how can I get a list of the countries used by the mapping toolbox as a cell array?

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I need to map countries in a dataset to countries on a map, but there are discrepencies in my data. mapping toolbox refers to 'USA' but my data uses 'United States' and corrupted data such as 'Unites States'. I wish to scrub my data for issues by comparing 60,000 entries against a definitive list of mappable countries. I know I can see a list of countries by typing worldmap() but how can I get this list into a cell array or table?

回答(2 个)

Stephen23
Stephen23 2023-11-22
编辑:Stephen23 2023-11-22
The regions used by WORLDMAP are (note that this is in a private directory, is subject to change, use at own risk):
F = fullfile(toolboxdir("map"),"mapdisp","private","regions.mat");
S = load(F,'worldRegions');
C = {S.worldRegions.name}
C = 1×293 cell array
Columns 1 through 12 {'World'} {'Africa'} {'Antarctica'} {'Asia'} {'Eurasia'} {'Europe'} {'North America'} {'South America'} {'North Pole'} {'South Pole'} {'Pacific'} {'Afghanistan'} Columns 13 through 22 {'Agalega Island'} {'Albania'} {'Alderney'} {'Algeria'} {'American Samoa'} {'Andorra'} {'Angola'} {'Anguilla'} {'Antigua and Barb…'} {'Antipodes Islands'} Columns 23 through 33 {'Argentina'} {'Armenia'} {'Aruba'} {'Auckland Islands'} {'Australia'} {'Austria'} {'Azerbaijan'} {'Azores'} {'Bahamas, The'} {'Bahrain'} {'Baker Island'} Columns 34 through 44 {'Bangladesh'} {'Barbados'} {'Bassas da India'} {'Belarus'} {'Belgium'} {'Belize'} {'Benin'} {'Bermuda'} {'Bhutan'} {'Bjornoya'} {'Bolivia'} Columns 45 through 54 {'Bosnia and Herze…'} {'Botswana'} {'Bounty Islands'} {'Bouvet Island'} {'Brazil'} {'British Indian O…'} {'Broughton Islands'} {'Brunei'} {'Bulgaria'} {'Burkina Faso'} Columns 55 through 64 {'Burma'} {'Burundi'} {'Cambodia'} {'Cameroon'} {'Campbell Islands'} {'Canada'} {'Canary Islands'} {'Cape Verde'} {'Cargados'} {'Cayman Islands'} Columns 65 through 74 {'Central African …'} {'Chad'} {'Chatham Islands'} {'Chile'} {'China'} {'Christmas Island'} {'Clipperton Island'} {'Cocos'} {'Colombia'} {'Comoros'} Columns 75 through 84 {'Congo, Democrati…'} {'Congo, Republic …'} {'Cook Islands'} {'Costa Rica'} {'Croatia'} {'Cuba'} {'Cyprus'} {'Czech Republic'} {'Denmark'} {'Djibouti'} Columns 85 through 94 {'Dominican Republ…'} {'East Timor'} {'Easter Island'} {'Ecuador'} {'Egypt'} {'El Salvador'} {'Equatorial Guinea'} {'Eritrea'} {'Estonia'} {'Ethiopia'} Columns 95 through 104 {'Europa Island'} {'Falkland Islands…'} {'Faroc Islands'} {'Faroe Islands'} {'Fiji'} {'Finland'} {'France'} {'French Antilles'} {'French Guyana'} {'French Polynesia'} Columns 105 through 114 {'French Southern …'} {'Gabon'} {'Galapagos Islands'} {'Gambia, The'} {'Georgia'} {'Germany'} {'Ghana'} {'Gibraltar'} {'Glorioso Islands'} {'Gough Island'} Columns 115 through 125 {'Greece'} {'Greenland'} {'Grenada'} {'Guadeloupe'} {'Guam'} {'Guatemala'} {'Guernsey'} {'Guinea, Republic…'} {'Guinea-Bissau'} {'Guyana'} {'Haiti'} Columns 126 through 136 {'Heard Island and…'} {'Honduras'} {'Howland Island'} {'Hungary'} {'Iceland'} {'India'} {'Indonesia'} {'Iran'} {'Iraq'} {'Ireland'} {'Isla Sala y Gomez'} Columns 137 through 146 {'Isla San Ambrosio'} {'Isla San Felix'} {'Isla de Annobon'} {'Isla del Coco'} {'Israel'} {'Italy'} {'Ivory Coast'} {'Jamaica'} {'Jan Mayen'} {'Japan'} Columns 147 through 156 {'Jarvis Island'} {'Jersey'} {'Johnson Atoll'} {'Jordan'} {'Juan de Nova Isl…'} {'Kazakhstan'} {'Kenya'} {'Kermadec Islands'} {'Kiribati'} {'Korea, Democrati…'} Columns 157 through 168 {'Korea, Republic …'} {'Kuwait'} {'Kyrgyzstan'} {'Laos'} {'Latvia'} {'Lebanon'} {'Lesotho'} {'Liberia'} {'Libya'} {'Liechtenstein'} {'Lithuania'} {'Luxembourg'} Columns 169 through 178 {'Macedonia, The F…'} {'Macquarie Island'} {'Madagascar'} {'Madeira Islands'} {'Malawi'} {'Malaysia'} {'Maldives'} {'Mali'} {'Malta'} {'Man, Isle of'} Columns 179 through 189 {'Marshall Islands'} {'Martinique'} {'Mauritania'} {'Mauritius'} {'Mayotte'} {'Mexico'} {'Micronesia, Fede…'} {'Midway Islands'} {'Moldova'} {'Monaco'} {'Mongolia'} Columns 190 through 199 {'Montenegro'} {'Montserrat'} {'Morocco'} {'Mozambique'} {'Namibia'} {'Nauru'} {'Navassa Island'} {'Nepal'} {'Netherlands Anti…'} {'Netherlands, Kin…'} Columns 200 through 210 {'New Caledonia'} {'New Zealand'} {'Nicaragua'} {'Niger, Republic …'} {'Nigeria'} {'Niue'} {'Norfolk Island'} {'Northern Mariana…'} {'Norway'} {'Oman'} {'Pakistan'} Columns 211 through 220 {'Palau, Republic …'} {'Palmyra Atoll'} {'Panama'} {'Papua New Guinea'} {'Paracel Islands'} {'Paraguay'} {'Peru'} {'Philippines'} {'Pitcairn Islands'} {'Poland'} Columns 221 through 231 {'Portugal'} {'Pratas Island'} {'Prince Edward Is…'} {'Puerto Rico'} {'Qatar'} {'Reunion'} {'Rodrigues'} {'Romania'} {'Russia'} {'Rwanda'} {'Saint Helena'} Columns 232 through 240 {'Saint Kitts and …'} {'Saint Lucia'} {'Saint Pierre and…'} {'Saint Vincent an…'} {'San Marino'} {'Sao Tome and Pri…'} {'Saudi Arabia'} {'Senegal'} {'Serbia'} Columns 241 through 250 {'Seychelles'} {'Sierra Leone'} {'Singapore'} {'Slovakia'} {'Slovenia'} {'Solomon Islands'} {'Somalia'} {'Sombrero'} {'South Africa'} {'South Georgia an…'} Columns 251 through 262 {'Spain'} {'Spratly Islands'} {'Sri Lanka'} {'Sudan'} {'Suriname'} {'Svalbard'} {'Swaziland'} {'Sweden'} {'Switzerland'} {'Syria'} {'Tajikistan'} {'Tanzania'} Columns 263 through 272 {'Tasmania'} {'Thailand'} {'Togo'} {'Tonga'} {'Trinidad and Tob…'} {'Tristan da Cunha…'} {'Tromelin Island'} {'Tunisia'} {'Turkey'} {'Turkmenistan'} Columns 273 through 282 {'Turks and Caicas…'} {'Tuvalu'} {'Uganda'} {'Ukraine'} {'United Arab Emir…'} {'United Kingdom'} {'United States of…'} {'Uruguay'} {'Uzbekistan'} {'Vanuatu'} Columns 283 through 292 {'Venezuela'} {'Vietnam'} {'Virgin Islands, …'} {'Virgin Islands, …'} {'Wake Island'} {'Wallis and Futuna'} {'Western Sahara'} {'Western Samoa'} {'Yemen'} {'Zambia'} Column 293 {'Zimbabwe'}
You might find these functions useful:

Peter Perkins
Peter Perkins 2023-11-27
Stephen seems to have answered your question, but also, you will find categorical useful for cleaning your data:
countryList = ["France" "United States"];
data = ["France" "Franz" "USA" "Unites States" "Junk"];
data = categorical(data)
data = 1×5 categorical array
France Franz USA Unites States Junk
setdiff(categories(data),countryList)
ans = 4×1 string array
"Franz" "Junk" "USA" "Unites States"
data = mergecats(data,["France" "Franz"]);
data = mergecats(data,["USA" "Unites States"],"United States")
data = 1×5 categorical array
France France United States United States Junk
data = removecats(data,"Junk")
data = 1×5 categorical array
France France United States United States <undefined>
data = rmmissing(data)
data = 1×4 categorical array
France France United States United States

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