如何使用 usmap 标记数字而不是名称？
How to label numbers instead of names using usmap?
我知道 usmap 在 plot_usmap() 中有一个选项 label。我想标记一些数字，而不是州名。我想在usmap中应该有与状态质心坐标相关的数据，但我不确定如何找到它。如果我能得到
坐标然后我可以用 geom_text().
标记数字
这是我的数据。
State Abbrev Code n_votes Attitude fips
1 Alabama Ala. AL 9 Solid Republican 01
2 Alaska Alaska AK 3 Toss-up 02
3 Arizona Ariz. AZ 11 Toss-up 04
4 Arkansas Ark. AR 6 Solid Republican 05
5 California Calif. CA 55 Solid Democrat 06
6 Colorado Colo. CO 9 Leaning to Democrat 08
7 Connecticut Conn. CT 7 Solid Democrat 09
8 Delaware Del. DE 3 Solid Democrat 10
9 District of Columbia D.C. DC 3 Solid Democrat 11
10 Florida Fla. FL 29 Leaning to Democrat 12
11 Georgia Ga. GA 16 Toss-up 13
12 Hawaii Hawaii HI 4 Solid Democrat 15
13 Idaho Idaho ID 4 Solid Republican 16
14 Illinois Ill. IL 20 Solid Democrat 17
15 Indiana Ind. IN 11 Leaning to Republican 18
16 Iowa Iowa IA 6 Leaning to Republican 19
17 Kansas Kans. KS 6 Leaning to Republican 20
18 Kentucky Ky. KY 8 Solid Republican 21
19 Louisiana La. LA 8 Solid Republican 22
20 Maine Maine ME 2 Solid Democrat 23
21 Maryland Md. MD 10 Solid Democrat 24
22 Massachusetts Mass. MA 11 Solid Democrat 25
23 Michigan Mich. MI 16 Leaning to Democrat 26
24 Minnesota Minn. MN 10 Toss-up 27
25 Mississippi Miss. MS 6 Solid Republican 28
26 Missouri Mo. MO 10 Leaning to Republican 29
27 Montana Mont. MT 3 Solid Republican 30
28 Nebraska Nebr. NE 2 Solid Republican 31
29 Nevada Nev. NV 6 Leaning to Democrat 32
30 New Hampshire N.H. NH 4 Leaning to Democrat 33
31 New Jersey N.J. NJ 14 Solid Democrat 34
32 New Mexico N.M. NM 5 Solid Democrat 35
33 New York N.Y. NY 29 Solid Democrat 36
34 North Carolina N.C. NC 15 Toss-up 37
35 North Dakota N.D. ND 3 Solid Republican 38
36 Ohio Ohio OH 18 Toss-up 39
37 Oklahoma Okla. OK 7 Solid Republican 40
38 Oregon Ore. OR 7 Solid Democrat 41
39 Pennsylvania Pa. PA 20 Leaning to Democrat 42
40 Rhode Island R.I. RI 4 Solid Democrat 44
41 South Carolina S.C. SC 9 Toss-up 45
42 South Dakota S.D. SD 3 Solid Republican 46
43 Tennessee Tenn. TN 11 Solid Republican 47
44 Texas Tex. TX 38 Toss-up 48
45 Utah Utah UT 6 Leaning to Republican 49
46 Vermont Vt. VT 3 Solid Democrat 50
47 Virginia Va. VA 13 Leaning to Democrat 51
48 Washington Wash. WA 12 Solid Democrat 53
49 West Virginia W.Va. WV 5 Solid Republican 54
50 Wisconsin Wis. WI 10 Leaning to Democrat 55
51 Wyoming Wyo. WY 3 Solid Republican 56
我想标注n_votes，应该是这样的。我该怎么做？
谢谢，
段
这可以这样实现：
获取包 usmap.
中作为数据包含的状态质心的坐标
使用坐标
将您的数据集加入 df
使用geom_text用您的数据标记地图
因为阅读和整理您提供的数据需要一些时间（下一次：在控制台中键入 dput(NAME_OF_DATASET) 并将以 structure(... 开头的输出复制并粘贴到您的 post) 我只是使用包 usmap 提供的 statepop 数据作为示例数据：
library(usmap)
library(ggplot2)
library(dplyr)
library(stringr)
# Get centroids
centroid_labels <- utils::read.csv(system.file("extdata", paste0("us_", "states", "_centroids.csv"), package = "usmap"), stringsAsFactors = FALSE)
# Join data to centroids
data_labels <- centroid_labels %>%
mutate(fips = stringr::str_pad(fips, 2, pad = "0")) %>%
left_join(statepop)
#> Joining, by = c("fips", "abbr", "full")
plot_usmap(data=statepop, values="pop_2015", color='white', labels=FALSE) +
guides(fill=FALSE) +
geom_text(data = data_labels, ggplot2::aes(x = x, y = y,
label = scales::number(pop_2015, scale = 1e-3, accuracy = 1)), color = "white")
这是一个替代方法 fully-worked 示例，它允许您通过将美国地图转换为 sf 对象来使用 ggplot。这使您可以自由选择 ggplot:
获得的绘图参数
library(usmap)
library(sf)
library(ggplot2)
d <- us_map("states")
USS <- lapply(split(d, d$full), function(x) {
if(length(table(x$piece)) == 1)
{
st_polygon(list(cbind(x$x, x$y)))
}
else
{
st_multipolygon(list(lapply(split(x, x$piece), function(y) cbind(y$x, y$y))))
}
})
USA <- st_sfc(USS, crs = usmap_crs()@projargs)
USA <- st_sf(data.frame(df, geometry = USA))
USA$centroids <- st_centroid(USA$geometry)
虽然这段代码可能看起来有点复杂，但它可以轻松绘制：
ggplot(USA) +
geom_sf(aes(fill = Attitude)) +
geom_sf_text(aes(label = n_votes, geometry = centroids), colour = "white") +
scale_fill_manual(values = c("#67b5e3", "#ffada2","#1155b6",
"#ed4747", "#cccccc"), guide = guide_none()) +
theme_void()
数据
df <- df <- structure(list(State = structure(1:51, .Label = c("Alabama",
"Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut",
"Delaware", "District of Columbia", "Florida", "Georgia", "Hawaii",
"Idaho", "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky",
"Louisiana", "Maine", "Maryland", "Massachusetts", "Michigan",
"Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska",
"Nevada", "New Hampshire", "New Jersey", "New Mexico", "New York",
"North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon",
"Pennsylvania", "Rhode Island", "South Carolina", "South Dakota",
"Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington",
"West Virginia", "Wisconsin", "Wyoming"), class = "factor"),
Abbrev = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 9L, 8L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 22L,
21L, 23L, 24L, 25L, 26L, 27L, 34L, 35L, 30L, 31L, 32L, 33L,
28L, 29L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L,
47L, 46L, 49L, 48L, 50L, 51L), .Label = c("Ala.", "Alaska",
"Ariz.", "Ark.", "Calif.", "Colo.", "Conn.", "D.C.", "Del.",
"Fla.", "Ga.", "Hawaii", "Idaho", "Ill.", "Ind.", "Iowa",
"Kans.", "Ky.", "La.", "Maine", "Mass.", "Md.", "Mich.",
"Minn.", "Miss.", "Mo.", "Mont.", "N.C.", "N.D.", "N.H.",
"N.J.", "N.M.", "N.Y.", "Nebr.", "Nev.", "Ohio", "Okla.",
