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.Rhistory
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w <- 0.14
if(y == 2000)
h <- 0.18
grid.raster(image = logo, x = 0.99, y = 0.99,
width = w, height = h,
hjust = 1, vjust = 1)
}
if(y %% 4 != 0)
y <- NULL
text(-1.1,1.02, paste0("FIFA World Cup Squads ", y), col="white", cex=1.4, pos=4)
text(-1.1,0.96,"Leagues to national teams", col="white", cex=0.75, pos=4)
text(-1.1,0.91,"by @guyabelguyabel", col="white", cex=0.75, pos=4)
text(-1.1,-0.72,"Details:", col="white", cex=0.7, pos=4)
yy = -0.76
text(-1.1,yy-0.03*0, "Colours based on the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*1, "shirt of each national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*2, "team. Chords represent", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*3, "connections between the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*4, "country of a player’s club (at ", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*5, "the chord base) and their national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*6, "team (at the arrow head). Chord thickness", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*7, "represents the number of players per club", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*8, "country-national team combination. Created", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*9, "in R. Data scraped from squad lists on Wikipedia:", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*10, "https://en.wikipedia.org/wiki/FIFA_World_Cup", col="white", cex=0.5, pos=4)
if(f %% 10 == 0)
message(f)
}
dev.off()
file.show("./plot/fifa.pdf")
d0$gap
d0
d0 <- n0 %>%
bind_rows(c0) %>%
mutate(label = str_wrap(string = lab, width = 12)) %>%
separate(col = label, into = c("lab1", "lab2"), sep = "\n",
fill = "right", remove = FALSE) %>%
mutate(y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lag(kig_shirt) == "transparent" | row_number == n(), 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
d0 <- n0 %>%
bind_rows(c0) %>%
mutate(label = str_wrap(string = lab, width = 12)) %>%
separate(col = label, into = c("lab1", "lab2"), sep = "\n",
fill = "right", remove = FALSE) %>%
mutate(y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lag(kit_shirt) == "transparent" | row_number == n(), 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
d0
n0$lab
d0 <- n0 %>%
bind_rows(c0) %>%
mutate(label = str_wrap(string = lab, width = 12)) %>%
separate(col = label, into = c("lab1", "lab2"), sep = "\n",
fill = "right", remove = FALSE) %>%
mutate(y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lab %in% c0$lab | lab == n0$lab[nrow(n0)], 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
View(d0)
# pdf(file = "./plot/fifa2018.pdf", height = 7, width = 7, useDingbats = FALSE)
pdf(file = "./plot/fifa.pdf", height = 7, width = 7, useDingbats = FALSE)
for(f in unique(d3$.frame)){
# for(f in max(d3$.frame)){
# for(f in min(d3$.frame)){
d4 <- d3 %>%
filter(.frame == f)
# d4 <- d4 %>%
# filter(kit_shirt != "#FEFFFE00")
if(!d4$year[1] %in% w3$year)
next()
par(mar = rep(0, 4), bg = "grey40", lheight = 0.8)
circos.clear()
circos.par(track.margin=c(0.01, -0.01), points.overflow.warning = FALSE,
# gap.degree = d0$gap,
gap.degree = 1.5,
start.degree = 90)
# plot the chord diagram
chordDiagram(
x = select(d4, nat_team, club_country, n),
col = pull(d4, kit_shirt),
order = d0 %>%
filter(lab %in% unique(c(d4$nat_team, d4$club_country))) %>%
pull(lab),
# fifa2018 order
# order = c(fifa2018, d0$lab[!d0$lab %in% fifa2018]),
grid.col = d0 %>%
select(lab, kit_shirt) %>%
deframe(),
transparency = 0.1,
directional = -1, direction.type = c("diffHeight", "arrows"),
link.arr.type = "big.arrow", diffHeight = -0.02,
link.sort = TRUE,
link.largest.ontop = TRUE,
h.ratio = 0.6,
xmax = m0,
annotationTrack = "grid",
annotationTrackHeight = 0.02,
preAllocateTracks = list(track.height = 0.2),
)
circos.trackPlotRegion(
track.index = 1,
bg.border = NA,
panel.fun = function(x, y) {
s <- get.cell.meta.data("sector.index")
dd <- filter(d0, lab == s)
xx <- get.cell.meta.data("xlim") %>%
