Nu Cd_ppm pH
1 0.024 5.51
2 0.023 5.53
3 0.024 5.60
4 0.025 5.60
5 0.025 6.41
6 0.024 6.38
7 0.024 6.42
8 0.026 6.39
9 0.016 6.45
10 0.015 6.46
11 0.016 6.46
12 0.014 6.44
13 0.018 7.00
14 0.017 7.10
15 0.017 7.05
16 0.023 7.01
17 0.030 6.80
18 0.034 6.88
19 0.030 6.87
20 0.035 6.89
21 0.024 6.21
22 0.029 6.18
23 0.028 6.21
24 0.031 6.21
25 0.019 6.43
26 0.023 6.38
27 0.021 6.41
28 0.029 6.39
29 0.027 6.98
30 0.025 6.91
31 0.026 6.71
32 0.029 6.67
33 0.037 6.45
34 0.039 6.41
35 0.038 6.48
36 0.037 6.48
37 0.047 6.42
38 0.043 6.36
39 0.051 6.36
40 0.048 6.40
41 0.033 5.95
42 0.036 6.02
43 0.038 5.96
44 0.038 5.95
45 0.041 6.13
46 0.042 6.14
47 0.040 6.13
48 0.048 6.15
49 NA NA
50 0.006 6.02
51 0.007 6.06
52 0.007 5.99
53 0.080 5.93
54 0.088 5.89
55 0.079 5.86
56 0.079 5.80
57 0.053 7.84
58 0.051 7.87
59 0.069 7.93
60 0.052 7.95
61 0.046 6.04
62 0.048 5.98
63 0.038 6.28
64 0.045 6.54
65 0.176 6.59
66 0.172 6.14
67 0.176 6.38
68 0.176 6.60
69 0.113 6.10
70 0.116 6.14
71 0.114 6.13
72 0.111 6.11
73 0.095 7.06
74 0.065 7.05
75 0.084 7.03
76 0.063 7.01
77 0.048 7.18
78 0.053 7.16
79 0.052 7.28
80 0.051 7.11
81 0.045 7.61
82 0.038 7.62
83 0.046 7.59
84 0.046 7.60
85 0.025 7.51
86 0.026 7.53
87 0.029 7.49
88 0.030 7.54
89 0.030 6.82
90 0.030 6.78
91 0.031 6.82
92 0.031 6.80
93 0.075 6.95
94 0.079 6.90
95 0.076 6.95
96 0.079 6.93
97 0.059 7.39
98 0.065 7.37
99 0.059 7.42
100 0.061 7.41
101 0.038 7.08
102 0.042 7.14
103 0.049 7.24
104 0.058 7.12
105 0.063 7.11
106 0.068 7.11
107 0.058 7.03
108 0.059 7.13
109 0.072 6.67
110 0.076 6.56
111 0.071 6.66
112 0.072 6.59
113 0.113 6.86
114 0.123 6.87
115 0.117 6.81
116 0.114 6.91
117 0.093 6.71
118 0.091 6.71
119 0.090 6.75
120 0.090 6.70
121 0.087 6.63
122 0.099 6.49
123 0.098 6.52
124 0.099 6.45
125 0.010 8.07
126 0.009 8.01
127 0.010 8.06
128 0.009 8.06
my.formula= y ~ exp(1.5*-x)
Pot=data[c(1:52),]
Pot1=data[c(53:64),]
Incub=data[c(65:76),]
Incub1=data[c(77:128),]
library(gridExtra)
library(tidyverse)
library(reshape2)
library(dplyr)
library(reshape2)
library(tidyr)
library(ggpmisc)
library(ggpubr)
library(patchwork) # combine plots
library(gapminder)
p1=ggplot(data=data, aes(x=pH,y=Cd_ppm,col="+Pl (l, control)", col="-Pl (l, control)"))+
geom_point( size=3.5, data = Pot, shape=16)+labs(x="pH", y=expression(Cd~~~mg~(kg~soil)^{-1}))+
geom_point(size=3.5, data=Pot1, shape=17)+
geom_point(size=3.5, data=Incub, shape=2)+
geom_point(size=3.5, data=Incub1, shape=1)+
geom_smooth(data = subset(data, Nu<53),formula= y ~ exp(1.5*-x), method = "lm", se=F, level=0.95, size=0.5,aes(col="+Pl ( Compost, FS, Fe)"))+
geom_smooth(data = subset(data, Nu %in% c(53:64)),formula= y ~ exp(1.5*-x), method = "lm", se=F, level=0.95,size=0.5,linetype="dashed", col="black")+
geom_smooth(data = subset(data, Nu %in% c(65:76)),formula= y ~ exp(1.5*-x), method = "lm", se=F, level=0.95,size=0.5,linetype="dashed", col="black")+
geom_smooth(data = subset(data, Nu>76),formula= y ~ exp(1.5*-x), method = "lm", se=F, level=0.95, size=0.5,aes(col="-Pl ( Compost, FS, Fe)"))+
stat_poly_eq(data = subset(data, Nu<53),formula= y ~ exp(1.5*-x),aes(label=paste(..rr.label..)),
label.x.npc = "left", label.y.npc = 0.03, parse=T, size=6, col="black")+
stat_poly_eq(data = subset(data, Nu=53:64),formula= y ~ exp(1.5*-x),aes(label=paste(..rr.label..)),
label.x.npc = "left", label.y.npc = 0.1, parse=T, size=6, col="black")+
stat_poly_eq(data = subset(data, Nu>76),formula= y ~ exp(1.5*-x),aes(label=paste( ..rr.label..)),
label.x.npc = "right", label.y.npc = 0.8, parse=T, size=6, col="black", vjust=2, show.legend=F)+
stat_poly_eq(data = subset(data, Nu=65:76),formula= y ~ exp(1.5*-x),aes(label=paste(..rr.label..)),
label.x.npc = "right", label.y.npc = 0.9, parse=T, size=6, col="black", vjust=2, show.legend=F)+
theme(legend.text = element_text(colour="black", size=17,face=1))+
theme(legend.position = "bottom") +
guides(color = guide_legend(nrow = 2, byrow = T))+
scale_colour_manual(labels=c(col="Pot liming", col="Incubation liming", col="Incubation", col="Pot"),values = c("black", "black", "black", "black"))+
guides(col = guide_legend(override.aes = list(linetype=c(0,0), shape = c(1, 2, 16, 17), color="black")))
png(file="grafic1.png",height = 125, width = 150, unit ="mm", res = 300)
(mfrow=c(2,2))
ggarrange(p1, ncol=1, nrow=1, common.legend = T, legend="bottom")
dev.off()
您好,我正在尝试将图中的图例拆分为两行。但它不起作用。如果有人给我写一个解决方案,我将非常感谢任何建议。图中的图例由一行组成,我想将其拆分为两行。
1条答案
按热度按时间7hiiyaii1#
您可以在
guides
函数中使用nrow
,如下所示:创建于2023年1月30日,使用reprex v2.0.2