18  Human geography lab: Annex 3

18.1 European regions with naturalearth data

library(tidyverse)
library(sf)
library(knitr)
map_data <- st_read("data/shapefile/ne_10m_admin_0_countries")
  • The map_data uses data.frames for its features and saves the geometric features as a list in the column geometry. We can now easily explore the data in map_data, e.g.,The map_data uses data.frames for its features and saves the geometric features as a list in the column geometry. We can now easily explore the data in map_data, e.g.,
features_map_data <- map_data %>%
    as_tibble() %>%
    select(-geometry) %>%
    head(10)

kable(features_map_data)
featurecla scalerank LABELRANK SOVEREIGNT SOV_A3 ADM0_DIF LEVEL TYPE TLC ADMIN ADM0_A3 GEOU_DIF GEOUNIT GU_A3 SU_DIF SUBUNIT SU_A3 BRK_DIFF NAME NAME_LONG BRK_A3 BRK_NAME BRK_GROUP ABBREV POSTAL FORMAL_EN FORMAL_FR NAME_CIAWF NOTE_ADM0 NOTE_BRK NAME_SORT NAME_ALT MAPCOLOR7 MAPCOLOR8 MAPCOLOR9 MAPCOLOR13 POP_EST POP_RANK POP_YEAR GDP_MD GDP_YEAR ECONOMY INCOME_GRP FIPS_10 ISO_A2 ISO_A2_EH ISO_A3 ISO_A3_EH ISO_N3 ISO_N3_EH UN_A3 WB_A2 WB_A3 WOE_ID WOE_ID_EH WOE_NOTE ADM0_ISO ADM0_DIFF ADM0_TLC ADM0_A3_US ADM0_A3_FR ADM0_A3_RU ADM0_A3_ES ADM0_A3_CN ADM0_A3_TW ADM0_A3_IN ADM0_A3_NP ADM0_A3_PK ADM0_A3_DE ADM0_A3_GB ADM0_A3_BR ADM0_A3_IL ADM0_A3_PS ADM0_A3_SA ADM0_A3_EG ADM0_A3_MA ADM0_A3_PT ADM0_A3_AR ADM0_A3_JP ADM0_A3_KO ADM0_A3_VN ADM0_A3_TR ADM0_A3_ID ADM0_A3_PL ADM0_A3_GR ADM0_A3_IT ADM0_A3_NL ADM0_A3_SE ADM0_A3_BD ADM0_A3_UA ADM0_A3_UN ADM0_A3_WB CONTINENT REGION_UN SUBREGION REGION_WB NAME_LEN LONG_LEN ABBREV_LEN TINY HOMEPART MIN_ZOOM MIN_LABEL MAX_LABEL LABEL_X LABEL_Y NE_ID WIKIDATAID NAME_AR NAME_BN NAME_DE NAME_EN NAME_ES NAME_FA NAME_FR NAME_EL NAME_HE NAME_HI NAME_HU NAME_ID NAME_IT NAME_JA NAME_KO NAME_NL NAME_PL NAME_PT NAME_RU NAME_SV NAME_TR NAME_UK NAME_UR NAME_VI NAME_ZH NAME_ZHT FCLASS_ISO TLC_DIFF FCLASS_TLC FCLASS_US FCLASS_FR FCLASS_RU FCLASS_ES FCLASS_CN FCLASS_TW FCLASS_IN FCLASS_NP FCLASS_PK FCLASS_DE FCLASS_GB FCLASS_BR FCLASS_IL FCLASS_PS FCLASS_SA FCLASS_EG FCLASS_MA FCLASS_PT FCLASS_AR FCLASS_JP FCLASS_KO FCLASS_VN FCLASS_TR FCLASS_ID FCLASS_PL FCLASS_GR FCLASS_IT FCLASS_NL FCLASS_SE FCLASS_BD FCLASS_UA
Admin-0 country 0 2 Indonesia IDN 0 2 Sovereign country 1 Indonesia IDN 0 Indonesia IDN 0 Indonesia IDN 0 Indonesia Indonesia IDN Indonesia NA Indo. INDO Republic of Indonesia NA Indonesia NA NA Indonesia NA 6 6 6 11 270625568 17 2019 1119190 2019 4. Emerging region: MIKT 4. Lower middle income ID ID ID IDN IDN 360 360 360 ID IDN 23424846 23424846 Exact WOE match as country IDN NA IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN IDN -99 -99 Asia Asia South-Eastern Asia East Asia & Pacific 9 9 5 -99 1 0 1.7 6.7 101.89295 -0.954404 1159320845 Q252 إندونيسيا ইন্দোনেশিয়া Indonesien Indonesia Indonesia اندونزی Indonésie Ινδονησία אינדונזיה इंडोनेशिया Indonézia Indonesia Indonesia インドネシア 인도네시아 Indonesië Indonezja Indonésia Индонезия Indonesien Endonezya Індонезія انڈونیشیا Indonesia 印度尼西亚 印度尼西亞 