#install.packages(c("cowplot", "googleway","ggplot2", "ggrepel", "ggspatial", "libwgeom", "sf", "rnaturalearth","rnaturalearthdata"))
パッケージの読み込み
library("ggplot2")
theme_set(theme_bw())
library("sf")
library("rnaturalearth")
library("rnaturalearthdata")
世界地図の表示（rnaturalearth）
world <- ne_countries(scale = "medium", returnclass = "sf")
class(world)
## [1] "sf" "data.frame"
world<-world[,c(18,45)]
ggplot(data = world) +
geom_sf()
ユニクロの国別工場数のデータの読み込み
library(readxl)
FR <- read_excel("FR.xlsx")
head(FR)
## # A tibble: 6 × 5
## country factory countryjp ison countrycode
## <chr> <dbl> <chr> <dbl> <chr>
## 1 Bangladesh 20 バングラデシュ 50 BGD
## 2 Bulgaria 2 ブルガリア 100 BGR
## 3 Cambodia 10 カンボジア 116 KHM
## 4 China 144 中国 156 CHN
## 5 India 9 インド 356 IND
## 6 Indonesia 14 インドネシア 360 IDN
工場数のデータとrnaturalearthのデータの接合（left_join）
library(dplyr)
FR$iso_a3 <- FR$countrycode
world_merged <- left_join(world, FR, by = "iso_a3")
head(world_merged)
## Simple feature collection with 6 features and 7 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
## name iso_a3 country factory countryjp ison countrycode
## 1 Aruba ABW <NA> NA <NA> NA <NA>
## 2 Afghanistan AFG <NA> NA <NA> NA <NA>
## 3 Angola AGO <NA> NA <NA> NA <NA>
## 4 Anguilla AIA <NA> NA <NA> NA <NA>
## 5 Albania ALB <NA> NA <NA> NA <NA>
## 6 Aland ALA <NA> NA <NA> NA <NA>
## geometry
## 1 MULTIPOLYGON (((-69.89912 1...
## 2 MULTIPOLYGON (((74.89131 37...
## 3 MULTIPOLYGON (((14.19082 -5...
## 4 MULTIPOLYGON (((-63.00122 1...
## 5 MULTIPOLYGON (((20.06396 42...
## 6 MULTIPOLYGON (((20.61133 60...
各国の重心の緯度経度の取得（rworldmap）
library(rworldmap)
library(rworldxtra)
#方法1
# get world map
wmap <- getMap(resolution="high")
# wmapをデータに変換すると重心の緯度経度ある
wmap_data <- as.data.frame(wmap)
wmap_data<-wmap_data[,c(19,32,33,34)]
head(wmap_data)
## NAME ISO3 LON LAT
## 1 Aruba ABW -69.97345 12.51678
## 2 Afghanistan AFG 66.00845 33.83627
## 3 Angola AGO 17.56405 -12.32934
## 4 Anguilla AIA -63.05667 18.22432
## 5 Albania ALB 20.05399 41.14258
## 6 Aland ALA 19.94429 60.22851
各国の重心の緯度経度を接合（left_join）
library(dplyr)
world_merged$ISO3<-world_merged$iso_a3
world_merged <- left_join(world_merged,wmap_data,by="ISO3")
head(world_merged)
