## 12 <NA> <NA>
## 13 <NA> <NA>
## 14 <NA> <NA>
## 15 <NA> <NA>
## 16 1999-01-01T00:00:00 <NA>
## 17 <NA> <NA>
## 18 1999-01-01T00:00:00 <NA>
## 19 1999-01-01T00:00:00 <NA>
## 20 2001-01-01T00:00:00 glabrescens
##
## $facets
## list()Before we dive too deep into web scrapping, we should check whether the website provides API. Similarly, before we dive deep into APIs, we should check whether there is already an R package that has wrapped the API for us thus makes it much easier to get data from the website.
For the case of GBIF, we have an existing R package
rgbif available. It wraps the API of GBIF and provides R
functions for users that have limited knowledge about APIs. Check the
webpage of rgbif to learn more.
Other similar R packages include rnoaa,
rtimes, etc.
For the case of Youtube API,
there is an R package called tuber.