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 3 Malaysia MYS 0 2 Sovereign country 1 Malaysia MYS 0 Malaysia MYS 0 Malaysia MYS 0 Malaysia Malaysia MYS Malaysia NA Malay. MY Malaysia NA Malaysia NA NA Malaysia NA 2 4 3 6 31949777 15 2019 364681 2019 6. Developing region 3. Upper middle income MY MY MY MYS MYS 458 458 458 MY MYS 23424901 23424901 Exact WOE match as country MYS NA MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS MYS -99 -99 Asia Asia South-Eastern Asia East Asia & Pacific 8 8 6 -99 1 0 3.0 8.0 113.83708 2.528667 1159321083 Q833 ماليزيا মালয়েশিয়া Malaysia Malaysia Malasia مالزی Malaisie Μαλαισία מלזיה मलेशिया Malajzia Malaysia Malaysia マレーシア 말레이시아 Maleisië Malezja Malásia Малайзия Malaysia Malezya Малайзія ملائیشیا Malaysia 马来西亚 馬來西亞 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 2 Chile CHL 0 2 Sovereign country 1 Chile CHL 0 Chile CHL 0 Chile CHL 0 Chile Chile CHL Chile NA Chile CL Republic of Chile NA Chile NA NA Chile NA 5 1 5 9 18952038 14 2019 282318 2019 5. Emerging region: G20 3. Upper middle income CI CL CL CHL CHL 152 152 152 CL CHL 23424782 23424782 Exact WOE match as country CHL NA CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL CHL -99 -99 South America Americas South America Latin America & Caribbean 5 5 5 -99 1 0 1.7 6.7 -72.31887 -38.151771 1159320493 Q298 تشيلي চিলি Chile Chile Chile شیلی Chili Χιλή צ’ילה चिली Chile Chili Cile チリ 칠레 Chili Chile Chile Чили Chile Şili Чилі چلی Chile 智利 智利 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 3 Bolivia BOL 0 2 Sovereign country 1 Bolivia BOL 0 Bolivia BOL 0 Bolivia BOL 0 Bolivia Bolivia BOL Bolivia NA Bolivia BO Plurinational State of Bolivia NA Bolivia NA NA Bolivia NA 1 5 2 3 11513100 14 2019 40895 2019 5. Emerging region: G20 4. Lower middle income BL BO BO BOL BOL 068 068 068 BO BOL 23424762 23424762 Exact WOE match as country BOL NA BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL BOL -99 -99 South America Americas South America Latin America & Caribbean 7 7 7 -99 1 0 3.0 7.5 -64.59343 -16.666015 1159320439 Q750 بوليفيا বলিভিয়া Bolivien Bolivia Bolivia بولیوی Bolivie Βολιβία בוליביה बोलिविया Bolívia Bolivia Bolivia ボリビア 볼리비아 Bolivia Boliwia Bolívia Боливия Bolivia Bolivya Болівія بولیویا Bolivia 玻利维亚 玻利維亞 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 2 Peru PER 0 2 Sovereign country 1 Peru PER 0 Peru PER 0 Peru PER 0 Peru Peru PER Peru NA Peru PE Republic of Peru NA Peru NA NA Peru NA 4 4 4 11 32510453 15 2019 226848 2019 5. Emerging region: G20 3. Upper middle income PE PE PE PER PER 604 604 604 PE PER 23424919 23424919 Exact WOE match as country PER NA PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER PER -99 -99 South America Americas South America Latin America & Caribbean 4 4 4 -99 1 0 2.0 7.0 -72.90016 -12.976679 1159321163 Q419 بيرو পেরু Peru Peru Perú پرو Pérou Περού פרו पेरू Peru Peru Perù ペルー 페루 Peru Peru Peru Перу Peru Peru Перу پیرو Peru 秘鲁 秘魯 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 2 Argentina ARG 0 2 Sovereign country 