"Ore.", "Pa.", "R.I.", "S.C.", "S.D.", "Tenn.", "Tex.", "Utah",
"Va.", "Vt.", "W.Va.", "Wash.", "Wis.", "Wyo."), class = "factor"),
Code = structure(c(2L, 1L, 4L, 3L, 5L, 6L, 7L, 9L, 8L, 10L,
11L, 12L, 14L, 15L, 16L, 13L, 17L, 18L, 19L, 22L, 21L, 20L,
23L, 24L, 26L, 25L, 27L, 30L, 34L, 31L, 32L, 33L, 35L, 28L,
29L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 47L,
46L, 48L, 50L, 49L, 51L), .Label = c("AK", "AL", "AR", "AZ",
"CA", "CO", "CT", "DC", "DE", "FL", "GA", "HI", "IA", "ID",
"IL", "IN", "KS", "KY", "LA", "MA", "MD", "ME", "MI", "MN",
"MO", "MS", "MT", "NC", "ND", "NE", "NH", "NJ", "NM", "NV",
"NY", "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX",
"UT", "VA", "VT", "WA", "WI", "WV", "WY"), class = "factor"),
n_votes = c(9, 3, 11, 6, 55, 9, 7, 3, 3, 29, 16, 4, 4, 20,
11, 6, 6, 8, 8, 2, 10, 11, 16, 10, 6, 10, 3, 2, 6, 4, 14,
5, 29, 15, 3, 18, 7, 7, 20, 4, 9, 3, 11, 38, 6, 3, 13, 12,
5, 10, 3), Attitude = structure(c(4L, 5L, 5L, 4L, 3L, 1L,
3L, 3L, 3L, 1L, 5L, 3L, 4L, 3L, 2L, 2L, 2L, 4L, 4L, 3L, 3L,
3L, 1L, 5L, 4L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 3L, 5L, 4L, 5L,
4L, 3L, 1L, 3L, 5L, 4L, 4L, 5L, 2L, 3L, 1L, 3L, 4L, 1L, 4L
), .Label = c("Leaning to Democrat", "Leaning to Republican",
"Solid Democrat", "Solid Republican", "Toss-up"), class = "factor"),
fips = structure(1:51, .Label = c("01", "02", "04", "05",
"06", "08", "09", "10", "11", "12", "13", "15", "16", "17",
"18", "19", "20", "21", "22", "23", "24", "25", "26", "27",
"28", "29", "30", "31", "32", "33", "34", "35", "36", "37",
"38", "39", "40", "41", "42", "44", "45", "46", "47", "48",
"49", "50", "51", "53", "54", "55", "56"), class = "factor")),
class = "data.frame", row.names = c(NA, -51L))
我知道 usmap 在 plot_usmap() 中有一个选项 label。我想标记一些数字，而不是州名。我想在usmap中应该有与状态质心坐标相关的数据，但我不确定如何找到它。如果我能得到
坐标然后我可以用 geom_text().
这是我的数据。
State Abbrev Code n_votes Attitude fips
1 Alabama Ala. AL 9 Solid Republican 01
2 Alaska Alaska AK 3 Toss-up 02
3 Arizona Ariz. AZ 11 Toss-up 04
4 Arkansas Ark. AR 6 Solid Republican 05
5 California Calif. CA 55 Solid Democrat 06
6 Colorado Colo. CO 9 Leaning to Democrat 08
7 Connecticut Conn. CT 7 Solid Democrat 09
8 Delaware Del. DE 3 Solid Democrat 10
9 District of Columbia D.C. DC 3 Solid Democrat 11
10 Florida Fla. FL 29 Leaning to Democrat 12
11 Georgia Ga. GA 16 Toss-up 13
12 Hawaii Hawaii HI 4 Solid Democrat 15
13 Idaho Idaho ID 4 Solid Republican 16
14 Illinois Ill. IL 20 Solid Democrat 17
15 Indiana Ind. IN 11 Leaning to Republican 18
16 Iowa Iowa IA 6 Leaning to Republican 19
17 Kansas Kans. KS 6 Leaning to Republican 20
18 Kentucky Ky. KY 8 Solid Republican 21
19 Louisiana La. LA 8 Solid Republican 22
20 Maine Maine ME 2 Solid Democrat 23
21 Maryland Md. MD 10 Solid Democrat 24
22 Massachusetts Mass. MA 11 Solid Democrat 25
23 Michigan Mich. MI 16 Leaning to Democrat 26
24 Minnesota Minn. MN 10 Toss-up 27
