为了让您了解结果的样子，我为您的数据创建了随机数：

A2c <- data.frame(maritalStatus = c("Married", "Married", "Widowed", "Widowed", "Divorced", "Divorced", "Separated", "Separated", "Never married", "Never married"),
                  Geschlecht = c("Männlich", "Weiblich", "Männlich", "Weiblich", "Männlich", "Weiblich", "Männlich","Weiblich", "Männlich", "Weiblich"),
                  nbr_total = sample(1:1500, 10),
                  Adipös = sample(1:600, 10))

随机数据：

maritalStatus Geschlecht nbr_total Adipös
1        Married   Männlich       376    422
2        Married   Weiblich        33    261
3        Widowed   Männlich       989    458
4        Widowed   Weiblich       329    397
5       Divorced   Männlich        41    222
6       Divorced   Weiblich       741    283
7      Separated   Männlich       743    579
8      Separated   Weiblich       236    262
9  Never married   Männlich        85     25
10 Never married   Weiblich       402    145

你应该在geom_col函数中设置position_dodge()来在你的条之间创建空间，就像前面提到的@Basti一样。

library(tidyverse)
A2c%>%
  group_by (maritalStatus, Geschlecht)%>%
  summarise (nbr_total=n(), nbr_adipos=sum(Adipös))%>%
  mutate( adipos_prozent = 100 * nbr_adipos / nbr_total )%>%
  filter (maritalStatus != "Refused")%>%
  ggplot +
  geom_col(aes(x=maritalStatus, y= adipos_prozent, color = Geschlecht, fill=Geschlecht), position = position_dodge(1))+
  theme(axis.text.x = element_text(angle = 90))+
  labs(y = "% Adipöser", x = "Marital Status")

输出：

正如你所看到的，现在的酒吧很好地显示。（不要看数字，他们是假的）