## Simple feature collection with 6 features and 11 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
## name iso_a3 country factory countryjp ison countrycode ISO3
## 1 Aruba ABW <NA> NA <NA> NA <NA> ABW
## 2 Afghanistan AFG <NA> NA <NA> NA <NA> AFG
## 3 Angola AGO <NA> NA <NA> NA <NA> AGO
## 4 Anguilla AIA <NA> NA <NA> NA <NA> AIA
## 5 Albania ALB <NA> NA <NA> NA <NA> ALB
## 6 Aland ALA <NA> NA <NA> NA <NA> ALA
## NAME LON LAT geometry
## 1 Aruba -69.97345 12.51678 MULTIPOLYGON (((-69.89912 1...
## 2 Afghanistan 66.00845 33.83627 MULTIPOLYGON (((74.89131 37...
## 3 Angola 17.56405 -12.32934 MULTIPOLYGON (((14.19082 -5...
## 4 Anguilla -63.05667 18.22432 MULTIPOLYGON (((-63.00122 1...
## 5 Albania 20.05399 41.14258 MULTIPOLYGON (((20.06396 42...
## 6 Aland 19.94429 60.22851 MULTIPOLYGON (((20.61133 60...
#工場がある国に絞る
library(tidyr)
world_merged_label<-drop_na(world_merged,factory)
#工場がない国は工場の数をゼロにする
world_merged$factory[is.na(world_merged$factory)] <- 0
地図描画
国名ラベルあり
ggp1 <-ggplot(data = world_merged_label) +
geom_sf(aes(fill = factory)) +
scale_fill_distiller(name="縫製工場数", palette = "Reds", direction=1)+
geom_sf(data = world_merged, fill = NA)+
labs(title="",caption="") +
geom_text(data = world_merged_label, label=paste0(world_merged_label$countryjp, " ", as.character(format(world_merged_label$factory, big.mark=","))), aes(x=LON, y=LAT), hjust=0, vjust=0, fontface='bold', size=2, check_overlap = TRUE) +
coord_sf(xlim = c(-90, 150), ylim = c(60, -30), expand = TRUE)+
theme(axis.text = element_blank(), axis.title = element_blank())
ggp1
ggsave("fig3_5_map_uniqlo.jpg", width = 8, height = 4, dpi = "print")
地図描画
国名ラベルなし
ggp1 <-ggplot(data = world_merged_label) +
geom_sf(aes(fill = factory)) +
scale_fill_distiller(name="縫製工場数", palette = "Reds", direction=1)+
geom_sf(data = world_merged, fill = NA)+
labs(title="",caption="") +
coord_sf(xlim = c(-90, 150), ylim = c(60, -30), expand = TRUE)+
theme(axis.text = element_blank(), axis.title = element_blank())
ggp1
ggsave("fig3_5_map_uniqlo2.jpg", width = 8, height = 4, dpi = "print")
地図描画
国名ラベルあり
ggp1 <-ggplot(data = world_merged_label) +
geom_sf(aes(fill = factory)) +
scale_fill_distiller(name="縫製工場数", palette = "Reds", direction=1)+
geom_sf(data = world_merged, fill = NA)+
labs(title="",caption="") +
coord_sf(xlim = c(-90, 150), ylim = c(60, -30), expand = TRUE)+
theme(axis.text = element_blank(), axis.title = element_blank())+
geom_sf_label(aes(label =paste0(world_merged_label$countryjp, " ", as.character(format(world_merged_label$factory, big.mark=",")))),size=2)
ggp1
ggsave("fig3_5_map_uniqlo3.jpg", width = 8, height = 4, dpi = "print")
地図描画
国名ラベルあり
参考
ggp1 <-ggplot(data = world_merged_label) +
geom_sf(aes(fill = factory)) +
scale_fill_distiller(name="縫製工場数", palette = "Reds", direction=1)+
geom_sf(data = world_merged, fill = NA)+
coord_sf(xlim = c(-90, 150), ylim = c(60, -30), expand = TRUE)+
theme(axis.text = element_blank(), axis.title = element_blank())+
ggrepel::geom_label_repel(
aes(label = paste0(world_merged_label$countryjp, " ", as.character(format(world_merged_label$factory))), geometry = geometry),
stat = "sf_coordinates",
segment.size = 0.2,
#min.segment.length = 5,
#label.size = 1, # with this we
color = "black"
)
ggp1
ggsave("fig3_5_map_uniqlo4.jpg", width = 16, height = 10, dpi = "print")