Question

我想绘制背对背的条形图，但是每侧都在一个独立的轴上。我可以通过取一组负值来将它们背对背绘制，但这使它们处于相同的访问方式，并且因为p值较小，所以它们的条形几乎无法表示。

library(ggplot2)
df <-structure(list(Description = c("a", "b", "c", "d", "e", "f", 
    "g", "h", "a", "b", "c", "d", "e", "f", "g", "h"), test = c("size", 
    "size", "size", "size", "size", "size", "size", "size", "p", 
    "p", "p", "p", "p", "p", "p", "p"), value = c(0.1, 0.1, 0.125, 
    0.1, 0.075, 0.1, 0.075, 0.125, 0.000230705311441713, 0.000314488619269942, 
    0.00106639822095382, 0.00108290238851994, 0.00114723539549198, 
    0.00160204850890075, 0.0019276388745184, 0.00320371567547557)), .Names = c("Description", 
    "test", "value"), row.names = c(NA, -16L), class = "data.frame")

df$value[df$test == 'p'] <- -(df$value[df$test == 'p'])

ggplot(df, aes(x=Description, y= value, group=test, fill=test)) + geom_col() +coord_flip()

理想情况下，我希望每个组都在独立的轴上，以使条形点在零点处（在绘图区域的中间）相交，但在本示例中，ylim的比例不同c（0，0.0035）

Answer 1

您可以通过以下方式进行操作：调整切面以消除切面之间的间距：

ggplot(df, aes(x=Description, y= value, fill=test)) + 
    facet_wrap(~ test, scales = "free_x") + 
    geom_col() + 
    coord_flip() +
    scale_y_continuous(expand = c(0, 0)) +
    theme(panel.spacing.x = unit(0, "mm"))

这可能会导致轴标签出现一些问题，要解决这些问题有些棘手。在这种情况下，在小平面之间保留一些空间可能会更容易，但要以没有在中间相遇为代价。

输出：

PS：您还可以使用以下方法删除负轴标签：

scale_y_continuous(
    expand = c(0, 0), 
    labels = function(x) signif(abs(x), 3)
)

Answer 2

@Marius解决方案比此解决方案更容易，但这可以独立控制每个图形。

我必须删除p1右侧和p2左侧的绘图边距。由于某种原因，在左边距有填充，因此需要-3.5pt使其平齐，不确定在所有图上是否一致。另一个手动操作是更改一个轴上的中断，这样就不会在彼此的顶部绘制0。

我也不需要只使用<section class="container"> <form action="" class="form"> <div class="section-bio"> <div class="section-header section-header--nouvelle-section"> <button type="button" class="btn btn-nouvelle-section">Add</button> </div> </div> </form> </section>

来否定p值

scale_y_reverse

我也使用过p1 <- ggplot(df[df$test == 'p',], aes(x=Description, y= value)) + geom_col(fill='red') + theme_minimal()+ coord_flip() + scale_y_reverse(name= "axis1",expand = expand_scale(mult= c(c(0.05,0)))) + theme(panel.spacing.x = unit(0, "mm")) +theme(plot.margin = unit(c(5.5, 0, 5.5, 5.5), "pt")) p2 <- ggplot(df[df$test != 'p',], aes(x=Description, y= value)) + geom_col(fill='blue') + scale_y_continuous(name = "axis2", breaks = seq(0.025, 0.125, 0.025) ,expand = expand_scale(mult= c(c(0,0.05)))) + coord_flip() + theme(panel.spacing.x = unit(0, "mm"))+ theme_minimal() + theme(axis.title.y=element_blank(), axis.text.y=element_blank(), axis.line.y = element_blank(), axis.ticks.y=element_blank(), plot.margin = unit(c(5.5, 5.5, 5.5, -3.5), "pt")) grid.newpage() grid.draw(cbind(ggplotGrob(p1), ggplotGrob(p2), size = "last"))，但这只是出于我的审美偏好。

Answer 3

我已经根据我的需要调整了 this elegant solution。为张凌云点赞。

library(dplyr)
library(ggplot2)

set.seed(123)
ten_positive_rand_numbers <- abs(rnorm(10)) + 0.1
the_prob <- ten_positive_rand_numbers / sum(ten_positive_rand_numbers)

fk_data <- data.frame(job_type = sample(LETTERS[1:10], 1000, 
                                        replace = TRUE, prob = the_prob),
                      gender = sample(c("Male", "Female"), 1000, 
                                      replace = TRUE))

# prepare data for plotting
plotting_df <-
  fk_data %>% 
  group_by(job_type, gender) %>% 
  summarise(Freq = n()) %>% 
  # a trick!
  mutate(Freq = if_else(gender == "Male", -Freq, Freq))
## find the order
temp_df <-
  plotting_df %>% 
  filter(gender == "Female") %>% 
  arrange(Freq)
the_order <- temp_df$job_type

# plot
p <- 
  plotting_df %>% 
  ggplot(aes(x = job_type, y = Freq, group = gender, fill = gender)) +
  geom_bar(stat = "identity", width = 0.75) +
  coord_flip() +
  scale_x_discrete(limits = the_order) +
  # another trick!
  scale_y_continuous(breaks = seq(-150, 150, 50), 
                     labels = abs(seq(-150, 150, 50))) +
  labs(x = "Job type", y = "Count", title = "Back-to-back bar chart") +
  theme(legend.position = "bottom",
        legend.title = element_blank(),
        plot.title = element_text(hjust = 0.5),
        panel.background = element_rect(fill =  "grey90")) +
  # reverse the order of items in legend
  # guides(fill = guide_legend(reverse = TRUE)) +
  # change the default colors of bars
  scale_fill_manual(values = c("red", "blue"),
                    name = "",
                    breaks = c("Male", "Female"),
                    labels = c("Male", "Female")) 
print(p)

可以通过其他小细节进行改进，包括 geom_hline(yintercept = 0, colour = "black")。

具有独立轴R的背对背条形图

3 个答案: