为了获得正确的线条颜色，请根据lead计算百分比变化，即，线基于“起始”被着色值。要仅在符号发生变化时添加点，请通过比较pct_change的符号及其lag值，向数据集添加一个指示变量。之后，您可以基于此指示变量过滤数据集，geom_point。另外，我使用replace_na为line_color和sign_change赋值，而不是删除带有NA的行。

library(tidyverse)

t <- economics %>%
  filter(date >= "2013-09-01") %>%
  mutate(
    pct_change = (uempmed / lead(uempmed) - 1) * 100,
    line_color = pct_change < 0,
    sign_change = sign(pct_change) * sign(lag(pct_change))
  ) %>%
  replace_na(list(line_color = FALSE, sign_change = 0))

ggplot(data = t, aes(x = date, y = uempmed)) +
  geom_line(aes(group = 1, color = line_color)) +
  geom_point(data = ~filter(.x, sign_change < 0), shape = 1)

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我们可以这样做：
1.我去掉了NA
1.为点创建逻辑向量sign_switch
1.将色彩美学包裹在ifelse
1.稍微调整了一下，看起来很漂亮

library(tidyverse)

t <- economics %>%
  filter(date >= "2013-09-01") %>%
  mutate(pct_change = (uempmed/lag(uempmed) - 1) * 100 ,
         line_color =  pct_change < 0) %>% 
  drop_na(pct_change) %>% 
  mutate(sign_switch = sign(pct_change) != sign(lag(pct_change))) 
  
ggplot(t, aes(x = date, y = pct_change, group = 1))+
  geom_line(aes(color = ifelse(pct_change < 0, "green", "red"))) +
  labs(color = "")+
  geom_point(data = filter(t, sign_switch & !is.na(sign_switch)), size = 3, color = "red") +
  scale_color_manual(values = c( "green", "red"))+
  scale_x_date(date_breaks = "1 month")+
  theme_minimal()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

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