ggplot2：向文本框传递一个变量值。

Question

R专家。

我想知道是否有办法将一个变量值传递给文本框。下面的代码是我用来创建地图的。在 "annotate "一行，我必须为每个地图输入状态平均值。因为我们有很多类似的地图，使用不同的变量，我想知道是否有办法在文本框中自动填充变量值？同样，在 "scale_fill_manual "这一行，我需要在变量 "quint "中输入数字来自定义图例标签，有没有更有效的方法？

先谢谢你了!

#quint is a quintile variable I developed from variable coef
ggplot()+
  geom_polygon(data=RIalz_data, aes(x=long, y=lat, group=group, fill=quint),size=0.3, color="#969696")+
  theme_void()+
  scale_fill_manual(values=c("#4292C6", "#92C5DE", "#FEE391","#EC7014","#CA0020"), 
               labels=c("7.84%-11.90%","11.91%-13.50%","13.51%-14.70%","14.71%-15.40%","15.41%-22.90%"))+
  theme(legend.position=c(0.84,0.15), 
        legend.background = element_blank(),
        legend.box.background = element_rect(colour = "black"),
        legend.title = element_text(colour = 'black', size = 10), 
        legend.key.size = unit(0.8, "cm"),
        legend.box.margin = margin(2, 2, 2, 2))+
  annotate("text", x=-71.92, y=41.26, label="State Average: 13.9%", hjust=0, size = 5, fontface=2)

EDIT：我已经附上了数据框架的前几个观测值的截图 演示图 而下面是前20行的输出。变量stateav53只有一个值，这是我希望传递给文本框的值。另一个变量'quint'是我用来编辑图例的值。

dput(head(RIdata2,20))

