ggplot2中的迷你图

Question

Tufte Sparklines(如他的美丽证据所示)已作为YaleToolkit的一部分在基础图形中复制,并由于这个问题而进一步完善.迷彩线也在格子中完成,作为我的小方案项目Tufte in R的一部分(自我推销并非预期).我现在的目标是在ggplot2中复制Tufte 迷你图.有一些脚本在Gist上浮动,也作为对SO的这个问题的回复,但没有一个为制作可复制的迷你图集提供了坚实的基础.

现在,我希望那些多个迷你图看起来像这样(它是在基本图形中完成的,代码在这里可用) - 点代表最大/最小值,右端的数字是特定时间序列和灰色带的最终值显示粗略的分位数范围:

我不是很远,但我坚持最小/最大值和标签的分配:

library(ggplot2)
library(ggthemes)
library(dplyr)
library(reshape)
library(RCurl)
dd <- read.csv(text =
  getURL("https://gist.githubusercontent.com/GeekOnAcid/da022affd36310c96cd4/raw/9c2ac2b033979fcf14a8d9b2e3e390a4bcc6f0e3/us_nr_of_crimes_1960_2014.csv"))
d <- melt(dd, id="Year")
names(d) <- c("Year","Crime.Type","Crime.Rate")
dd <- group_by(d, Crime.Type) %>% 
  mutate(color = (min(Crime.Rate) == Crime.Rate | max(Crime.Rate) == Crime.Rate))
ggplot(dd, aes(x=Year, y=Crime.Rate)) + 
  facet_grid(Crime.Type ~ ., scales = "free_y") + 
  geom_line(size=0.3) + geom_point(aes(color = color)) + 
  scale_color_manual(values = c(NA, "red"), guide=F) +
  theme_tufte(base_size = 15) + 
  theme(axis.title=element_blank(), 
        axis.text.y = element_blank(), axis.ticks = element_blank()) +
  theme(strip.text.y = element_text(angle = 0, vjust=0.2, hjust=0)) 

Answer 1

以下是获取单个彩色点的一种方法,以及三组标签和阴影四分位数范围:

# Calculate the min and max values, which.min returns the first (like your example):
mins <- group_by(d, Crime.Type) %>% slice(which.min(Crime.Rate))
maxs <- group_by(d, Crime.Type) %>% slice(which.max(Crime.Rate))
ends <- group_by(d, Crime.Type) %>% filter(Year == max(Year))
quarts <- d %>%
  group_by(Crime.Type) %>%
  summarize(quart1 = quantile(Crime.Rate, 0.25),
            quart2 = quantile(Crime.Rate, 0.75)) %>%
  right_join(d)

ggplot(d, aes(x=Year, y=Crime.Rate)) + 
  facet_grid(Crime.Type ~ ., scales = "free_y") + 
  geom_ribbon(data = quarts, aes(ymin = quart1, ymax = quart2), fill = 'grey90') +
  geom_line(size=0.3) +
  geom_point(data = mins, col = 'blue') +
  geom_text(data = mins, aes(label = Crime.Rate), vjust = -1) +
  geom_point(data = maxs, col = 'red') +
  geom_text(data = maxs, aes(label = Crime.Rate), vjust = 2) +
  geom_text(data = ends, aes(label = Crime.Rate), hjust = 0) +
  geom_text(data = ends, aes(label = Crime.Type), hjust = 0, nudge_x = 5) +
  expand_limits(x = max(d$Year) + (0.25 * (max(d$Year) - min(d$Year)))) +
  scale_x_continuous(breaks = seq(1960, 2010, 10)) +
  scale_y_continuous(expand = c(0.1, 0)) +
  theme_tufte(base_size = 15) +
  theme(axis.title=element_blank(),
        axis.text.y = element_blank(), 
        axis.ticks = element_blank(),
        strip.text = element_blank())

我假设你不想要这里的传奇.几乎可以肯定,通过合并一些data.frames可以使事情变得更简洁,但是多个geom调用似乎在这里最简单.