World map

Download the data files from Natural Earth
Plot the map

world <- ne_countries(scale = "medium", returnclass = "sf")
class(world)

## [1] "sf"         "data.frame"

str(world)

## Classes 'sf' and 'data.frame':   241 obs. of  64 variables:
##  $ scalerank : int  3 1 1 1 1 3 3 1 1 1 ...
##  $ featurecla: chr  "Admin-0 country" "Admin-0 country" "Admin-0 country" "Admin-0 country" ...
##  $ labelrank : num  5 3 3 6 6 6 6 4 2 6 ...
##  $ sovereignt: chr  "Netherlands" "Afghanistan" "Angola" "United Kingdom" ...
##  $ sov_a3    : chr  "NL1" "AFG" "AGO" "GB1" ...
##  $ adm0_dif  : num  1 0 0 1 0 1 0 0 0 0 ...
##  $ level     : num  2 2 2 2 2 2 2 2 2 2 ...
##  $ type      : chr  "Country" "Sovereign country" "Sovereign country" "Dependency" ...
##  $ admin     : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ adm0_a3   : chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ geou_dif  : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ geounit   : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ gu_a3     : chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ su_dif    : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ subunit   : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ su_a3     : chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ brk_diff  : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ name      : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ name_long : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ brk_a3    : chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ brk_name  : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ brk_group : chr  NA NA NA NA ...
##  $ abbrev    : chr  "Aruba" "Afg." "Ang." "Ang." ...
##  $ postal    : chr  "AW" "AF" "AO" "AI" ...
##  $ formal_en : chr  "Aruba" "Islamic State of Afghanistan" "People's Republic of Angola" NA ...
##  $ formal_fr : chr  NA NA NA NA ...
##  $ note_adm0 : chr  "Neth." NA NA "U.K." ...
##  $ note_brk  : chr  NA NA NA NA ...
##  $ name_sort : chr  "Aruba" "Afghanistan" "Angola" "Anguilla" ...
##  $ name_alt  : chr  NA NA NA NA ...
##  $ mapcolor7 : num  4 5 3 6 1 4 1 2 3 3 ...
##  $ mapcolor8 : num  2 6 2 6 4 1 4 1 1 1 ...
##  $ mapcolor9 : num  2 8 6 6 1 4 1 3 3 2 ...
##  $ mapcolor13: num  9 7 1 3 6 6 8 3 13 10 ...
##  $ pop_est   : num  103065 28400000 12799293 14436 3639453 ...
##  $ gdp_md_est: num  2258 22270 110300 109 21810 ...
##  $ pop_year  : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ lastcensus: num  2010 1979 1970 NA 2001 ...
##  $ gdp_year  : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ economy   : chr  "6. Developing region" "7. Least developed region" "7. Least developed region" "6. Developing region" ...
##  $ income_grp: chr  "2. High income: nonOECD" "5. Low income" "3. Upper middle income" "3. Upper middle income" ...
##  $ wikipedia : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ fips_10   : chr  NA NA NA NA ...
##  $ iso_a2    : chr  "AW" "AF" "AO" "AI" ...
##  $ iso_a3    : chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ iso_n3    : chr  "533" "004" "024" "660" ...
##  $ un_a3     : chr  "533" "004" "024" "660" ...
##  $ wb_a2     : chr  "AW" "AF" "AO" NA ...
##  $ wb_a3     : chr  "ABW" "AFG" "AGO" NA ...
##  $ woe_id    : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ adm0_a3_is: chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ adm0_a3_us: chr  "ABW" "AFG" "AGO" "AIA" ...
##  $ adm0_a3_un: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ adm0_a3_wb: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ continent : chr  "North America" "Asia" "Africa" "North America" ...
##  $ region_un : chr  "Americas" "Asia" "Africa" "Americas" ...
##  $ subregion : chr  "Caribbean" "Southern Asia" "Middle Africa" "Caribbean" ...
##  $ region_wb : chr  "Latin America & Caribbean" "South Asia" "Sub-Saharan Africa" "Latin America & Caribbean" ...
##  $ name_len  : num  5 11 6 8 7 5 7 20 9 7 ...
##  $ long_len  : num  5 11 6 8 7 13 7 20 9 7 ...
##  $ abbrev_len: num  5 4 4 4 4 5 4 6 4 4 ...
##  $ tiny      : num  4 NA NA NA NA 5 5 NA NA NA ...
##  $ homepart  : num  NA 1 1 NA 1 NA 1 1 1 1 ...
##  $ geometry  :sfc_MULTIPOLYGON of length 241; first list element: List of 1
##   ..$ :List of 1
##   .. ..$ : num [1:10, 1:2] -69.9 -69.9 -69.9 -70 -70.1 ...
##   ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
##   ..- attr(*, "names")= chr [1:63] "scalerank" "featurecla" "labelrank" "sovereignt" ...

