如何通过折线图将y轴上的所有点连接到同一组ggplot的x轴点

Question

I'm new to R and been playing around with some ggplot logic for a friend. Where I'm trying to connect all points on a Y-axis to the points on the x-axis that belong to the same group. But my Y-axis points are also being connected which I don't want

ggplot(data=data, aes(x= Letter_coding, y= Lectin_C, group=Island, 
color = Island)) +
geom_line()+
geom_point() 

Something like this.

Edit 1:

Sample data:

Organism            Letter_coding   Island          Lectin_C    
Coral (Pocillopora)     A           FlintMos3_2     77.42858683 
Coral (Pocillopora)     A           FlintMos3_2     206.5272288 
C-A (Red Algae)         B           FlintMos3_2     201.8928979 
Coral (Porites)         C           FlintMos3_5     100.0270507 
Coral (Porites)         C           FlintMos3_5     116.1427727 
C-A (Red Algae)         D           FlintMos3_5     113.2093909 
Coral (Porites)         E           FlintMos5_2     148.1921679 
C-C                     F           FlintMos5_2     140.8645009 
Coral (Porites)         E           FlintMos5_2     120.3082097 
Coral (Porites)         G           MaldInv         259.2967552 
Coral (Porites)         G           MaldInv         238.4524644 
C-A (CCA)               H           MaldInv         58.82896626 
Coral (Porites)         C           StarTent        137.056068  
Coral (Porites)         C           StarTent        107.1444611 
C-A (Red Algae)         D           StarTent        120.4673744 
Coral (Porites)         G           VostMos_2       162.9043976 
Coral (Porites)         G           VostMos_2       202.3885923 
C-A (CCA)               H           VostMos_2       144.3439106
Coral (Porites)         I           VostMos_4       309.4388754 
Coral (Porites)         I           VostMos_4       276.9731826 
C-C                     J           VostMos_4       170.3126185
Coral (Montipora)       I           VostMos_4       181.4586178 
Coral (Montipora)       I           VostMos_4       158.7184731 

Any help would be appreciated. Thanks

Answer 1

It seems that you want to group data by island and then connect the Coral organisms to the C_ organisms by lines. You can do this in a straightforward way by using several functions from tidyverse as shown below.

#
# Load tidyverse which includes the ggplot2, dplyr, and stringr packages  
#
   library(tidyverse)
#
#  Data should be in island_data
#  Separate Coral and C_ organisms
#
   coral <- island_data %>% filter(str_detect(Organism, "Coral"))
   C_dash <- island_data %>% filter(str_detect(Organism, "C-"))
#
#   Make data for line segment ends by joining coral and C_ data
#
   plt_data <- left_join(coral, C_dash, by = "Island", suffix = c("","_C") ) 
   sp <-  plt_data %>% ggplot(aes( color = Island)) +  
          geom_segment(aes( x= Letter_coding, y = Lectin_C, xend = Letter_coding_C, yend = Lectin_C_C), size=1.1) +
           geom_point(aes(x= Letter_coding, y=Lectin_C), size = 4) +
           geom_point(aes(x = Letter_coding_C, y = Lectin_C_C), size = 4)

   plot(sp)

This gives the plot

Answer 2

I will state at the outset that this answer is not a direct answer to your question. I think you need to address two issues.

First: what is the rationale for connecting the points using lines? Generally, we do this when there is change over time. That is not apparent in your data.

Second: what is it about the data that you want to convey in the chart? I see a dependent variable, Lectin_C , and two categories: Island and Organism . The letter coding I do not fully understand. So what's interesting? Is it Lectin_C content by island, or by organism, or perhaps by both?

If I were plotting this data, I'd plot the values as jittered points, colour by one of island or organism and split the data into groups (facets) by organism or island. As an example, if we are primarily interested in Lectin_C by Organism :

library(tidyverse)
coral_data %>% 
ggplot(aes(Letter_coding, Lectin_C)) + 
  geom_jitter(aes(color = Island)) + 
  facet_wrap(~Organism) + theme_bw()

Or conversely, if we want to look at Lectin_C by Island: