英文:
How to map two continuous variables to the height and width of boxes in ggplot?
问题
我能帮你翻译这个内容。
英文:
I want to create a plot with two continuous variables (v1 and v2) and one categorical variable (ex levels A,B,C,D). The plot should show a matrix of proportions. The categorical variable should be on the x-axis and each column should have two boxes (v1 and v2) representing the proportion of each continuous variable within that category (Within A, v1/(v1+v2) then v2/(v1+v2)). The width of the columns should represent the proportion of the total that is within that category (v1+v2 for A divided by the sum of all v1 and v2)
It should look like a heatmap but with the variable type (v1 or v2) mapped to color and the height and width of the boxes mapped as described above.
Using a stacked bar graph approach worked well and is close to what I want but there is horizontal space between the bars. Since I'm already using the width aesthetic to map the proportion within each category I wasn't able to eliminate this space.
Alternatively I tried to use geom_tile but that suffered from the same space issue and didn't result in all bars with a height of 1.
The closest solution I have found is: https://stackoverflow.com/questions/66996598/ggplot2-heatmap-with-tile-height-and-width-as-aes
However in that example they have a categorical variable on both X and Y axes which is a little different than my case.
Reproducible example for reference:
library(tidyverse)cat <- c("A","B","C","D")v1 <- c(1,3,6,2)v2 <- c(3,3,10,1)df <- data.frame(cat,v1,v2)df <- df %>%group_by(cat) %>%mutate(sum.cat = sum(v1,v2)) %>%mutate(prop.v1 = v1/sum.cat) %>%ungroup() %>%mutate(prop.cat = sum.cat/sum(v1,v2)) %>%mutate(sum.tot = sum(sum.cat)) %>%mutate(prop.v2 = 1-prop.v1) %>%pivot_longer(cols = c(5,8), names_to = "prop.v.type", values_to = "prop.v")ggplot(df,aes(cat,prop.v, fill = prop.v.type))+geom_bar(position = "stack", stat = "identity",aes(width=prop.cat))ggplot(df,aes(x=cat, y=prop.v, fill = prop.v.type))+geom_tile(aes(width=prop.cat,height=prop.v))
Thanks in advance!
答案1
得分: 1
它可以通过对x轴值进行小小的修改来实现。我所做的是根据 prop.cat 计算 x 轴值，然后将 cat 标签分配给与每个柱位置相对应的匹配值。这将使得 x 轴成为连续值，以便 `width` 美学现在可以匹配轴值。cat <- c("A","B","C","D")v1 <- c(1,3,6,2)v2 <- c(3,3,10,1)df <- data.frame(cat,v1,v2)df <- df %>%group_by(cat) %>%mutate(sum.cat = sum(v1,v2)) %>%mutate(prop.v1 = v1/sum.cat) %>%ungroup() %>%mutate(prop.cat = sum.cat/sum(v1,v2)) %>%mutate(sum.tot = sum(sum.cat)) %>%mutate(prop.v2 = 1-prop.v1) %>%pivot_longer(cols = c(5,8), names_to = "prop.v.type", values_to = "prop.v")# 这里我计算了每个 cat 的 x 轴位置df_revised <- df |>group_by(cat) |>mutate(prop.cat_cumsum = if_else(row_number() == 1, prop.cat, 0)) |>ungroup() |>mutate(prop.cat_cumsum = cumsum(prop.cat_cumsum)) |>mutate(x_axis_value = 0 + prop.cat_cumsum - prop.cat / 2)# 因为 cat 和值在顺序上是对齐的，所以我只是将它们提取出来x_asix_breaks <- unique(df_revised$x_axis_value)x_asix_labels <- unique(df_revised$cat)# 现在我绘制它们以测试它们是否匹配得很好。ggplot(df_revised,aes(x = x_axis_value, y = prop.v, fill = prop.v.type))+geom_bar(position = "stack", stat = "identity",aes(width = prop.cat)) +scale_x_continuous(breaks = x_asix_breaks, expand = c(0, 0)) +scale_y_continuous(expand = c(0, 0))#> 警告 in geom_bar(position = "stack", stat = "identity", aes(width = prop.cat)): Ignoring unknown aesthetics: width
好的，它按预期工作了。现在只需要将正确的 cat 标签分配给 x 轴，并在柱状图上添加一条线框，以便更容易区分柱之间的差异。
ggplot(df_revised,aes(x = x_axis_value, y = prop.v, fill = prop.v.type))+geom_bar(position = "stack", stat = "identity",color = "black", aes(width = prop.cat)) +scale_x_continuous(breaks = x_asix_breaks, labels = x_asix_labels,expand = c(0, 0)) +scale_y_continuous(expand = c(0, 0))#> 警告 in geom_bar(position = "stack", stat = "identity", color = "black", : Ignoring unknown aesthetics: width
创建于2023-05-18，使用 reprex v2.0.2
<details><summary>英文:</summary>It can be done with a little hack to the x-axis values. What I did is I calculate the x-Axis value based on the prop.cat the assign the cat labels to matched values of each bar position corresponded to each cat. This will make the x-Axis continous values so that the `width` aes now able to matched Axis values.``` rlibrary(tidyverse)cat <- c("A","B","C","D")v1 <- c(1,3,6,2)v2 <- c(3,3,10,1)df <- data.frame(cat,v1,v2)df <- df %>%group_by(cat) %>%mutate(sum.cat = sum(v1,v2)) %>%mutate(prop.v1 = v1/sum.cat) %>%ungroup() %>%mutate(prop.cat = sum.cat/sum(v1,v2)) %>%mutate(sum.tot = sum(sum.cat)) %>%mutate(prop.v2 = 1-prop.v1) %>%pivot_longer(cols = c(5,8), names_to = "prop.v.type", values_to = "prop.v")# Here I calculate the x_axis position for each catdf_revised <- df |>group_by(cat) |>mutate(prop.cat_cumsum = if_else(row_number() == 1, prop.cat, 0)) |>ungroup() |>mutate(prop.cat_cumsum = cumsum(prop.cat_cumsum)) |>mutate(x_axis_value = 0 + prop.cat_cumsum - prop.cat / 2)# As the cat & the values are well aligned in order so I just extract themx_asix_breaks <- unique(df_revised$x_axis_value)x_asix_labels <- unique(df_revised$cat)# Now I plot them to test if it fit well.ggplot(df_revised,aes(x = x_axis_value, y = prop.v, fill = prop.v.type))+geom_bar(position = "stack", stat = "identity",aes(width = prop.cat)) +scale_x_continuous(breaks = x_asix_breaks, expand = c(0, 0)) +scale_y_continuous(expand = c(0, 0))#> Warning in geom_bar(position = "stack", stat = "identity", aes(width =#> prop.cat)): Ignoring unknown aesthetics: width
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Ok it worked as expected. Now just need to assign the proper cat labels to the x-Axis and add a line border to the bar so it easy to distinct between bars.
ggplot(df_revised,aes(x = x_axis_value, y = prop.v, fill = prop.v.type))+geom_bar(position = "stack", stat = "identity",color = "black", aes(width = prop.cat)) +scale_x_continuous(breaks = x_asix_breaks, labels = x_asix_labels,expand = c(0, 0)) +scale_y_continuous(expand = c(0, 0))#> Warning in geom_bar(position = "stack", stat = "identity", color = "black", :#> Ignoring unknown aesthetics: width
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<sup>Created on 2023-05-18 with reprex v2.0.2</sup>
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