更改绘图框的宽度和/或它们之间的空间

发布于 2025-02-01 04:11:39 字数 1363 浏览 2 评论 0原文

我已经对数据进行了分组，我想使用r的 plotly 软件包将其绘制为一组框图，并控制框的宽度和/或主题之间的空间。

以下是数据：

set.seed(1)
df <- data.frame(type = c(rep("t1", 1000), rep("t2", 1000), rep("t3", 1000), rep("t4", 1000), rep("t5", 1000), rep("t6", 1000)),
                 age = rep(c(rep("y", 500),rep("o", 500)), 6),
                 value = rep(c(runif(500, 5, 10), runif(500, 7.5, 12.5)), 6),
                 stringsAsFactors = F)
df$age <- factor(df$age, levels = c("y", "o"), ordered = T)

以下plotly's tutorial 这是我如何绘制它：

library(plotly)
library(dplyr)
plot_ly(x = df$type, y = df$value, name = df$age, color = df$type, type = 'box',showlegend = F) %>%
  layout(yaxis=list(title="Diversity"),boxmode='group')

给出：

盒子出来太窄的地方以及相同类型的框之间的空间以及不同的类型 s之间的空间大的。

知道如何更改框宽度和/或空间吗？

根据 a>，在python boxgap和boxgroupgap控制这些方面。

原文

I have grouped data which I want to plot as a group of box plots using R's plotly package, and control the width of the boxes and/or the space between theme.

Here are the data:

set.seed(1)
df <- data.frame(type = c(rep("t1", 1000), rep("t2", 1000), rep("t3", 1000), rep("t4", 1000), rep("t5", 1000), rep("t6", 1000)),
                 age = rep(c(rep("y", 500),rep("o", 500)), 6),
                 value = rep(c(runif(500, 5, 10), runif(500, 7.5, 12.5)), 6),
                 stringsAsFactors = F)
df$age <- factor(df$age, levels = c("y", "o"), ordered = T)

Following plotly's tutorial this is how I'm plotting it:

library(plotly)
library(dplyr)
plot_ly(x = df$type, y = df$value, name = df$age, color = df$type, type = 'box',showlegend = F) %>%
  layout(yaxis=list(title="Diversity"),boxmode='group')

Which gives:

Where the boxes come out too narrow and the space both between boxes of the same type as well as the space between the different types are big.

Any idea how to change the box widths and/or the spaces?

According to this post, in python the boxgap and boxgroupgap control these aspects.

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调妓 2025-02-08 04:11:39

类似于Python版本，布局参数为被记录为在这里可以作为参数更改为功能布局：

plot_ly(x = df$type, y = df$value, name = df$age, color = df$type,
  type = "box", showlegend = F) %>%
  layout(yaxis = list(title = "Diversity"),
   boxmode = "group", boxgap = 0, boxgroupgap = 0
  )

Analogous to the python version, layout parameters as being documented here can be changed as arguments of the function layout:

plot_ly(x = df$type, y = df$value, name = df$age, color = df$type,
  type = "box", showlegend = F) %>%
  layout(yaxis = list(title = "Diversity"),
   boxmode = "group", boxgap = 0, boxgroupgap = 0
  )

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奢望 2025-02-08 04:11:39

一种选择是使用连续的X轴。在这里使用ggplotly：

# convert factors to numbers
df$itype <- as.numeric (factor (df$type))
sc <- scale (unique (as.numeric (factor (df$age))))
df$iage <- sc[as.numeric (factor (df$age))] * .3

# plot
gg <- 
  ggplot (df, aes (x=itype+iage, y=value, color=type, group=itype+iage)) + 
  geom_boxplot() + 
  scale_x_continuous(labels = levels (factor (df$type)), breaks = 1:length (levels (factor (df$type)))) +
  labs (x="", y="Diversity")


ggplotly (gg) %>%
  layout(boxgroupgap = 0, boxgap=0)

plot

One alternative is to use a continuous x-axis. Here with ggplotly instead:

# convert factors to numbers
df$itype <- as.numeric (factor (df$type))
sc <- scale (unique (as.numeric (factor (df$age))))
df$iage <- sc[as.numeric (factor (df$age))] * .3

# plot
gg <- 
  ggplot (df, aes (x=itype+iage, y=value, color=type, group=itype+iage)) + 
  geom_boxplot() + 
  scale_x_continuous(labels = levels (factor (df$type)), breaks = 1:length (levels (factor (df$type)))) +
  labs (x="", y="Diversity")


ggplotly (gg) %>%
  layout(boxgroupgap = 0, boxgap=0)

plot

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