25 Mississippi Miss. MS 6 Solid Republican 28
26 Missouri Mo. MO 10 Leaning to Republican 29
27 Montana Mont. MT 3 Solid Republican 30
28 Nebraska Nebr. NE 2 Solid Republican 31
29 Nevada Nev. NV 6 Leaning to Democrat 32
30 New Hampshire N.H. NH 4 Leaning to Democrat 33
31 New Jersey N.J. NJ 14 Solid Democrat 34
32 New Mexico N.M. NM 5 Solid Democrat 35
33 New York N.Y. NY 29 Solid Democrat 36
34 North Carolina N.C. NC 15 Toss-up 37
35 North Dakota N.D. ND 3 Solid Republican 38
36 Ohio Ohio OH 18 Toss-up 39
37 Oklahoma Okla. OK 7 Solid Republican 40
38 Oregon Ore. OR 7 Solid Democrat 41
39 Pennsylvania Pa. PA 20 Leaning to Democrat 42
40 Rhode Island R.I. RI 4 Solid Democrat 44
41 South Carolina S.C. SC 9 Toss-up 45
42 South Dakota S.D. SD 3 Solid Republican 46
43 Tennessee Tenn. TN 11 Solid Republican 47
44 Texas Tex. TX 38 Toss-up 48
45 Utah Utah UT 6 Leaning to Republican 49
46 Vermont Vt. VT 3 Solid Democrat 50
47 Virginia Va. VA 13 Leaning to Democrat 51
48 Washington Wash. WA 12 Solid Democrat 53
49 West Virginia W.Va. WV 5 Solid Republican 54
50 Wisconsin Wis. WI 10 Leaning to Democrat 55
51 Wyoming Wyo. WY 3 Solid Republican 56
我想标注n_votes，应该是
谢谢，
段
这可以这样实现：
获取包
中作为数据包含的状态质心的坐标usmap.使用坐标
将您的数据集加入 df使用geom_text用您的数据标记地图
因为阅读和整理您提供的数据需要一些时间（下一次：在控制台中键入 dput(NAME_OF_DATASET) 并将以 structure(... 开头的输出复制并粘贴到您的 post) 我只是使用包 usmap 提供的 statepop 数据作为示例数据：
library(usmap)
library(ggplot2)
library(dplyr)
library(stringr)
# Get centroids
centroid_labels <- utils::read.csv(system.file("extdata", paste0("us_", "states", "_centroids.csv"), package = "usmap"), stringsAsFactors = FALSE)
# Join data to centroids
data_labels <- centroid_labels %>%
mutate(fips = stringr::str_pad(fips, 2, pad = "0")) %>%
left_join(statepop)
#> Joining, by = c("fips", "abbr", "full")
plot_usmap(data=statepop, values="pop_2015", color='white', labels=FALSE) +
guides(fill=FALSE) +
geom_text(data = data_labels, ggplot2::aes(x = x, y = y,
label = scales::number(pop_2015, scale = 1e-3, accuracy = 1)), color = "white")
这是一个替代方法 fully-worked 示例，它允许您通过将美国地图转换为 sf 对象来使用 ggplot。这使您可以自由选择 ggplot:
library(usmap)
library(sf)
library(ggplot2)
d <- us_map("states")
USS <- lapply(split(d, d$full), function(x) {
if(length(table(x$piece)) == 1)
{
st_polygon(list(cbind(x$x, x$y)))
}
else
{
st_multipolygon(list(lapply(split(x, x$piece), function(y) cbind(y$x, y$y))))
}
})
USA <- st_sfc(USS, crs = usmap_crs()@projargs)
USA <- st_sf(data.frame(df, geometry = USA))
USA$centroids <- st_centroid(USA$geometry)
虽然这段代码可能看起来有点复杂，但它可以轻松绘制：
ggplot(USA) +
geom_sf(aes(fill = Attitude)) +
geom_sf_text(aes(label = n_votes, geometry = centroids), colour = "white") +
scale_fill_manual(values = c("#67b5e3", "#ffada2","#1155b6",
"#ed4747", "#cccccc"), guide = guide_none()) +
theme_void()
数据
df <- df <- structure(list(State = structure(1:51, .Label = c("Alabama",
"Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut",
