添加点大小并向ggplot添加均值

Question

我想通过做两件事来改进我的图表。首先，我想添加一个包含每个变量的平均值的点。其次，我想让点大小成为每个变量中值实际出现次数的函数。如果您对如何使我的图表更清晰有任何其他建议，请毫不犹豫地向我提出。非常感谢！

MD4_long <- MD4 %>%
  pivot_longer(everything())  %>%
  mutate(value = as.numeric(value) - 3,
         value = ifelse(value == 3, NA, value)) %>%
  group_by(name)


ggplot(MD4_long, aes(x = value, y = reorder(name, value))) +
  geom_point(aes (colour = value, size = 3)) +
  scale_y_discrete(labels = ~gsub("^.*_", "", .x)) +
  theme_light()+
  scale_colour_viridis_c(aesthetics = "colour")+
  labs(x = NULL, y = NULL)

structure(list(veränderung_imap_austausch.verstärkt.akteuren = structure(c(3L, 
4L, NA, NA, 3L, 4L, 4L, 3L, NA, NA, NA, NA, NA, NA, NA, 3L, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 5L, NA, 4L, NA, NA, NA, NA, NA, 5L, 4L, NA, NA, NA, 4L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 5L, 3L, 4L, NA, NA, NA, 4L, 4L, 
NA, 1L, 4L, NA, 3L, 4L, 3L, NA, NA, NA, 5L, 5L, 3L, NA, NA, NA, 
5L, NA, 1L, 4L, NA, 4L, NA, 4L, 4L, 4L, 3L, 3L, 3L, NA, 3L, 6L, 
2L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_austausch.verstärkt.ideen = structure(c(5L, 
4L, NA, NA, 3L, 4L, 4L, 2L, NA, NA, NA, NA, NA, NA, NA, 4L, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 5L, NA, 4L, NA, NA, NA, NA, NA, 4L, 4L, NA, NA, NA, 4L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 5L, 4L, 5L, NA, NA, NA, 4L, 4L, 
NA, 3L, 4L, NA, 2L, 4L, 4L, NA, NA, NA, 5L, 5L, 3L, NA, NA, NA, 
5L, NA, 4L, 4L, NA, 4L, NA, 3L, 5L, 4L, 3L, 4L, 4L, NA, 4L, 6L, 
3L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_fortschritt.umsetzung = structure(c(4L, 
4L, NA, NA, 3L, 4L, 6L, 3L, NA, NA, NA, NA, NA, NA, NA, 4L, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 4L, NA, 4L, NA, NA, NA, NA, NA, 5L, 3L, NA, NA, NA, 4L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 4L, 3L, 4L, NA, NA, NA, 4L, 4L, 
NA, 3L, 4L, NA, 3L, 3L, 4L, NA, NA, NA, 5L, 5L, 3L, NA, NA, NA, 
5L, NA, 3L, 3L, NA, 4L, NA, 3L, 5L, 3L, 4L, 2L, 3L, NA, 3L, 6L, 
3L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_neue.strukturen = structure(c(4L, 
4L, NA, NA, 3L, 4L, 4L, 3L, NA, NA, NA, NA, NA, NA, NA, 3L, NA, 
NA, NA, NA, NA, 3L, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 3L, NA, 4L, NA, NA, NA, NA, NA, 5L, 3L, NA, NA, NA, 4L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 4L, 4L, 3L, NA, NA, NA, 4L, 4L, 
NA, 3L, 4L, NA, 3L, 4L, 4L, NA, NA, NA, 5L, 4L, 3L, NA, NA, NA, 
5L, NA, 5L, 3L, NA, 5L, NA, 3L, 5L, 3L, 2L, 2L, 2L, NA, 2L, 6L, 
1L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_zuständigkeiten.klarer = structure(c(3L, 
3L, NA, NA, 3L, 4L, 6L, 3L, NA, NA, NA, NA, NA, NA, NA, 2L, NA, 
NA, NA, NA, NA, 3L, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 3L, NA, 4L, NA, NA, NA, NA, NA, 3L, 3L, NA, NA, NA, 3L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 3L, 3L, 4L, NA, NA, NA, 3L, 3L, 
NA, 4L, 3L, NA, 3L, 3L, 4L, NA, NA, NA, 5L, 4L, 3L, NA, NA, NA, 
5L, NA, 2L, 4L, NA, 3L, NA, 3L, 3L, 3L, 3L, 2L, 2L, NA, 4L, 6L, 
2L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_rollen.klarer = structure(c(3L, 
3L, NA, NA, 3L, 4L, 6L, 2L, NA, NA, NA, NA, NA, NA, NA, 3L, NA, 
NA, NA, NA, NA, 3L, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 4L, NA, 4L, NA, NA, NA, NA, NA, 3L, 1L, NA, NA, NA, 3L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 3L, 3L, 1L, NA, NA, NA, 4L, 3L, 
NA, 4L, 1L, NA, 3L, 4L, 4L, NA, NA, NA, 5L, 4L, 3L, NA, NA, NA, 
5L, NA, 2L, 3L, NA, 3L, NA, 3L, 4L, 3L, 2L, 3L, 3L, NA, 4L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_digitale.lösungen = structure(c(4L, 
4L, NA, NA, 5L, 4L, 4L, 4L, NA, NA, NA, NA, NA, NA, NA, 3L, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, 6L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 5L, NA, 4L, NA, NA, NA, NA, NA, 5L, 4L, NA, NA, NA, 4L, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, 1L, 3L, 4L, NA, NA, NA, 5L, 5L, 
NA, 6L, 5L, NA, 4L, 4L, 4L, NA, NA, NA, 4L, 5L, 6L, NA, NA, NA, 
4L, NA, 1L, 5L, NA, 4L, NA, 4L, 5L, 5L, 4L, 4L, 4L, NA, 4L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_klarheit.prozesse = structure(c(5L, 
3L, NA, NA, 4L, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, 
NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 5L, NA, NA, 5L, 5L, 3L, 4L, 4L, NA, 3L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_weiterent.planung = structure(c(5L, 
3L, NA, NA, 3L, NA, NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, 
NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 4L, NA, NA, 4L, 5L, 3L, 4L, 4L, NA, 3L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_arbeit.relfelktieren = structure(c(4L, 
3L, NA, NA, 4L, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, 
NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 4L, NA, NA, 3L, 5L, 3L, 4L, 4L, NA, 4L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_veranstaltung.ergebnisorientiert = structure(c(6L, 
4L, NA, NA, 5L, NA, NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, 
NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 5L, NA, NA, 5L, 5L, 3L, 3L, 3L, NA, 6L, 6L, 
3L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_motivation = structure(c(5L, 4L, 
NA, NA, 5L, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, NA, 
4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 5L, NA, NA, 5L, 5L, 4L, 4L, 4L, NA, 3L, 6L, 4L
), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_salienz = structure(c(3L, 4L, NA, 
NA, 5L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, 3L, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, 4L, NA, NA, 3L, 4L, 4L, 4L, 3L, NA, 4L, 6L, 3L), .Label = c("Stimme nicht zu", 
"Stimme eher nicht zu", "Stimme teilweise zu", "Stimme zu", "Stimme voll zu", 
"k. A."), class = c("ordered", "factor")), veränderung_imap_interkult.öffnung = structure(c(3L, 
4L, NA, NA, 3L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, 
NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 4L, NA, NA, 3L, 4L, 3L, 3L, 6L, NA, 3L, 6L, 
2L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_austausch.kommunen.verstärkt = structure(c(4L, 
4L, NA, NA, 4L, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5L, NA, NA, NA, NA, NA, 
NA, 6L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 3L, NA, NA, 4L, 2L, 3L, 2L, 6L, NA, 2L, 6L, 
4L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_einarbeitung = structure(c(3L, 3L, 
NA, NA, 5L, NA, NA, 2L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 4L, NA, NA, NA, NA, NA, NA, 
6L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 4L, NA, NA, 4L, 1L, 1L, 2L, 1L, NA, 6L, 6L, 4L
), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor")), veränderung_imap_einsatz.vielfalt.verstärkt = structure(c(3L, 
4L, NA, NA, 3L, NA, NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3L, NA, NA, NA, NA, NA, 
NA, 6L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 3L, NA, NA, 4L, 3L, 3L, 2L, 3L, NA, 6L, 6L, 
2L), .Label = c("Stimme nicht zu", "Stimme eher nicht zu", "Stimme teilweise zu", 
"Stimme zu", "Stimme voll zu", "k. A."), class = c("ordered", 
"factor"))), row.names = c(NA, -114L), class = "data.frame")

Answer 1

您只需要计算每个 category/value 对出现的次数并在 aes(size=) 函数中使用它。您还需要计算每个值的平均值并将第二个 geom_point() 传递给图形。

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyverse)

MD4_long <- MD4 %>%
  pivot_longer(everything())  %>%
  mutate(value = as.numeric(value) - 3,
         value = ifelse(value == 3, NA, value)) %>%
  group_by(name, value) %>% 
  summarise(count = n()) %>% 
  ungroup() %>% 
  group_by(name) %>% 
  mutate(mean = mean(value, na.rm = T)) %>% 
  filter(!is.na(value))
#> `summarise()` has grouped output by 'name'. You can override using the `.groups` argument.
  

ggplot(MD4_long, aes(x = value, y = reorder(name, value))) +
  geom_point(aes (size = count)) +
  geom_point(aes (x = mean), colour = "red") +
  scale_y_discrete(labels = ~gsub("^.*_", "", .x)) +
  theme_light()+
  scale_colour_viridis_c(aesthetics = "colour")+
  labs(x = NULL, y = NULL)

^{由 reprex package (v2.0.0)}

于 2022-04-25 创建

添加点大小并向ggplot添加均值

Addjust pointsize and add mean to ggplot

r

ggplot2