structure(list(long = c(-71.32217025, -71.32217741, -71.32218078, 
-71.32217968, -71.32217042, -71.3221554, -71.32213002, -71.32209299, 
-71.32207521, -71.32206824, -71.32205179, -71.32202472, -71.32201494, 
-71.3219907, -71.32197626, -71.32194267, -71.32190906, -71.32189649, 
-71.32186853, -71.32183016), lat = c(41.76994015, 41.7699019, 
41.76986367, 41.76975468, 41.76967901, 41.76959771, 41.76951862, 
41.76940913, 41.7693335, 41.76931201, 41.76926145, 41.7691979, 
41.76916612, 41.7691061, 41.76908071, 41.76903135, 41.76897847, 
41.76895236, 41.76889874, 41.76884377), order = 1:20, hole = c(FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE), piece = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "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", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74"), class = "factor"), id = c("1", 
"1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "1", "1", "1"), group = structure(c(1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L), .Label = c("1.1", "1.2", "1.3", "1.4", "1.5", "1.6", "1.7", 
"1.8", "1.9", "1.10", "10.1", "10.2", "10.3", "10.4", "10.5", 
"10.6", "10.7", "10.8", "11.1", "12.1", "13.1", "14.1", "15.1", 
"15.2", "15.3", "15.4", "15.5", "15.6", "15.7", "15.8", "15.9", 
"15.10", "15.11", "15.12", "15.13", "15.14", "15.15", "15.16", 
"15.17", "15.18", "15.19", "16.1", "17.1", "18.1", "18.2", "18.3", 
"18.4", "18.5", "18.6", "18.7", "18.8", "18.9", "18.10", "18.11", 
"18.12", "18.13", "18.14", "18.15", "18.16", "18.17", "18.18", 
"18.19", "18.20", "18.21", "18.22", "18.23", "18.24", "18.25", 
"18.26", "18.27", "18.28", "18.29", "18.30", "18.31", "18.32", 
"18.33", "18.34", "18.35", "18.36", "18.37", "18.38", "18.39", 
"18.40", "18.41", "18.42", "18.43", "18.44", "18.45", "18.46", 
"18.47", "18.48", "18.49", "18.50", "18.51", "18.52", "18.53", 
"18.54", "18.55", "18.56", "18.57", "18.58", "18.59", "18.60", 
"18.61", "18.62", "18.63", "18.64", "18.65", "18.66", "18.67", 
"18.68", "18.69", "18.70", "18.71", "18.72", "18.73", "18.74", 
"19.1", "19.2", "19.3", "19.4", "19.5", "19.6", "19.7", "2.1", 
"2.2", "2.3", "20.1", "20.2", "20.3", "20.4", "20.5", "20.6", 
"20.7", "20.8", "20.9", "20.10", "20.11", "20.12", "20.13", "20.14", 
"20.15", "20.16", "20.17", "20.18", "20.19", "20.20", "20.21", 
"20.22", "20.23", "20.24", "20.25", "20.26", "20.27", "20.28", 
"20.29", "20.30", "20.31", "20.32", "20.33", "20.34", "20.35", 
"20.36", "20.37", "20.38", "21.1", "21.2", "21.3", "21.4", "21.5", 
"21.6", "21.7", "21.8", "21.9", "21.10", "21.11", "21.12", "21.13", 
"21.14", "21.15", "21.16", "21.17", "21.18", "21.19", "21.20", 
"21.21", "21.22", "21.23", "21.24", "21.25", "21.26", "21.27", 
"21.28", "21.29", "21.30", "21.31", "21.32", "21.33", "21.34", 
"21.35", "21.36", "21.37", "21.38", "21.39", "21.40", "21.41", 
"21.42", "21.43", "21.44", "21.45", "21.46", "21.47", "21.48", 
"21.49", "21.50", "21.51", "21.52", "21.53", "21.54", "21.55", 
"21.56", "21.57", "21.58", "21.59", "21.60", "21.61", "21.62", 
"21.63", "21.64", "21.65", "22.1", "22.2", "23.1", "23.2", "23.3", 
"23.4", "23.5", "23.6", "23.7", "23.8", "24.1", "25.1", "26.1", 
"27.1", "27.2", "27.3", "27.4", "27.5", "27.6", "27.7", "27.8", 
"27.9", "27.10", "27.11", "27.12", "27.13", "27.14", "27.15", 
"27.16", "27.17", "27.18", "27.19", "27.20", "27.21", "27.22", 
"27.23", "28.1", "28.2", "28.3", "28.4", "28.5", "28.6", "28.7", 
"29.1", "3.1", "30.1", "31.1", "32.1", "32.2", "32.3", "32.4", 
"32.5", "32.6", "32.7", "32.8", "32.9", "32.10", "32.11", "32.12", 
"32.13", "32.14", "32.15", "32.16", "32.17", "32.18", "32.19", 
"32.20", "32.21", "32.22", "32.23", "32.24", "32.25", "32.26", 
"32.27", "32.28", "32.29", "32.30", "32.31", "32.32", "32.33", 
"33.1", "33.2", "33.3", "33.4", "33.5", "33.6", "33.7", "33.8", 
"33.9", "33.10", "33.11", "33.12", "33.13", "33.14", "33.15", 
"33.16", "33.17", "33.18", "34.1", "34.2", "34.3", "35.1", "35.2", 
"35.3", "35.4", "35.5", "35.6", "35.7", "35.8", "35.9", "35.10", 
"36.1", "36.2", "36.3", "36.4", "36.5", "36.6", "36.7", "36.8", 
"36.9", "36.10", "36.11", "36.12", "36.13", "36.14", "36.15", 
"36.16", "37.1", "38.1", "39.1", "4.1", "5.1", "5.2", "5.3", 
"5.4", "5.5", "5.6", "5.7", "5.8", "5.9", "5.10", "5.11", "5.12", 
"5.13", "5.14", "5.15", "5.16", "5.17", "5.18", "5.19", "5.20", 
"5.21", "5.22", "5.23", "5.24", "5.25", "5.26", "5.27", "5.28", 
"5.29", "5.30", "5.31", "5.32", "5.33", "5.34", "5.35", "5.36", 
"5.37", "5.38", "5.39", "5.40", "6.1", "7.1", "8.1", "9.1"), class = "factor"), 
    coef = c(0.1349402, 0.1349402, 0.1349402, 0.1349402, 0.1349402, 
    0.1349402, 0.1349402, 0.1349402, 0.1349402, 0.1349402, 0.1349402, 
    0.1349402, 0.1349402, 0.1349402, 0.1349402, 0.1349402, 0.1349402, 
    0.1349402, 0.1349402, 0.1349402), quint = structure(c(2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L), .Label = c("[0.0784,0.119]", "(0.119,0.135]", 
    "(0.135,0.147]", "(0.147,0.154]", "(0.154,0.229]"), class = "factor"), 
    stateav53 = c(0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 
    0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 0.139, 
    0.139, 0.139, 0.139, 0.139)), row.names = c(NA, 20L), class = "data.frame")

Answer 1

我将创建一个注释数据框，并将其与geom_text一起使用。你可以用以下方法创建变量元素 paste.

对于图例，我会创建一个标签栏，这样你就可以只用这个来满足你的审美。

然后你可以按组来分面。

library(tidyverse)

RIalz_data2 <- RIalz_data %>% mutate(stateav53 = 0.149, quint = "(1,2]", group = "2")
RIalz <- bind_rows(RIalz_data, RIalz_data2) %>%
  mutate(quint = str_sub(quint, 2, -2)) %>% 
  separate(quint, c("min", "max"), sep = ",") %>%
  mutate(newquint = paste0(as.numeric(min)*100,"%-",as.numeric(max)*100,"%"))

ann_df <- 
  RIalz %>% 
  group_by(group) %>%
  summarise(quint = unique(newquint), stateav53 = unique(stateav53)) 

ggplot()+
  geom_polygon(data=RIalz, aes(x=long, y=lat, group=group, fill=newquint)) +
  geom_text(data = ann_df, 
            mapping = aes(x=-71.92, y=41.26, 
                          label=paste("State Average:", stateav53*100, "%")), 
                          hjust=0) +
  facet_wrap(~group)

^{创建于2020-04-25由 重读包 (v0.3.0)}

有益的回答thread。https:/stackoverflow.coma521076577941188