"Delaware", "District of Columbia", "Florida", "Georgia", "Hawaii",
"Idaho", "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky",
"Louisiana", "Maine", "Maryland", "Massachusetts", "Michigan",
"Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska",
"Nevada", "New Hampshire", "New Jersey", "New Mexico", "New York",
"North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon",
"Pennsylvania", "Rhode Island", "South Carolina", "South Dakota",
"Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington",
"West Virginia", "Wisconsin", "Wyoming"), class = "factor"),
Abbrev = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 9L, 8L,
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 22L,
21L, 23L, 24L, 25L, 26L, 27L, 34L, 35L, 30L, 31L, 32L, 33L,
28L, 29L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L,
47L, 46L, 49L, 48L, 50L, 51L), .Label = c("Ala.", "Alaska",
"Ariz.", "Ark.", "Calif.", "Colo.", "Conn.", "D.C.", "Del.",
"Fla.", "Ga.", "Hawaii", "Idaho", "Ill.", "Ind.", "Iowa",
"Kans.", "Ky.", "La.", "Maine", "Mass.", "Md.", "Mich.",
"Minn.", "Miss.", "Mo.", "Mont.", "N.C.", "N.D.", "N.H.",
"N.J.", "N.M.", "N.Y.", "Nebr.", "Nev.", "Ohio", "Okla.",
"Ore.", "Pa.", "R.I.", "S.C.", "S.D.", "Tenn.", "Tex.", "Utah",
"Va.", "Vt.", "W.Va.", "Wash.", "Wis.", "Wyo."), class = "factor"),
Code = structure(c(2L, 1L, 4L, 3L, 5L, 6L, 7L, 9L, 8L, 10L,
11L, 12L, 14L, 15L, 16L, 13L, 17L, 18L, 19L, 22L, 21L, 20L,
23L, 24L, 26L, 25L, 27L, 30L, 34L, 31L, 32L, 33L, 35L, 28L,
29L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 47L,
46L, 48L, 50L, 49L, 51L), .Label = c("AK", "AL", "AR", "AZ",
"CA", "CO", "CT", "DC", "DE", "FL", "GA", "HI", "IA", "ID",
"IL", "IN", "KS", "KY", "LA", "MA", "MD", "ME", "MI", "MN",
"MO", "MS", "MT", "NC", "ND", "NE", "NH", "NJ", "NM", "NV",
"NY", "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX",
"UT", "VA", "VT", "WA", "WI", "WV", "WY"), class = "factor"),
n_votes = c(9, 3, 11, 6, 55, 9, 7, 3, 3, 29, 16, 4, 4, 20,
11, 6, 6, 8, 8, 2, 10, 11, 16, 10, 6, 10, 3, 2, 6, 4, 14,
5, 29, 15, 3, 18, 7, 7, 20, 4, 9, 3, 11, 38, 6, 3, 13, 12,
5, 10, 3), Attitude = structure(c(4L, 5L, 5L, 4L, 3L, 1L,
3L, 3L, 3L, 1L, 5L, 3L, 4L, 3L, 2L, 2L, 2L, 4L, 4L, 3L, 3L,
3L, 1L, 5L, 4L, 2L, 4L, 4L, 1L, 1L, 3L, 3L, 3L, 5L, 4L, 5L,
4L, 3L, 1L, 3L, 5L, 4L, 4L, 5L, 2L, 3L, 1L, 3L, 4L, 1L, 4L
), .Label = c("Leaning to Democrat", "Leaning to Republican",
"Solid Democrat", "Solid Republican", "Toss-up"), class = "factor"),
fips = structure(1:51, .Label = c("01", "02", "04", "05",
"06", "08", "09", "10", "11", "12", "13", "15", "16", "17",
"18", "19", "20", "21", "22", "23", "24", "25", "26", "27",
"28", "29", "30", "31", "32", "33", "34", "35", "36", "37",
"38", "39", "40", "41", "42", "44", "45", "46", "47", "48",
"49", "50", "51", "53", "54", "55", "56"), class = "factor")),
class = "data.frame", row.names = c(NA, -51L))