head(world)

## Simple feature collection with 6 features and 63 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: -70.06611 ymin: -18.01973 xmax: 74.89131 ymax: 60.40581
## Geodetic CRS:  +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0
##   scalerank      featurecla labelrank     sovereignt sov_a3 adm0_dif level
## 0         3 Admin-0 country         5    Netherlands    NL1        1     2
## 1         1 Admin-0 country         3    Afghanistan    AFG        0     2
## 2         1 Admin-0 country         3         Angola    AGO        0     2
## 3         1 Admin-0 country         6 United Kingdom    GB1        1     2
## 4         1 Admin-0 country         6        Albania    ALB        0     2
## 5         3 Admin-0 country         6        Finland    FI1        1     2
##                type       admin adm0_a3 geou_dif     geounit gu_a3 su_dif
## 0           Country       Aruba     ABW        0       Aruba   ABW      0
## 1 Sovereign country Afghanistan     AFG        0 Afghanistan   AFG      0
## 2 Sovereign country      Angola     AGO        0      Angola   AGO      0
## 3        Dependency    Anguilla     AIA        0    Anguilla   AIA      0
## 4 Sovereign country     Albania     ALB        0     Albania   ALB      0
## 5           Country       Aland     ALD        0       Aland   ALD      0
##       subunit su_a3 brk_diff        name     name_long brk_a3    brk_name
## 0       Aruba   ABW        0       Aruba         Aruba    ABW       Aruba
## 1 Afghanistan   AFG        0 Afghanistan   Afghanistan    AFG Afghanistan
## 2      Angola   AGO        0      Angola        Angola    AGO      Angola
## 3    Anguilla   AIA        0    Anguilla      Anguilla    AIA    Anguilla
## 4     Albania   ALB        0     Albania       Albania    ALB     Albania
## 5       Aland   ALD        0       Aland Aland Islands    ALD       Aland
##   brk_group abbrev postal                    formal_en formal_fr note_adm0
## 0      <NA>  Aruba     AW                        Aruba      <NA>     Neth.
## 1      <NA>   Afg.     AF Islamic State of Afghanistan      <NA>      <NA>
## 2      <NA>   Ang.     AO  People's Republic of Angola      <NA>      <NA>
## 3      <NA>   Ang.     AI                         <NA>      <NA>      U.K.
## 4      <NA>   Alb.     AL          Republic of Albania      <NA>      <NA>
## 5      <NA>  Aland     AI                Åland Islands      <NA>      Fin.
##   note_brk   name_sort name_alt mapcolor7 mapcolor8 mapcolor9 mapcolor13
## 0     <NA>       Aruba     <NA>         4         2         2          9
## 1     <NA> Afghanistan     <NA>         5         6         8          7
## 2     <NA>      Angola     <NA>         3         2         6          1
## 3     <NA>    Anguilla     <NA>         6         6         6          3
## 4     <NA>     Albania     <NA>         1         4         1          6
## 5     <NA>       Aland     <NA>         4         1         4          6
##    pop_est gdp_md_est pop_year lastcensus gdp_year                    economy
## 0   103065     2258.0       NA       2010       NA       6. Developing region
## 1 28400000    22270.0       NA       1979       NA  7. Least developed region
## 2 12799293   110300.0       NA       1970       NA  7. Least developed region
## 3    14436      108.9       NA         NA       NA       6. Developing region
## 4  3639453    21810.0       NA       2001       NA       6. Developing region
## 5    27153     1563.0       NA         NA       NA 2. Developed region: nonG7
##                income_grp wikipedia fips_10 iso_a2 iso_a3 iso_n3 un_a3 wb_a2
## 0 2. High income: nonOECD        NA    <NA>     AW    ABW    533   533    AW
## 1           5. Low income        NA    <NA>     AF    AFG    004   004    AF
## 2  3. Upper middle income        NA    <NA>     AO    AGO    024   024    AO
## 3  3. Upper middle income        NA    <NA>     AI    AIA    660   660  <NA>
## 4  4. Lower middle income        NA    <NA>     AL    ALB    008   008    AL
## 5    1. High income: OECD        NA    <NA>     AX    ALA    248   248  <NA>
##   wb_a3 woe_id adm0_a3_is adm0_a3_us adm0_a3_un adm0_a3_wb     continent
## 0   ABW     NA        ABW        ABW         NA         NA North America
## 1   AFG     NA        AFG        AFG         NA         NA          Asia
## 2   AGO     NA        AGO        AGO         NA         NA        Africa
## 3  <NA>     NA        AIA        AIA         NA         NA North America
## 4   ALB     NA        ALB        ALB         NA         NA        Europe
## 5  <NA>     NA        ALA        ALD         NA         NA        Europe
##   region_un       subregion                 region_wb name_len long_len
## 0  Americas       Caribbean Latin America & Caribbean        5        5
## 1      Asia   Southern Asia                South Asia       11       11
## 2    Africa   Middle Africa        Sub-Saharan Africa        6        6
## 3  Americas       Caribbean Latin America & Caribbean        8        8
## 4    Europe Southern Europe     Europe & Central Asia        7        7
## 5    Europe Northern Europe     Europe & Central Asia        5       13
##   abbrev_len tiny homepart                       geometry
## 0          5    4       NA MULTIPOLYGON (((-69.89912 1...
## 1          4   NA        1 MULTIPOLYGON (((74.89131 37...
## 2          4   NA        1 MULTIPOLYGON (((14.19082 -5...
## 3          4   NA       NA MULTIPOLYGON (((-63.00122 1...
## 4          4   NA        1 MULTIPOLYGON (((20.06396 42...
## 5          5    5       NA MULTIPOLYGON (((20.61133 60...

world[world$sov_a3 == "TUR",]

## Simple feature collection with 1 feature and 63 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 25.66895 ymin: 35.83145 xmax: 44.81719 ymax: 42.09326
## Geodetic CRS:  +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0
##     scalerank      featurecla labelrank sovereignt sov_a3 adm0_dif level
## 220         1 Admin-0 country         2     Turkey    TUR        0     2
##                  type  admin adm0_a3 geou_dif geounit gu_a3 su_dif subunit
## 220 Sovereign country Turkey     TUR        0  Turkey   TUR      0  Turkey
##     su_a3 brk_diff   name name_long brk_a3 brk_name brk_group abbrev postal
## 220   TUR        0 Turkey    Turkey    TUR   Turkey      <NA>   Tur.     TR
##              formal_en formal_fr note_adm0 note_brk name_sort name_alt
## 220 Republic of Turkey      <NA>      <NA>     <NA>    Turkey     <NA>
##     mapcolor7 mapcolor8 mapcolor9 mapcolor13  pop_est gdp_md_est pop_year
## 220         6         3         8          4 76805524     902700       NA
##     lastcensus gdp_year                  economy             income_grp
## 220       2000       NA 4. Emerging region: MIKT 3. Upper middle income
##     wikipedia fips_10 iso_a2 iso_a3 iso_n3 un_a3 wb_a2 wb_a3 woe_id adm0_a3_is
## 220        NA    <NA>     TR    TUR    792   792    TR   TUR     NA        TUR
##     adm0_a3_us adm0_a3_un adm0_a3_wb continent region_un    subregion
## 220        TUR         NA         NA      Asia      Asia Western Asia
##                 region_wb name_len long_len abbrev_len tiny homepart
## 220 Europe & Central Asia        6        6          4   NA        1
##                           geometry
## 220 MULTIPOLYGON (((25.97002 40...

ggplot(data = world) + geom_sf()

ggplot(data = world) + geom_sf() + theme_bw()

ggplot(data = world) + geom_sf() + theme_void()

ggplot(data = world) + geom_sf() + theme_bw() +
  labs(title = "World map", 
  subtitle = paste0(length(unique(world$sov_a3)), " countries"), 
  x = "Longitude", y = "Latitude")

ctitles <-   labs(title = "World map", 
                  subtitle = paste0(length(unique(world$sov_a3)), " countries"), 
                  x = "Longitude", y = "Latitude")

ggplot(data = world) + 
  geom_sf() + 
  theme_bw() + ctitles

ggplot(data = world) + 
  geom_sf(color = "black", fill = "lightblue") + 
  theme_bw() + ctitles

ggplot(data = world) + 
  geom_sf(color = "black", fill = "lightblue") + 
  coord_sf(ylim = c(-65, 90), expand = FALSE) +
  theme_bw() + ctitles

ggplot(data = world) + 
  geom_sf(aes(fill = economy)) + 
  coord_sf(ylim = c(-65, 90), expand = FALSE) +
  theme_bw() + ctitles +
  scale_fill_viridis_d(option = "plasma")

ggplot(data = world) + 
  geom_sf(aes(fill = pop_est)) + 
  coord_sf(ylim = c(-65, 90), expand = FALSE) +
  theme_bw() + ctitles +
  scale_fill_viridis_c(option = "plasma", trans = "sqrt")

ggplot(data = world) + 
  geom_sf(aes(fill = pop_est)) + 
  coord_sf(ylim = c(-65, 90), expand = FALSE) +
  theme_bw() + ctitles +
  scale_fill_viridis_c(option = "plasma", trans = "sqrt", direction = -1)

ggplot(data = world) + 
  geom_sf(aes(fill = pop_est)) + 
  theme_bw() + ctitles +
  scale_fill_viridis_c(option = "plasma", trans = "sqrt", direction = -1) +
  coord_sf(crs = st_crs(3035))

Turkey map

turkey <- ne_states(country = "turkey", returnclass = "sf")

class(turkey)

## [1] "sf"         "data.frame"

str(turkey)

## Classes 'sf' and 'data.frame':   81 obs. of  122 variables:
##  $ featurecla: chr  "Admin-1 states provinces lakes" "Admin-1 states provinces lakes" "Admin-1 states provinces lakes" "Admin-1 states provinces lakes" ...
##  $ scalerank : int  6 6 6 6 6 6 6 6 6 6 ...
##  $ adm1_code : chr  "TUR-4839" "TUR-2298" "TUR-3044" "TUR-3047" ...
##  $ diss_me   : int  4839 2298 3044 3047 4840 2307 3048 2241 2240 3040 ...
##  $ iso_3166_2: chr  "TR-75" "TR-08" "TR-73" "TR-30" ...
##  $ wikipedia : chr  "http://en.wikipedia.org/wiki/Ardahan_Province" NA NA NA ...
##  $ iso_a2    : chr  "TR" "TR" "TR" "TR" ...
##  $ adm0_sr   : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ name      : chr  "Ardahan" "Artvin" "Sirnak" "Hakkari" ...
##  $ name_alt  : chr  NA "Çoruh" "Şırnak" NA ...
##  $ name_local: chr  NA NA NA NA ...
##  $ type      : chr  "Il" "Il" "Il" "Il" ...
##  $ type_en   : chr  "Province" "Province" "Province" "Province" ...
##  $ code_local: chr  NA NA NA NA ...
##  $ code_hasc : chr  "TR.AR" "TR.AV" "TR.SR" "TR.HK" ...
##  $ note      : chr  NA NA NA NA ...
##  $ hasc_maybe: chr  NA NA NA NA ...
##  $ region    : chr  NA NA NA NA ...
##  $ region_cod: chr  NA NA NA NA ...
##  $ provnum_ne: int  20021 20019 20029 20027 0 20020 20018 20005 20004 20021 ...
##  $ gadm_level: int  1 1 1 1 1 1 1 1 1 1 ...
##  $ check_me  : int  20 20 20 20 20 20 20 20 20 20 ...
##  $ datarank  : int  5 5 5 5 5 5 5 5 5 5 ...
##  $ abbrev    : chr  NA NA NA NA ...
##  $ postal    : chr  "AR" "AV" "SR" "HK" ...
##  $ area_sqkm : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ sameascity: int  7 -99 -99 7 7 7 7 7 7 7 ...
##  $ labelrank : int  7 6 6 7 7 7 7 7 7 7 ...
##  $ name_len  : int  7 6 6 7 5 4 3 10 6 4 ...
##  $ mapcolor9 : int  8 8 8 8 8 8 8 8 8 8 ...
##  $ mapcolor13: int  4 4 4 4 4 4 4 4 4 4 ...
##  $ fips      : chr  "TU86" "TU08" "TU80" "TU70" ...
##  $ fips_alt  : chr  NA NA NA NA ...
##  $ woe_id    : int  20070284 2347265 2347330 2347320 20070183 2347261 2347316 2347294 2347279 2347291 ...
##  $ woe_label : chr  "Ardahan, TR, Turkey" "Artvin, TR, Turkey" "ÅžÄ±rnak, TR, Turkey" "HakkÃ¢ri, TR, Turkey" ...
##  $ woe_name  : chr  "Ardahan" "Artvin" "Sirnak" "Hakkari" ...
##  $ latitude  : num  41.2 41 37.4 37.6 39.8 ...
##  $ longitude : num  42.8 41.8 42.5 44.1 44 ...
##  $ sov_a3    : chr  "TUR" "TUR" "TUR" "TUR" ...
##  $ adm0_a3   : chr  "TUR" "TUR" "TUR" "TUR" ...
##  $ adm0_label: int  2 2 2 2 2 2 2 2 2 2 ...
##  $ admin     : chr  "Turkey" "Turkey" "Turkey" "Turkey" ...
##  $ geonunit  : chr  "Turkey" "Turkey" "Turkey" "Turkey" ...
##  $ gu_a3     : chr  "TUR" "TUR" "TUR" "TUR" ...
##  $ gn_id     : int  862470 751816 443189 312888 443184 325163 298113 743165 747711 743942 ...
##  $ gn_name   : chr  "Ardahan" "Artvin" "Sirnak" "Hakkari" ...
##  $ gns_id    : int  9034903 -735804 9035020 -752257 9034900 -733172 -774910 -760442 -747444 -758248 ...
##  $ gns_name  : chr  "Ardahan Ili" "Artvin Ili" "Sirnak Ili" "Hakkari Ili" ...
##  $ gn_level  : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ gn_region : chr  NA NA NA NA ...
##  $ gn_a1_code: chr  "TR.86" "TR.08" "TR.80" "TR.70" ...
##  $ region_sub: chr  NA NA NA NA ...
##  $ sub_code  : chr  NA NA NA NA ...
##  $ gns_level : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ gns_lang  : chr  "tur" "tur" "tur" "tur" ...
##  $ gns_adm1  : chr  "TU86" "TU08" "TU80" "TU70" ...
##  $ gns_region: chr  NA NA NA NA ...
##  $ min_label : num  7 7 7 7 7 7 7 7 7 7 ...
##  $ max_label : num  11 11 11 11 11 11 11 11 11 11 ...
##  $ min_zoom  : num  7 7 7 7 7 7 7 7 7 7 ...
##  $ wikidataid: chr  "Q79840" "Q43745" "Q647378" "Q93209" ...
##  $ name_ar   : chr  "أرداهان" "أرتوين" "شرناق" "هكاري" ...
##  $ name_bn   : chr  "আরদাহান প্রদেশ" "আর্টভিন প্রদেশ" "সিনাক প্রদেশ" "হাক্কারি প্রদেশ" ...
##  $ name_de   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_en   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_es   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_fr   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkari" ...
##  $ name_el   : chr  "Αρνταχάν" "Επαρχία Αρτβίν" "Σίρνακ" "Χακάρι" ...
##  $ name_hi   : chr  "अर्दहन प्रांत" "आर्टविन प्रांत" "सिर्नक प्रांत" "हक्कारी प्रोविंस" ...
##  $ name_hu   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkari" ...
##  $ name_id   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_it   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_ja   : chr  "アルダハン県" "アルトヴィン県" "シュルナク県" "ハッキャリ県" ...
##  $ name_ko   : chr  "아르다한" "아르트빈" "시르나크" "하카리" ...
##  $ name_nl   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_pl   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkari" ...
##  $ name_pt   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_ru   : chr  "Ардахан" "Артвин" "Ширнак" "Хаккяри" ...
##  $ name_sv   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkari" ...
##  $ name_tr   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_vi   : chr  "Ardahan" "Artvin" "Şırnak" "Hakkâri" ...
##  $ name_zh   : chr  "阿尔达汉省" "阿尔特温省" "舍尔纳克省" "哈卡里省" ...
##  $ ne_id     : num  1.16e+09 1.16e+09 1.16e+09 1.16e+09 1.16e+09 ...
##  $ name_he   : chr  "ארדהאן" "ארטווין" "סירנאק" "האקארי" ...
##  $ name_uk   : chr  "Ардахан" "Артвін" "Ширнак" "Хаккярі" ...
##  $ name_ur   : chr  "ارداہان صوبہ" "آرتوین صوبہ" "شرناق صوبہ" "حکاری صوبہ" ...
##  $ name_fa   : chr  "استان اردهان" "استان آرتوین" "استان شرناق" "استان حکاری" ...
##  $ name_zht  : chr  "阿尔达汉省" "阿尔特温省" "舍爾納克省" "哈卡里省" ...
##  $ FCLASS_ISO: chr  NA NA NA NA ...
##  $ FCLASS_US : chr  NA NA NA NA ...
##  $ FCLASS_FR : chr  NA NA NA NA ...
##  $ FCLASS_RU : chr  NA NA NA NA ...
##  $ FCLASS_ES : chr  NA NA NA NA ...
##  $ FCLASS_CN : chr  NA NA NA NA ...
##  $ FCLASS_TW : chr  NA NA NA NA ...
##  $ FCLASS_IN : chr  NA NA NA NA ...
##  $ FCLASS_NP : chr  NA NA NA NA ...
##  $ FCLASS_PK : chr  NA NA NA NA ...
##  $ FCLASS_DE : chr  NA NA NA NA ...
##   [list output truncated]
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
##   ..- attr(*, "names")= chr [1:121] "featurecla" "scalerank" "adm1_code" "diss_me" ...

