ggrepel labels outside (to the right) of ggplot area

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

Sorry for the giant data frame code block above. It's what I'm working with. Please copy paste it into R Studio to get things started.

Now that that's done I'm trying to get the ggrepel package to label the red lines as shown below. I've been spinning the knobs (arguments) in ggrepel but can't get anything pretty. I want the labels to get out of the way, and get to the right of the graph, in the same order the lines are ranked. Can we make the labels red as well?

What ggrepel arguments will get me there? Or is there a better way to do this with normal ggplot?

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)

https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html#limit-labels-to-a-specific-area — Jon Spring, May 07 '19 at 15:05
@Jon Spring I added the `xlim = as.Date(c("2019-04-01", "2019-08-01"))` argument but it doesn't seem to change anything. Thanks for the tip though. — Display name, May 07 '19 at 15:13

Jon Spring · Accepted Answer · 2019-05-07T17:28:57.267

9

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))

edited May 07 '19 at 17:28

answered May 07 '19 at 17:22

Jon Spring

55,165
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This is a great trick, and it works for https://stackoverflow.com/q/68278953/3358272 as well. One thought: instead of `data = df %>% filter(Violation==TRUE)`, one can use `data = ~ filter(., Violation==TRUE)`. The benefit is that it uses the data as it was passed to `ggplot`; without it, if you change the original data from (say) `df` to `df2` and forget to change all `data=` references that use `df`, then you may see some perplexing results; with `data=~...`, that can't happen. – r2evans Jul 07 '21 at 12:54
(JonSpring, I recognize this is code copied from the question, just thought this would be a good place to make the mention.) – r2evans Jul 07 '21 at 12:55
@r2evans, And what should one do to place the labels not on the right, but above the plot? – ramen Dec 15 '21 at 14:54

Oka · Answer 2 · 2019-05-07T18:23:34.343

While you can make it work with ggrepel, I probably would try to make a secondary y-axis and add the labels as custom ticks to it. Which should yield the same result. It would go somehow like this:

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))

Do you mind attempting that so I can see exactly what you mean? — Display name, May 07 '19 at 15:14

ggrepel labels outside (to the right) of ggplot area

2 Answers2

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