geom_point，手动颜色和磅值

Question

我要

将 "energetic level" 颜色的类别分配给较高级别的红色阴影和较低级别的绿色阴影。
对类别"functional level"每个点的SIZE进行排序，顺序如下low_TL、inter_TL、Myrmecophage、mesocarnivores、large_species、apex carnivores、megafauna （分配给 "low_TL" 较小的点大小和最大的巨型动物）。

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

你是说类似的意思吗？

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))

所以你唯一需要做的就是重新调整你的 functional_level，然后你可以将它映射到点的大小（ggplot 会警告你）并将 energetic_level 映射到点的颜色。

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))

geom_point，手动颜色和磅值

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