Question

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

对不起，上面的巨型数据帧代码块。这就是我的工作。请复制粘贴到R Studio中以开始操作。

现在，这已经完成了，我正在尝试获取ggrepel包以标记红线，如下所示。我一直在旋转ggrepel中的旋钮（参数），但无法获得任何漂亮的结果。我希望标签摆脱障碍，并以相同的顺序排列到图表的右侧。我们也可以将标签设为红色吗？

哪些ggrepel参数可以使我到达那里？还是有一种更好的方法可以通过常规ggplot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)

Answer 1

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))

Answer 2

虽然您可以使其与ggrepel一起使用，但我可能会尝试制作辅助 y 轴，并将标签添加为自定义刻度。哪个应该产生相同的结果。它会像这样：

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))

ggplot区域外部（右侧）的ggrepel标签

2 个答案: