如何使用小平面网格和位置闪避对图中的点范围进行排序和着色?

时间:2018-12-18 13:43:17

标签: r sorting ggplot2 colors facet

我有两组固定效果模型的刻面网格图。在第一组中,我想抑制控制变量(显示为绿色)。在第二组中,我想显示模型中是否有一个带有position_dodgev()的控制变量。

到目前为止,我已经弄清楚了这段代码:

library(ggplot2)
library(ggstance)
ggplot(mf, aes(fill=mn)) +
  geom_vline(xintercept=0) +
  geom_pointrangeh(aes(y=mn, x=coef, group=cv, color=cv, 
                       xmin=coef - se*1.96, xmax=coef + se*1.96),
                   position=position_dodgev(.5),
                   show.legend=FALSE) +
  scale_color_manual(values=c("green", "red", "green", "red")) +
  facet_grid(gr ~ ., scales="free", space="free")

这给了我这个:

enter image description here

但是,在模型1中,解释变量是重复的,而在组2的模型中,解释变量并不总是在顶部。

我实际上想看这样的情节(照片购物):

enter image description here

ggplot()怎么可能?


数据

mf <- structure(list(coef = c(3.025, 0.762499999999999, -1.44237073106609, 
-0.125042600081792, -0.689108910891089, 2.64264321029771, 2.64264321029771
), se = c(5.26319027539381, 3.34469904756018, 2.02098677878979, 
2.02098677878979, 2.02098677878979, 0.763989041657158, 0.763989041657158
), mn = structure(c(1L, 1L, 2L, 2L, 3L, 4L, 4L), .Label = c("Model 2c", 
"Model 2b", "Model 2a", "Model 1"), class = "factor"), gr = c(2, 
2, 2, 2, 2, 1, 1), cv = structure(c(2L, 1L, 2L, 3L, 2L, 2L, 3L
), .Label = c("gear", "vs", "disp"), class = "factor")), row.names = c("vs", 
"gear", "vs1", "disp", "1", "11", "2"), class = "data.frame")

1 个答案:

答案 0 :(得分:2)

对数据进行一些小的更改将有助于修复该图。首先,我们可以删除模型1的重复行。其次,简历颜色更改顺序的问题是,模型2a和2b之间的控制变量不同。我们可以创建一个指标列,以简单地说出该行是否为控制变量,然后使用它来为图着色。

library(tidyverse)
library(ggstance)

mf %>% 
  #remove the dupe from Model 1
  filter(!(mn == "Model 1" & cv == "disp")) %>% 
  #create an indicator column for control variables
  mutate(Control = cv == "vs") %>% 
  ggplot(aes(fill=mn)) +
  geom_vline(xintercept=0) +
  #group and color using our new indicator variable
  geom_pointrangeh(aes(y=mn, x=coef, group=Control, color=Control, 
                       xmin=coef - se*1.96, xmax=coef + se*1.96),
                   position=position_dodgev(.5),
                   show.legend=FALSE) +
  scale_color_manual(values=c("green", "red", "green", "red")) +
  facet_grid(gr ~ ., scales="free", space="free")

final plot