r - geom_point，手动颜色和点大小

Question

我想要

1. 将“能量级别”颜色类别分配给较高级别的红色色调，以及较低级别的绿色色调颜色。
2. 按以下顺序对“功能级别”类别中每个点的大小进行排序:low_TL、inter_TL、Myrmecophage、mesocarnivores、large_species、apex carnivores、megafauna(将较小的点大小分配给“low_TL”，将最大的点分配给megafauna) )。

Dataset<-read.csv(file= "meat.csv", header= TRUE, sep= ";" )
library(ggplot2)
options(scipen=999)
theme_set(theme_bw())
gg <- ggplot(Dataset, aes(x=specie, y=responserate))+ 
  geom_point(aes(col=energetic_level, size=functional_level)) + 
  geom_smooth(method="loess", se=F) + 
  labs(subtitle="Bushmeat trade", 
       y="Response rate", 
       x="Body mass")
gg+scale_color_gradient(low="green", high="red", space ="Lab" )
plot(gg)

specie	responserate	energetic_level	functional_level
AAOtol_cras	7.2	2.4	low_TL
ABMiop_tal	1.6	3	low_TL
ACCLep_cap	14.4	3	low_TL
BAThry_swin	20	2.8	low_TL
BBPhil_mont	20.8	2.6	low_TL
BCChlor_cyn	72.8	3.2	low_TL
BDCerc_mit	5.6	2.5	low_TL
CCHys_afri	23.2	2.8	low_TL
FCan_mes	1.6	4.9	inter_TL
PTrag_oryx	16	2.7	low_TL
CBCivet_civ	43.2	4.4	inter_TL
DSylv_grim	48	3.1	inter_TL
IOryct_afer	11.2	5	Myrmecophage
ADGenet_gen	0	5.8	mesocarnivores 
CALept_serv	0.8	5.8	mesocarnivores 
ELyc_pict	0.8	5.8	mesocarnivores 
GTrag_scri	100	3	 large_species 
JRed_aru	100	3	large_species 
MPota_larv	100	3.2	large_species 
OHipp_eq	14.4	3	large_species 
QSync_caf	81.6	3	 large_species 
HPant_pa	18.4	6	apex carnivores 
LCroc_croc	0	6	apex carnivores 
NPant_le	0	6	apex carnivores 
RHipp_amph	22.4	3	megafauna
SLox_afric	1.6	3	megafauna

下图是我要更改点颜色和名称

Answer 1

你的意思是这样的吗？

library(tidyverse)

dat %>%
  mutate(
    functional_level = fct_relevel(functional_level, 
                                   c("low_TL", "inter_TL", "Myrmecophage", 
                                     "mesocarnivores",    "large_species", 
                                     "apex_carnivores",   "megafauna"
                                     )
                                   )
    ) %>%
  ggplot(aes(x = specie, y = responserate, 
             colour = energetic_level, size = functional_level)) +
  geom_point(alpha = .9) +
  scale_colour_continuous(low = '#32CD32', high = '#ff4040') +
  labs(x = 'Species', y = 'Response rate') +
  ggthemes::theme_few() +
  theme(axis.text.x = element_text(angle = 90, vjust = .5))

因此，您唯一要做的就是重新调整您的功能级别，然后您可以将其映射到点大小(ggplot 会警告您想法)并映射能量级别转化为点的颜色。

数据:

structure(list(specie = structure(c(1L, 2L, 3L, 5L, 6L, 7L, 8L, 
11L, 14L, 23L, 10L, 12L, 17L, 4L, 9L, 13L, 15L, 18L, 20L, 22L, 
24L, 16L, 19L, 21L, 25L, 26L), .Label = c("AAOtol_cras", "ABMiop_tal", 
"ACCLep_cap", "ADGenet_gen", "BAThry_swin", "BBPhil_mont", "BCChlor_cyn", 
"BDCerc_mit", "CALept_serv", "CBCivet_civ", "CCHys_afri", "DSylv_grim", 
"ELyc_pict", "FCan_mes", "GTrag_scri", "HPant_pa", "IOryct_afer", 
"JRed_aru", "LCroc_croc", "MPota_larv", "NPant_le", "OHipp_eq", 
"PTrag_oryx", "QSync_caf", "RHipp_amph", "SLox_afric"), class = "factor"), 
    responserate = c(7.2, 1.6, 14.4, 20, 20.8, 72.8, 5.6, 23.2, 
    1.6, 16, 43.2, 48, 11.2, 0, 0.8, 0.8, 100, 100, 100, 14.4, 
    81.6, 18.4, 0, 0, 22.4, 1.6), energetic_level = c(2.4, 3, 
    3, 2.8, 2.6, 3.2, 2.5, 2.8, 4.9, 2.7, 4.4, 3.1, 5, 5.8, 5.8, 
    5.8, 3, 3, 3.2, 3, 3, 6, 6, 6, 3, 3), functional_level = structure(c(4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 2L, 2L, 7L, 6L, 6L, 6L, 
    3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 5L, 5L), .Label = c("apex_carnivores", 
    "inter_TL", "large_species", "low_TL", "megafauna", "mesocarnivores", 
    "Myrmecophage"), class = "factor")), class = "data.frame", row.names = c(NA, 
-26L))