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ggrepel：将标签移动到ggplot区域外（向右侧）

rggplot2ggrepel
4
library(tidyverse)
library(ggrepel)
df <- structure(list(Fruit = c("Yellow Pear", "Yellow Pear", "Yellow Pear", 
"Yellow Pear", "Yellow Pear", "Yellow Pear", "Yellow Pear", "Yellow Pear", 
"Yellow Pear", "Yellow Pear", "Yellow Pear", "Yellow Pear", "Tropical Banana", 
"Tropical Banana", "Tropical Banana", "Tropical Banana", "Tropical Banana", 
"Tropical Banana", "Tropical Banana", "Tropical Banana", "Tropical Banana", 
"Tropical Banana", "Tropical Banana", "Tropical Banana", "Farm Fresh Strawberries", 
"Farm Fresh Strawberries", "Farm Fresh Strawberries", "Farm Fresh Strawberries", 
"Farm Fresh Strawberries", "Farm Fresh Strawberries", "Farm Fresh Strawberries", 
"Farm Fresh Strawberries", "Farm Fresh Strawberries", "Farm Fresh Strawberries", 
"Farm Fresh Strawberries", "Farm Fresh Strawberries", "Melon Mango", 
"Melon Mango", "Melon Mango", "Melon Mango", "Melon Mango", "Melon Mango", 
"Melon Mango", "Melon Mango", "Melon Mango", "Melon Mango", "Melon Mango", 
"Melon Mango", "Dragonfruit", "Dragonfruit", "Dragonfruit", "Dragonfruit", 
"Dragonfruit", "Dragonfruit", "Dragonfruit", "Dragonfruit", "Dragonfruit", 
"Dragonfruit", "Dragonfruit", "Dragonfruit", "Peaches", "Peaches", 
"Peaches", "Peaches", "Peaches", "Peaches", "Peaches", "Peaches", 
"Peaches", "Peaches", "Peaches", "Peaches", "Blueberry", "Blueberry", 
"Blueberry", "Blueberry", "Blueberry", "Blueberry", "Blueberry", 
"Blueberry", "Blueberry", "Blueberry", "Blueberry", "Blueberry", 
"Blueberry GS", "Blueberry GS", "Blueberry GS", "Blueberry GS", 
"Blueberry GS", "Blueberry GS", "Blueberry GS", "Blueberry GS", 
"Blueberry GS", "Blueberry GS", "Blueberry GS", "Blueberry GS", 
"Red Delicious Apples", "Red Delicious Apples", "Red Delicious Apples", 
"Red Delicious Apples", "Red Delicious Apples", "Red Delicious Apples", 
"Red Delicious Apples", "Red Delicious Apples", "Red Delicious Apples", 
"Red Delicious Apples", "Red Delicious Apples", "Red Delicious Apples", 
"Grapes", "Grapes", "Grapes", "Grapes", "Grapes", "Grapes", "Grapes", 
"Grapes", "Grapes", "Grapes", "Grapes", "Grapes", "Cherry", "Cherry", 
"Cherry", "Cherry", "Cherry", "Cherry", "Cherry", "Cherry", "Cherry", 
"Cherry", "Cherry", "Cherry", "Green Apples", "Green Apples", 
"Green Apples", "Green Apples", "Green Apples", "Green Apples", 
"Green Apples", "Green Apples", "Green Apples", "Green Apples", 
"Green Apples", "Green Apples", "Yellow Apples", "Yellow Apples", 
"Yellow Apples", "Yellow Apples", "Yellow Apples", "Yellow Apples", 
"Yellow Apples", "Yellow Apples", "Yellow Apples", "Yellow Apples", 
"Yellow Apples", "Yellow Apples", "Perfect Punchy Pineapple", 
"Perfect Punchy Pineapple", "Perfect Punchy Pineapple", "Perfect Punchy Pineapple", 
"Perfect Punchy Pineapple", "Perfect Punchy Pineapple", "Perfect Punchy Pineapple", 
"Perfect Punchy Pineapple", "Perfect Punchy Pineapple", "Perfect Punchy Pineapple", 
"Perfect Punchy Pineapple", "Perfect Punchy Pineapple", "Watermelon", 
"Watermelon", "Watermelon", "Watermelon", "Watermelon", "Watermelon", 
"Watermelon", "Watermelon", "Watermelon", "Watermelon", "Watermelon", 
"Watermelon", "Red Raspberry", "Red Raspberry", "Red Raspberry", 
"Red Raspberry", "Red Raspberry", "Red Raspberry", "Red Raspberry", 
"Red Raspberry", "Red Raspberry", "Red Raspberry", "Red Raspberry", 
"Red Raspberry", "Blackberry", "Blackberry", "Blackberry", "Blackberry", 
"Blackberry", "Blackberry", "Blackberry", "Blackberry", "Blackberry", 
"Blackberry", "Blackberry", "Blackberry", "Avocado", "Avocado", 
"Avocado", "Avocado", "Avocado", "Avocado", "Avocado", "Avocado", 
"Avocado", "Avocado", "Avocado", "Avocado", "Cherimoya Custard Apple", 
"Cherimoya Custard Apple", "Cherimoya Custard Apple", "Cherimoya Custard Apple", 
"Cherimoya Custard Apple", "Cherimoya Custard Apple", "Cherimoya Custard Apple", 
"Cherimoya Custard Apple", "Cherimoya Custard Apple", "Cherimoya Custard Apple", 
"Cherimoya Custard Apple", "Cherimoya Custard Apple", "Nectarine", 
"Nectarine", "Nectarine", "Nectarine", "Nectarine", "Nectarine", 
"Nectarine", "Nectarine", "Nectarine", "Nectarine", "Nectarine", 
"Nectarine", "Plum Prune Pineapple", "Plum Prune Pineapple", 
"Plum Prune Pineapple", "Plum Prune Pineapple", "Plum Prune Pineapple", 
"Plum Prune Pineapple", "Plum Prune Pineapple", "Plum Prune Pineapple", 
"Plum Prune Pineapple", "Plum Prune Pineapple", "Plum Prune Pineapple", 
"Plum Prune Pineapple", "Pomegranate", "Pomegranate", "Pomegranate", 
"Pomegranate", "Pomegranate", "Pomegranate", "Pomegranate", "Pomegranate", 
"Pomegranate", "Pomegranate", "Pomegranate", "Pomegranate", "Surinam Cherry", 
"Surinam Cherry", "Surinam Cherry", "Surinam Cherry", "Surinam Cherry", 
"Surinam Cherry", "Surinam Cherry", "Surinam Cherry", "Surinam Cherry", 
"Surinam Cherry", "Surinam Cherry", "Surinam Cherry"), Date = structure(c(17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956, 17622, 17652, 17683, 17713, 
17744, 17775, 17805, 17836, 17866, 17897, 17928, 17956, 17622, 
17652, 17683, 17713, 17744, 17775, 17805, 17836, 17866, 17897, 
17928, 17956, 17622, 17652, 17683, 17713, 17744, 17775, 17805, 
17836, 17866, 17897, 17928, 17956), class = "Date"), Value = c(0.00488, 
0.00603, 0.00477, 0.00589, 0.00814, 0.00642, 0.00679, 0.00609, 
0.00403, 0.00909, 0.00727, 0.0048, 0.02366, 0.01599, 0.01527, 
0.0164, 0.01521, 0.01566, 0.01381, 0.01941, 0.0196, 0.02411, 
0.02158, 0.02307, 0.02161, 0.02419, 0.02393, 0.01991, 0.0218, 
0.02036, 0.01666, 0.02389, 0.01842, 0.02932, 0.01998, 0.02315, 
0.04053, 0.04161, 0.04045, 0.04937, 0.03595, 0.03852, 0.04895, 
0.03786, 0.03136, 0.04497, 0.03678, 0.04276, 0.00175, 0.00243, 
0.00474, 0.00502, 0.00665, 0.00457, 0.00847, 0.00494, 0.00271, 
0.00265, 0.00602, 0.00451, 0.03749, 0.0341, 0.03823, 0.0432, 
0.04814, 0.03773, 0.03829, 0.0383, 0.03803, 0.04674, 0.03968, 
0.04482, 0.25824, 0.2541, 0.26486, 0.32075, 0.26146, 0.27273, 
0.28191, 0.23684, 0.22193, 0.29765, 0.30052, 0.31282, 0.0131, 
0.02674, 0.01137, 0.01965, 0.02185, 0.02844, 0.02298, 0.02145, 
0.02187, 0.03242, 0.02213, 0.02128, 0.05535, 0.0588, 0.05653, 
0.05804, 0.04997, 0.05085, 0.05835, 0.05721, 0.05204, 0.06247, 
0.06009, 0.06425, 0.275, 0.5, 0.4, 0.375, 0.45, 0.425, 0.275, 
0.275, 0.225, 0.3, 0.325, 0.35, 0.25047, 0.26969, 0.23524, 0.21364, 
0.23965, 0.21167, 0.2466, 0.2575, 0.22213, 0.23955, 0.22099, 
0.20157, 0.01455, 0.01958, 0.0194, 0.01931, 0.01916, 0.01901, 
0.02117, 0.02436, 0.03012, 0.02367, 0.0211, 0.01618, 0.03707, 
0.03481, 0.03357, 0.03637, 0.04391, 0.03939, 0.03922, 0.05372, 
0.03559, 0.05253, 0.04771, 0.04948, 0.09733, 0.12215, 0.11575, 
0.10066, 0.11662, 0.09571, 0.09593, 0.11425, 0.09891, 0.13107, 
0.11913, 0.12753, 0.16986, 0.17615, 0.21867, 0.18883, 0.18898, 
0.22762, 0.135, 0.17317, 0.16945, 0.14858, 0.19451, 0.11659, 
0.09441, 0.15135, 0.11804, 0.11181, 0.12594, 0.10972, 0.11313, 
0.08373, 0.10206, 0.10558, 0.08821, 0.10629, 0.01472, 0.01466, 
0.01521, 0.01733, 0.01718, 0.01489, 0.01457, 0.0174, 0.01009, 
0.01713, 0.01636, 0.01198, 0.0687, 0.08581, 0.08247, 0.08407, 
0.08265, 0.0785, 0.06906, 0.08113, 0.07246, 0.07717, 0.07311, 
0.07862, 0.04762, 0.02301, 0.01534, 0.0291, 0.03063, 0.02757, 
0.0229, 0.03049, 0.01524, 0.01524, 0.01979, 0.02435, 0.3038, 
0.32317, 0.34615, 0.28571, 0.30423, 0.35196, 0.34341, 0.28165, 
0.24615, 0.26303, 0.3, 0.28471, 0.20833, 0.21667, 0.28926, 0.29032, 
0.31496, 0.18182, 0.31343, 0.26277, 0.23188, 0.26056, 0.24658, 
0.21711, 0.24265, 0.38571, 0.22667, 0.24837, 0.29221, 0.27848, 
0.2622, 0.28824, 0.26901, 0.29444, 0.2459, 0.3, 0.25843, 0.2809, 
0.18436, 0.3352, 0.26816, 0.22222, 0.25556, 0.24309, 0.22099, 
0.24309, 0.21547, 0.20879), Violation = c(FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-276L)) %>% 
  mutate(label = if_else(Date == max(Date), Fruit, NA_character_))