mean()
theta <- circlize(mean(xx), 1.3)[1, 1] %% 360
ff <- ifelse(theta < 90 || theta > 270,
"clockwise", "reverse.clockwise")
aa <- c(1, 0.5)
if(theta < 90 || theta > 270)
aa <- c(0, 0.5)
flag_disp <- TRUE
if(is.na(dd$alpha3))
flag_disp <- FALSE
if(dd$alpha3 %in% c0$alpha3)
flag_disp <- FALSE
# fifa2018 drop flags for past teams
# if(!dd$lab %in% fifa2018)
# flag_disp <- FALSE
if(flag_disp){
flag_rot <- ifelse(theta < 90 || theta > 270, -90, 90)
flag <- dd$alpha3 %>%
paste0("./flag/", . ,".png") %>%
image_read() %>%
image_rotate(degrees = flag_rot)
circos.raster(image = flag, x = mean(xx), y = 0.2,
width = "0.3cm", facing = "inside")
}
circos.text(x = xx, y = ifelse(flag_disp, 0.38, 0.1),
# labels = dd$label2020,
labels = dd$label,
facing = ff, adj = aa,
col = "white", cex = 0.8)
}
)
y <- d4$year[1]
if(y %in% w3$year){
logo <- w3 %>%
filter(year == y) %>%
slice(1) %>%
pull(url_comp_logo) %>%
paste0("https:", .) %>%
image_read()
w <- h <- NULL
if(y != 2000)
w <- 0.14
if(y == 2000)
h <- 0.18
grid.raster(image = logo, x = 0.99, y = 0.99,
width = w, height = h,
hjust = 1, vjust = 1)
}
if(y %% 4 != 0)
y <- NULL
text(-1.1,1.02, paste0("FIFA World Cup Squads ", y), col="white", cex=1.4, pos=4)
text(-1.1,0.96,"Leagues to national teams", col="white", cex=0.75, pos=4)
text(-1.1,0.91,"by @guyabelguyabel", col="white", cex=0.75, pos=4)
text(-1.1,-0.72,"Details:", col="white", cex=0.7, pos=4)
yy = -0.76
text(-1.1,yy-0.03*0, "Colours based on the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*1, "shirt of each national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*2, "team. Chords represent", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*3, "connections between the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*4, "country of a player’s club (at ", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*5, "the chord base) and their national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*6, "team (at the arrow head). Chord thickness", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*7, "represents the number of players per club", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*8, "country-national team combination. Created", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*9, "in R. Data scraped from squad lists on Wikipedia:", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*10, "https://en.wikipedia.org/wiki/FIFA_World_Cup", col="white", cex=0.5, pos=4)
if(f %% 10 == 0)
message(f)
}
dev.off()
file.show("./plot/fifa.pdf")
# file.show("./plot/fifa2018.pdf")
# pdf(file = "./plot/fifa2018.pdf", height = 7, width = 7, useDingbats = FALSE)
pdf(file = "./plot/fifa.pdf", height = 7, width = 7, useDingbats = FALSE)
for(f in unique(d3$.frame)){
# for(f in max(d3$.frame)){
# for(f in min(d3$.frame)){
d4 <- d3 %>%
filter(.frame == f)
# d4 <- d4 %>%
# filter(kit_shirt != "#FEFFFE00")
if(!d4$year[1] %in% w3$year)
next()
par(mar = rep(0, 4), bg = "grey40", lheight = 0.8)
circos.clear()
circos.par(track.margin=c(0.01, -0.01), points.overflow.warning = FALSE,
gap.degree = d0$gap,
# gap.degree = 1.5,
start.degree = 90)
# plot the chord diagram
chordDiagram(
x = select(d4, nat_team, club_country, n),
col = pull(d4, kit_shirt),
order = d0 %>%
filter(lab %in% unique(c(d4$nat_team, d4$club_country))) %>%
pull(lab),
# fifa2018 order
# order = c(fifa2018, d0$lab[!d0$lab %in% fifa2018]),
grid.col = d0 %>%
select(lab, kit_shirt) %>%
deframe(),
transparency = 0.1,
directional = -1, direction.type = c("diffHeight", "arrows"),
link.arr.type = "big.arrow", diffHeight = -0.02,
link.sort = TRUE,
link.largest.ontop = TRUE,
h.ratio = 0.6,
xmax = m0,
annotationTrack = "grid",
annotationTrackHeight = 0.02,
preAllocateTracks = list(track.height = 0.2),
)
circos.trackPlotRegion(
track.index = 1,
bg.border = NA,
panel.fun = function(x, y) {
s <- get.cell.meta.data("sector.index")
dd <- filter(d0, lab == s)
xx <- get.cell.meta.data("xlim") %>%
mean()
theta <- circlize(mean(xx), 1.3)[1, 1] %% 360
ff <- ifelse(theta < 90 || theta > 270,
"clockwise", "reverse.clockwise")
aa <- c(1, 0.5)
if(theta < 90 || theta > 270)
aa <- c(0, 0.5)
flag_disp <- TRUE
if(is.na(dd$alpha3))
flag_disp <- FALSE
if(dd$alpha3 %in% c0$alpha3)
flag_disp <- FALSE
# fifa2018 drop flags for past teams
# if(!dd$lab %in% fifa2018)
# flag_disp <- FALSE
if(flag_disp){
flag_rot <- ifelse(theta < 90 || theta > 270, -90, 90)
flag <- dd$alpha3 %>%
paste0("./flag/", . ,".png") %>%
image_read() %>%
image_rotate(degrees = flag_rot)
circos.raster(image = flag, x = mean(xx), y = 0.2,
width = "0.3cm", facing = "inside")
}
circos.text(x = xx, y = ifelse(flag_disp, 0.38, 0.1),
# labels = dd$label2020,
labels = dd$label,
facing = ff, adj = aa,
col = "white", cex = 0.8)
}
)
y <- d4$year[1]
if(y %in% w3$year){
logo <- w3 %>%
filter(year == y) %>%
slice(1) %>%
pull(url_comp_logo) %>%
paste0("https:", .) %>%
image_read()
w <- h <- NULL
if(y != 2000)
w <- 0.14
if(y == 2000)
h <- 0.18
grid.raster(image = logo, x = 0.99, y = 0.99,
width = w, height = h,
hjust = 1, vjust = 1)
}
if(y %% 4 != 0)
y <- NULL
text(-1.1,1.02, paste0("FIFA World Cup Squads ", y), col="white", cex=1.4, pos=4)
text(-1.1,0.96,"Leagues to national teams", col="white", cex=0.75, pos=4)
text(-1.1,0.91,"by @guyabelguyabel", col="white", cex=0.75, pos=4)
text(-1.1,-0.72,"Details:", col="white", cex=0.7, pos=4)
yy = -0.76
text(-1.1,yy-0.03*0, "Colours based on the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*1, "shirt of each national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*2, "team. Chords represent", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*3, "connections between the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*4, "country of a player’s club (at ", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*5, "the chord base) and their national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*6, "team (at the arrow head). Chord thickness", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*7, "represents the number of players per club", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*8, "country-national team combination. Created", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*9, "in R. Data scraped from squad lists on Wikipedia:", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*10, "https://en.wikipedia.org/wiki/FIFA_World_Cup", col="white", cex=0.5, pos=4)
if(f %% 10 == 0)
message(f)
}
dev.off()
file.show("./plot/fifa.pdf")
# file.show("./plot/fifa2018.p
d0 <- n0 %>%
bind_rows(c0) %>%
# mutate(label = str_wrap(string = lab, width = 12)) %>%
# separate(col = label, into = c("lab1", "lab2"), sep = "\n",
# fill = "right", remove = FALSE) %>%
mutate(y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lab %in% c0$lab | lab == n0$lab[nrow(n0)], 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
d0 <- n0 %>%
bind_rows(c0) %>%
# mutate(label = str_wrap(string = lab, width = 12)) %>%
# separate(col = label, into = c("lab1", "lab2"), sep = "\n",
# fill = "right", remove = FALSE) %>%
mutate(
y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lab %in% c0$lab | lab == n0$lab[nrow(n0)], 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
d0 <- n0 %>%
bind_rows(c0) %>%
# mutate(label = str_wrap(string = lab, width = 12)) %>%
# separate(col = label, into = c("lab1", "lab2"), sep = "\n",
# fill = "right", remove = FALSE) %>%
mutate(
# y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lab %in% c0$lab | lab == n0$lab[nrow(n0)], 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
d0 <- n0 %>%
bind_rows(c0) %>%
mutate(
label = lab,
# label = str_wrap(string = lab, width = 12)
) %>%
# separate(col = label, into = c("lab1", "lab2"), sep = "\n",
# fill = "right", remove = FALSE) %>%
mutate(
# y = ifelse(test = !is.na(lab2), yes = 1, no = 0.6),
# label = ifelse(test = alpha3 %in% c("DEU", "GB-NIR", "IRL", "CZE"),
# label, lab),
# label = ifelse(label == "Czechoslovakia", "Czecho-\nslovakia", label),
# label = ifelse(label == "Bosnia and Herzegovina", "Bosnia and Herz.", label),
# label = ifelse(label == "Switzerland", "Switzer-\nland", label),
# gap = ifelse(kit_shirt == "transparent", 2.5, 1.5),
gap = ifelse(lab %in% c0$lab | lab == n0$lab[nrow(n0)], 2.5, 1.5),
