ggplot 区域外(右侧)的 ggrepel 标签

Jas*_*ter 2 r ggplot2 ggrepel

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
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抱歉上面的巨型数据框代码块。这就是我正在处理的。请将其复制粘贴到 R Studio 中以开始工作。

既然已经完成,我正在尝试让ggrepel包裹标记红线,如下所示。我一直在旋转旋钮(参数),ggrepel但无法得到任何漂亮的东西。我希望标签不碍事,并到达图表的右侧,按照线条排列的相同顺序。我们也可以将标签设为红色吗?

什么ggrepel论据会让我到达那里?或者有没有更好的方法来使用普通的 ggplot 来做到这一点?

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)
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Ggrepel 标签

Jon*_*ing 5

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))
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在此处输入图片说明