df
#> # A tibble: 276 x 5
#>    Fruit       Date         Value Violation label
#>    <chr>       <date>       <dbl> <lgl>     <chr>
#>  1 Yellow Pear 2018-04-01 0.00488 FALSE     NA   
#>  2 Yellow Pear 2018-05-01 0.00603 FALSE     NA   
#>  3 Yellow Pear 2018-06-01 0.00477 FALSE     NA   
#>  4 Yellow Pear 2018-07-01 0.00589 FALSE     NA   
#>  5 Yellow Pear 2018-08-01 0.00814 FALSE     NA   
#>  6 Yellow Pear 2018-09-01 0.00642 FALSE     NA   
#>  7 Yellow Pear 2018-10-01 0.00679 FALSE     NA   
#>  8 Yellow Pear 2018-11-01 0.00609 FALSE     NA   
#>  9 Yellow Pear 2018-12-01 0.00403 FALSE     NA   
#> 10 Yellow Pear 2019-01-01 0.00909 FALSE     NA   
#> # ... with 266 more rows

抱歉之前提供的数据框代码块太大了，请将其复制粘贴到R Studio中以开始工作。

现在，我正在尝试使用ggrepel包来标记如下所示的红线。我已经在ggrepel中调整了各种参数，但没有得到想要的效果。我希望标签不会挡住图表，并排列在右侧，按照排名顺序。能否让标签也变成红色?