1 Argentina ARG 0 Argentina ARG 0 Argentina ARG 0 Argentina Argentina ARG Argentina NA Arg. AR Argentine Republic NA Argentina NA NA Argentina NA 3 1 3 13 44938712 15 2019 445445 2019 5. Emerging region: G20 3. Upper middle income AR AR AR ARG ARG 032 032 032 AR ARG 23424747 23424747 Exact WOE match as country ARG NA ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG ARG -99 -99 South America Americas South America Latin America & Caribbean 9 9 4 -99 1 0 2.0 7.0 -64.17333 -33.501159 1159320331 Q414 الأرجنتين আর্জেন্টিনা Argentinien Argentina Argentina آرژانتین Argentine Αργεντινή ארגנטינה अर्जेण्टीना Argentína Argentina Argentina アルゼンチン 아르헨티나 Argentinië Argentyna Argentina Аргентина Argentina Arjantin Аргентина ارجنٹائن Argentina 阿根廷 阿根廷 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 3 3 United Kingdom GB1 1 2 Dependency 1 Dhekelia Sovereign Base Area ESB 0 Dhekelia Sovereign Base Area ESB 0 Dhekelia Sovereign Base Area ESB 0 Dhekelia Dhekelia ESB Dhekelia NA Dhek. DH NA NA NA U.K. U.K. Base Dhekelia Sovereign Base Area NA 6 6 6 3 7850 5 2013 314 2013 2. Developed region: nonG7 2. High income: nonOECD -99 -99 -99 -99 -99 -99 -99 -099 -99 -99 -99 -99 No WOE equivalent. -99 1 ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB ESB -99 -99 Asia Asia Western Asia Europe & Central Asia 8 8 5 3 -99 0 6.5 11.0 33.79058 35.011042 1159320709 Q9206745 ديكيليا كانتونمنت দেখেলিয়া ক্যান্টনমেন্ট Dekelia Dhekelia Cantonment Dekelia دکلیا Dhekelia Ντεκέλια Κάντονμεντ דקליה ढेकेलिया छावनी Dekélia Dhekelia Cantonment Base di Dhekelia デケリア 데켈리아 지역 Dhekelia Cantonment Dhekelia Deceleia Декелия Dhekelia Dhekelia Kantonu Муніципалітет Декелія دحیکیلیا کانتونمینٹ Căn cứ quân sự Dhekelia 泽凯利亚军营 德凱利亞軍營 Unrecognized 1 Admin-0 dependency Admin-0 dependency Admin-0 dependency NA Admin-0 dependency NA NA NA NA NA Admin-0 dependency Admin-0 dependency NA NA NA NA NA NA Admin-0 dependency NA NA Admin-0 dependency NA Admin-0 dependency NA Admin-0 dependency Admin-0 dependency Admin-0 dependency Admin-0 dependency Admin-0 dependency NA Admin-0 dependency
Admin-0 country 1 5 Cyprus CYP 0 2 Sovereign country 1 Cyprus CYP 0 Cyprus CYP 0 Cyprus CYP 0 Cyprus Cyprus CYP Cyprus NA Cyp. CY Republic of Cyprus NA Cyprus NA NA Cyprus NA 1 2 3 7 1198575 12 2019 24948 2019 6. Developing region 2. High income: nonOECD CY CY CY CYP CYP 196 196 196 CY CYP -90 23424994 WOE lists as subunit of united Cyprus CYP NA CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP CYP -99 -99 Asia Asia Western Asia Europe & Central Asia 6 6 4 -99 1 0 4.5 9.5 33.08418 34.913329 1159320533 Q229 قبرص সাইপ্রাস Republik Zypern Cyprus Chipre قبرس Chypre Κύπρος קפריסין साइप्रस Ciprus Siprus Cipro キプロス 키프로스 Cyprus Cypr Chipre Кипр Cypern Kıbrıs Cumhuriyeti Кіпр قبرص Cộng hòa Síp 塞浦路斯 賽普勒斯 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 2 India IND 0 2 Sovereign country 1 India IND 0 India IND 0 India IND 0 India India IND India NA India IND Republic of India NA India NA NA India NA 1 3 2 2 1366417754 18 2019 2868929 2019 3. Emerging region: BRIC 4. Lower middle income IN IN IN IND IND 356 356 356 IN IND 23424848 23424848 Exact WOE match as country IND NA IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND IND -99 -99 Asia Asia Southern Asia South Asia 5 5 5 -99 1 0 1.7 6.7 79.35810 22.686852 1159320847 Q668 الهند ভারত Indien India India هند Inde Ινδία הודו भारत India India India インド 인도 India Indie Índia Индия Indien Hindistan Індія بھارت Ấn Độ 印度 印度 Admin-0 country NA Admin-0 country NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
Admin-0 country 0 2 China CH1 1 2 Country 1 China CHN 0 China CHN 0 China CHN 0 China China CHN China NA China CN People’s Republic of China NA China NA NA China NA 4 4 4 3 1397715000 18 2019 14342903 2019 3. Emerging region: BRIC 3. Upper middle income CH CN CN CHN CHN 156 156 156 CN CHN 23424781 23424781 Exact WOE match as country CHN NA CHN CHN CHN CHN CHN CHN TWN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN CHN -99 -99 Asia Asia Eastern Asia East Asia & Pacific 5 5 5 -99 1 0 1.7 5.7 106.33729 32.498178 1159320471 Q148 الصين গণচীন Volksrepublik China People’s Republic of China China جمهوری خلق چین République populaire de Chine Λαϊκή Δημοκρατία της Κίνας הרפובליקה העממית של סין चीनी जनवादी गणराज्य Kína Republik Rakyat Tiongkok Cina 中華人民共和国 중화인민공화국 Volksrepubliek China Chińska Republika Ludowa China Китайская Народная Республика Kina Çin Halk Cumhuriyeti Китайська Народна Республіка عوامی جمہوریہ چین Trung Quốc 中华人民共和国 中華人民共和國 Admin-0 country NA Admin-0 country NA NA NA NA NA Unrecognized NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
  • For this tutorial we want to focus on a European countries, hence we need to filter the data to only contain the European countries’ info. Fortunately, the map_data contains a feature CONTINTENT, so we can easily filter out the unwanted countries.
europe_map_data <- map_data %>%
    select(NAME, CONTINENT, SUBREGION, POP_EST) %>%
    filter(CONTINENT == "Europe")
  • Lets try to plot a map of European countries. New versions of ggplot2 contain a function geom_sf which supports plotting sf objects directly, so lets try it…
ggplot(europe_map_data) + geom_sf() +
    theme_minimal()

  • That does not seem to work… the reason is that, even though we removed the data of non European countries, we never changed the bbox setting of our data. The bbox object sets the longitude and latitude range for our plot, which is still for the whole Europe. To change this we can use the st_crop function as
europe_map_data <- europe_map_data %>%
    st_crop(xmin=-25, xmax=55, ymin=35, ymax=71)
ggplot(europe_map_data) + geom_sf() +
    theme_minimal()

  • If you’re familiar with the ggplot2 workflow, it is now easy to construct the aesthetic mappings like you’re used to. Our map_data contains a feature SUBREGION and Europe is divided into Northern, Eastern, Southern and Western Europe. We can easily visualize this in our European map as
ggplot(europe_map_data) + geom_sf(aes(fill=SUBREGION)) +
    theme_minimal()