ggplot(data = turkey) + 
  geom_sf() + 
  theme_void() + 
  labs(title = "Turkey map")

ggplot(data = turkey) + 
  geom_sf() + 
  geom_sf_text(aes(latitude, longitude, label = name), size = 2) +
  theme_void() + 
  labs(title = "Turkey map")

ggplot(data = turkey) +
  geom_sf(color = "black", fill = "white") + 
  geom_sf_text(aes(latitude, longitude, label = name), size = 2) +
  theme_void() + 
  labs(title = "Turkey map")

Add data to the map

library(rvest)

pwiki <- read_html("https://en.wikipedia.org/wiki/Provinces_of_Turkey")

ptables <- html_elements(pwiki, "table")

length(ptables)

## [1] 12

pdat <- html_table(ptables, header = TRUE)[[3]]

head(pdat)

## # A tibble: 6 × 7
##      `` Name  Capital `Area (km2)` Populationcensus22.1…¹ Populationcensus2.11…²
##   <int> <chr> <chr>   <chr>        <chr>                  <chr>                 
## 1     1 Adana Adana   14,045.56    1,849,478              2,102,375             
## 2     2 Adıy… Adıyam… 7,606.16     623,811                594,163               
## 3     3 Afyo… Afyonk… 14,718.63    812,416                701,461               
## 4     4 Ağrı  Ağrı    11,498.67    528,744                553,241               
## 5     5 Amas… Amasya  5,703.78     365,231                323,331               
## 6     6 Anka… Ankara  25,401.94    4,007,860              4,868,418             
## # ℹ abbreviated names: ¹Populationcensus22.10.2000, ²Populationcensus2.11.2011
## # ℹ 1 more variable: `Population estimate31.12.2021[1]` <chr>

names(pdat) <- c("id", "name_de", "capital", "area", "pop2000", "pop2011", "pop2021")

str(pdat)

## tibble [81 × 7] (S3: tbl_df/tbl/data.frame)
##  $ id     : int [1:81] 1 2 3 4 5 6 7 8 9 10 ...
##  $ name_de: chr [1:81] "Adana" "Adıyaman" "Afyonkarahisar" "Ağrı" ...
##  $ capital: chr [1:81] "Adana" "Adıyaman" "Afyonkarahisar" "Ağrı" ...
##  $ area   : chr [1:81] "14,045.56" "7,606.16" "14,718.63" "11,498.67" ...
##  $ pop2000: chr [1:81] "1,849,478" "623,811" "812,416" "528,744" ...
##  $ pop2011: chr [1:81] "2,102,375" "594,163" "701,461" "553,241" ...
##  $ pop2021: chr [1:81] "2,263,373" "632,148" "744,179" "524,069" ...

head(pdat)

## # A tibble: 6 × 7
##      id name_de        capital        area      pop2000   pop2011   pop2021  
##   <int> <chr>          <chr>          <chr>     <chr>     <chr>     <chr>    
## 1     1 Adana          Adana          14,045.56 1,849,478 2,102,375 2,263,373
## 2     2 Adıyaman       Adıyaman       7,606.16  623,811   594,163   632,148  
## 3     3 Afyonkarahisar Afyonkarahisar 14,718.63 812,416   701,461   744,179  
## 4     4 Ağrı           Ağrı           11,498.67 528,744   553,241   524,069  
## 5     5 Amasya         Amasya         5,703.78  365,231   323,331   335,331  
## 6     6 Ankara         Ankara         25,401.94 4,007,860 4,868,418 5,747,325

# chartr("ğüşıöç", "gusioc", x)

pdat$area <- gsub(",", "", pdat$area)

pdat$pop2021 <- gsub(",", "", pdat$pop2021)

pdat$pdensity <- as.numeric(pdat$pop2021) / as.numeric(pdat$area)

turkey <- merge(turkey, pdat[, c("name_de", "pdensity")], on = "name_de")

ggplot(data = turkey) +
  geom_sf(aes(fill = pdensity)) + 
  scale_fill_viridis_c(option = "plasma", trans = "log", direction = -1) +
  theme_void() + 
  labs(title = "Population density in Turkey")

turkey$pdensity2 <-cut(turkey$pdensity, c(0, 20, 50, 100, 250, 500, 3000))

ggplot(data = turkey) +
  geom_sf(aes(fill = pdensity2)) + 
  scale_fill_viridis_d(option = "plasma", direction = -1) +
  theme_void() + 
  labs(title = "Population density in Turkey")

ggplot(data = turkey) +
  geom_sf(aes(fill = pdensity2), color = "white") + 
  geom_sf_text(aes(latitude, longitude, label = name), size = 2) +
  scale_fill_viridis_d(option = "plasma", direction = -1) +
  theme_void() + 
  labs(title = "Population density in Turkey")

leaflet maps

leaflet
leaflet.extras

For map types, see https://leaflet-extras.github.io/leaflet-providers/preview/

library(leaflet)
library(leaflet.extras)

leaflet() %>% addTiles()

leaflet() %>% addTiles() %>% 
  setView(35, 39, zoom = 5)

leaflet() %>% addTiles() %>% 
  setView(35, 39, zoom = 7)

# ESRI topographic
leaflet() %>%
  addTiles(urlTemplate = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Topo_Map/MapServer/tile/{z}/{y}/{x}") %>%
  setView(35, 39, zoom = 5)

# Esri.WorldShadedRelief
leaflet() %>%
  addTiles(urlTemplate = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Shaded_Relief/MapServer/tile/{z}/{y}/{x}") %>%
  setView(35, 39, zoom = 5)

# Two layers
leaflet(icons) %>%
  setView(35, 39, zoom = 5) %>%
  addTiles(group = "Map") %>% 
  addProviderTiles(providers$Esri.WorldImagery, group = "Satellite") %>% 
  addFullscreenControl() %>%
  addLayersControl(
    baseGroups = c("Map", "Satellite"),
    options = layersControlOptions(collapsed = FALSE)) %>% 
  hideGroup("Satellite")

# Popup icons and  html content 
c_1 <- '<iframe width="300" height="200" src="https://www.youtube.com/embed/wlgtuuyBmrw" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>'
c_2 <- "METU Economics<br/><img src='http://econ.metu.edu.tr/system/files/home/predefined/gorselmedia_c.jpg' width=300px/>"
c_3 <- "<b><a href='http://econ.metu.edu.tr/'>METU Economics</a></b><br/>Ankara/Turkey"
c_4 <- '<iframe width="300" height="200" src="https://www.youtube.com/embed/iRkekjtnycc" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>'

icons <- data.frame(lat = c(41.0, 37.0, 39.9, 40), 
                    lon = c(28.9, 33.0, 32.8, 39), 
                    labels = c("İş imkanları", "Mezuniyet", "ODTÜ İktisat", "Mezunlar"),
                    content = c(c_1, c_2, c_3, c_4))
leaflet(icons) %>%
  addTiles(urlTemplate = "https://server.arcgisonline.com/ArcGIS/rest/services/World_Shaded_Relief/MapServer/tile/{z}/{y}/{x}") %>%
  setView(35, 39, zoom = 5) %>%
  addMarkers(~lon, ~lat, popup = ~content, label = ~as.character(labels))

ECON 413
Maps

Mapping data

Load libraries

World map

Turkey map

Add data to the map

leaflet maps

ECON 413 Maps

Mapping data

Load libraries

World map

Turkey map

Add data to the map

leaflet maps

ECON 413
Maps