使用哪些ggrepel参数可以实现我的需求？或者是否有更好的方法在普通ggplot中实现这一点？

ggplot(df, aes(Date, Value, group = Fruit)) + 
  geom_line(aes(color = Violation)) +
  scale_color_manual(values = c("grey30", "red")) + 
  scale_x_date(breaks = "month", date_labels = "%b") +
  scale_y_continuous(breaks = seq(0, 0.7, by = 0.05)) + 
  coord_cartesian(ylim = c(-0.25, 0.7)) +
  labs(x = NULL, y = "Value\n") +
  theme_minimal() + 
  theme(panel.grid = element_blank(),
        axis.ticks.x = element_line(),
        #axis.line.x = element_blank(),
        axis.line.y = element_line(), 
        axis.ticks.y = element_line()) + 
  geom_text_repel(data = df %>% filter(Violation == TRUE),
                  aes(label = label), 
                  direction = "y", 
                  hjust = 0, 
                  segment.size = 0.2,
                  nudge_x = 1,
                  na.rm = TRUE)

ggrepel labels

2
https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html#limit-labels-to-a-specific-area - Jon Spring
@Jon Spring 我添加了 xlim = as.Date(c("2019-04-01", "2019-08-01")) 参数，但似乎没有改变任何东西。不过还是谢谢你的提示。 - Display name
1
添加 coord_cartesian(ylim = c(-0.25, 0.7), clip = "off")。 - Jon Spring
2个回答
10
ggplot(df, aes(Date, Value, group = Fruit)) + 
  geom_line(aes(color = Violation)) +
  scale_color_manual(values = c("grey30", "red")) + 
  scale_x_date(breaks = "month", date_labels = "%b") +
  scale_y_continuous(breaks = seq(0, 0.7, by = 0.05)) + 
  coord_cartesian(ylim = c(-0.25, 0.7), clip = "off") +
  labs(x = NULL, y = "Value\n") +
  theme_minimal() + 
  theme(panel.grid = element_blank(),
        axis.ticks.x = element_line(),
        #axis.line.x = element_blank(),
        axis.line.y = element_line(), 
        axis.ticks.y = element_line(), 
        legend.position = c(0.8, 0.8),
        plot.margin = unit(c(0.1, 5, 0.1, 0.1), "cm")) + 
  geom_text_repel(data = df %>% filter(Violation == TRUE),
                  aes(label = label), 
                  direction = "y", 
                  hjust = 0, 
                  segment.size = 0.2,
                  na.rm = TRUE,
                  xlim = as.Date(c("2019-04-01", "2019-10-01")),
                  ylim = c(0, .2))

enter image description here

1
这是一个很棒的技巧，同样适用于 https://dev59.com/1sHqa4cB1Zd3GeqPxVW7。一个想法：可以使用 data = ~ filter(., Violation==TRUE) 替代 data = df %>% filter(Violation==TRUE)。好处在于它使用传递给 ggplot 的数据；如果不使用它，如果您将原始数据从（例如）df 更改为 df2 并忘记更改所有使用 df 的 data= 引用，则可能会看到一些令人困惑的结果；使用 data=~...，这种情况就不会发生。 - r2evans
JonSpring，我认识到这是从问题中复制的代码，只是觉得这是一个提及的好地方。 - r2evans
@r2evans，如果要将标签放置在图形上方而不是右侧，应该怎么做？ - ramen
1
虽然你可以使用ggrepel来实现，但我建议你尝试创建一个次要的y轴，并将标签添加为自定义刻度。这样应该能够得到相同的结果。步骤大致如下：
val <- c(0.023070, 0.049185, 0.075300, 0.101415, 0.127530)
lbl <- c("Tropical Banana", "Peaches", "Red Delicious Apples", "Yellow Apples", "Perfect Punchy Pineapple")

ggplot(df, aes(Date, Value, group = Fruit)) + 
  geom_line(aes(color = Violation)) +
  scale_color_manual(values = c("grey30", "red")) + 
  scale_x_date(breaks = "month", date_labels = "%b") +
  scale_y_continuous(breaks = seq(0, 0.7, by = 0.05)) + 
  coord_cartesian(ylim = c(-0.25, 0.7)) +
  labs(x = NULL, y = "Value\n") +
  theme_minimal() + 
  theme(panel.grid = element_blank(),
        axis.ticks.x = element_line(),
        #axis.line.x = element_blank(),
        axis.line.y = element_line(), 
        axis.ticks.y = element_line()) + 
  scale_y_continuous(sec.axis = sec_axis(trans=~.*1, name="", labels=lbl, breaks=val))

enter image description here

你介意试一下吗，这样我就能明确了解你的意思？ - Display name
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