如何在x轴上使用分类变量在R中制作散点图？

Question

This question has been asked before but somehow the answers are not helpful for me.

So I have the following data; NW are different forests, which are differentiated in two groups ("Gruppe"), some have been fenced (Z) some have not (KZ). Then for both groups of each forest, I have calculated the biodiversity (Shannon-Index, H) and the Evenness (E).

Here a short section of the data (i am not allowed to upload pictures yet :D)

I would like to create two scatterplots, one for the Shannonindex and one for the Eveness, where on the x-axis the forests (NW) are displayed and the different groups of each forest are compared/next to each other. I tried to do so and the problem is, that R uses the NW as a scale and not each data point is labeled.

I want it to look roughly like this , just not as a barplot, instead, each datapoint should simply be a point.

graph_data3 <- tapply(Shannon$H, list(Shannon$Gruppe, Shannon$NW),sum)

barplot((graph_data3),
        beside = T,
        las = 2,
        ylim = c(0,2),
        xlab = "Naturwald Nummer",
        ylab = "Shannonindex",
        main = "Durchschnittliche Biodiversität (Shannonindex)",
        legend = T,
        args.legend = list (x=90, y=2),
        col = c("paleturquoise3","forestgreen")
)

It seems to be such a dumb question but I just can't fix it. I hope it is understandable what my problem is.

Answer 1

So I created a short dataset to demonstrate what I think you want: let me know if you need me to make modifications.

I used tidyverse for this, which has packages like dplyr and ggplot .

df <- data.frame(ID = rep(c("A", "B", "C"), each = 2), type = rep(c("head", "shoulder")), avg = abs(rnorm(6)))

The data df looks like:

  ID     type        avg
1  A     head 1.05664244
2  A shoulder 0.39070804
3  B     head 1.07129057
4  B shoulder 0.73273048
5  C     head 0.01978039
6  C shoulder 0.60652992

Using this data:

df %>% 
ggplot(aes(x = type, y = avg, group = type, fill = type, color = type)) + 
geom_point() + 
facet_wrap( ~ ID)

Which looks like