label2018 = label,
# label2018 = ifelse(lab2018 == "Bosnia and Herzegovina", "Bosnia", label2018)
)
# pdf(file = "./plot/fifa2018.pdf", height = 7, width = 7, useDingbats = FALSE)
pdf(file = "./plot/fifa.pdf", height = 7, width = 7, useDingbats = FALSE)
for(f in unique(d3$.frame)){
# for(f in max(d3$.frame)){
# for(f in min(d3$.frame)){
d4 <- d3 %>%
filter(.frame == f)
# d4 <- d4 %>%
# filter(kit_shirt != "#FEFFFE00")
if(!d4$year[1] %in% w3$year)
next()
par(mar = rep(0, 4), bg = "grey40", lheight = 0.8)
circos.clear()
circos.par(track.margin=c(0.01, -0.01), points.overflow.warning = FALSE,
gap.degree = d0$gap,
# gap.degree = 1.5,
start.degree = 90)
# plot the chord diagram
chordDiagram(
x = select(d4, nat_team, club_country, n),
col = pull(d4, kit_shirt),
order = d0 %>%
filter(lab %in% unique(c(d4$nat_team, d4$club_country))) %>%
pull(lab),
# fifa2018 order
# order = c(fifa2018, d0$lab[!d0$lab %in% fifa2018]),
grid.col = d0 %>%
select(lab, kit_shirt) %>%
deframe(),
transparency = 0.1,
directional = -1, direction.type = c("diffHeight", "arrows"),
link.arr.type = "big.arrow", diffHeight = -0.02,
link.sort = TRUE,
link.largest.ontop = TRUE,
h.ratio = 0.6,
xmax = m0,
annotationTrack = "grid",
annotationTrackHeight = 0.02,
preAllocateTracks = list(track.height = 0.3),
)
circos.trackPlotRegion(
track.index = 1,
bg.border = NA,
panel.fun = function(x, y) {
s <- get.cell.meta.data("sector.index")
dd <- filter(d0, lab == s)
xx <- get.cell.meta.data("xlim") %>%
mean()
theta <- circlize(mean(xx), 1.3)[1, 1] %% 360
ff <- ifelse(theta < 90 || theta > 270,
"clockwise", "reverse.clockwise")
aa <- c(1, 0.5)
if(theta < 90 || theta > 270)
aa <- c(0, 0.5)
flag_disp <- TRUE
if(is.na(dd$alpha3))
flag_disp <- FALSE
if(dd$alpha3 %in% c0$alpha3)
flag_disp <- FALSE
# fifa2018 drop flags for past teams
# if(!dd$lab %in% fifa2018)
# flag_disp <- FALSE
if(flag_disp){
flag_rot <- ifelse(theta < 90 || theta > 270, -90, 90)
flag <- dd$alpha3 %>%
paste0("./flag/", . ,".png") %>%
image_read() %>%
image_rotate(degrees = flag_rot)
circos.raster(image = flag, x = mean(xx), y = 0.2,
width = "0.3cm", facing = "inside")
}
circos.text(x = xx, y = ifelse(flag_disp, 0.38, 0.1),
# labels = dd$label2020,
labels = dd$label,
facing = ff, adj = aa,
col = "white", cex = 0.8)
}
)
y <- d4$year[1]
if(y %in% w3$year){
logo <- w3 %>%
filter(year == y) %>%
slice(1) %>%
pull(url_comp_logo) %>%
paste0("https:", .) %>%
image_read()
w <- h <- NULL
if(y != 2000)
w <- 0.14
if(y == 2000)
h <- 0.18
grid.raster(image = logo, x = 0.99, y = 0.99,
width = w, height = h,
hjust = 1, vjust = 1)
}
if(y %% 4 != 0)
y <- NULL
text(-1.1,1.02, paste0("FIFA World Cup Squads ", y), col="white", cex=1.4, pos=4)
text(-1.1,0.96,"Leagues to national teams", col="white", cex=0.75, pos=4)
text(-1.1,0.91,"by @guyabelguyabel", col="white", cex=0.75, pos=4)
text(-1.1,-0.72,"Details:", col="white", cex=0.7, pos=4)
yy = -0.76
text(-1.1,yy-0.03*0, "Colours based on the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*1, "shirt of each national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*2, "team. Chords represent", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*3, "connections between the", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*4, "country of a player’s club (at ", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*5, "the chord base) and their national", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*6, "team (at the arrow head). Chord thickness", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*7, "represents the number of players per club", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*8, "country-national team combination. Created", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*9, "in R. Data scraped from squad lists on Wikipedia:", col="white", cex=0.5, pos=4)
text(-1.1,yy-0.03*10, "https://en.wikipedia.org/wiki/FIFA_World_Cup", col="white", cex=0.5, pos=4)
if(f %% 10 == 0)
message(f)
}
dev.off()
file.show("./plot/fifa.pdf")
# file.show("./plot/fifa2018.pdf")
477 +509
477 +509