我很难找到如何在组合回归图中更改 geom_point 的内部颜色,但我无法使用 scale_color_manual()
对于站点 F 和 F1,我希望具有相同的形状和相同的外部颜色,但“F”内部为黑色,“F1”内部为灰色
这是我的代码和情节
mydata<-read.csv(choose.files(),header=T)
ggplot(mydata,aes(y=density,x=Do, color=color, shape=color,group=site))+geom_point(size=3.5)+
stat_smooth(method="lm",se=FALSE)+
scale_shape_manual(values=seq(0,8))+
scale_y_log10()+
scale_x_log10()+
labs(x = "Do", y = bquote('density'~(No.m^-3)))+
theme_classic()+
theme(aspect.ratio=1)+
theme(axis.title.x = element_text(color = 'black',face = 'bold',size = 18, hjust = 0.5))+
theme(axis.text = font)+
theme(axis.title.y = element_text(color = 'black',face = 'bold',size=25, hjust = 0.5))+theme(legend.title = element_text(size=8, color = "white"),legend.position=c(0.17, 0.20),
我的数据
site Do density color
1 A 15.32500000 14.6254359 A
2 A 3.46153846 2.5634207 A
3 A 1.37692308 54.5375387 A
4 A 0.52115385 44.4123777 A
5 B 9.71431056 5.4299784 B
6 B 7.60803311 2.9582927 B
7 B 6.61874506 1.3994870 B
8 B 5.38889098 2.1169919 B
9 C 18.95522388 0.6911765 C
10 C 12.23880597 1.2352941 C
11 C 7.91044776 1.1029412 C
12 C 4.02985075 1.0441176 C
13 C 3.43283582 0.7500000 C
14 D 19.85892857 5.7023070 D
15 D 15.21785714 3.2076197 D
16 D 8.00357143 2.3692545 D
17 D 7.67142857 3.0929227 D
18 D 5.75357143 3.8173552 D
19 E 96.26288660 5.5576024 E
20 E 118.41752580 4.3844430 E
21 E 88.97938144 4.3557405 E
22 E 33.16752577 6.1140918 E
23 E 8.27164948 4.8505888 E
24 F 23.54920101 2.7593361 F
25 F 20.52144659 2.3236515 F
26 F 15.97981497 3.0497925 F
27 F 56.09756097 5.6639004 F
28 F 37.93103448 6.2448133 F
29 F 2.80908326 5.5186722 F
30 F 5.53406223 11.0373444 F
31 F 4.85281750 5.2282158 F
32 F 9.92430614 1.8879668 F
33 F 0.36809306 5.6639004 F
34 F 2.73338940 1.8879668 F
35 F 3.94449117 6.3900415 F
36 F 1.59798150 3.9211618 F
37 F 4.39865433 2.6141079 F
38 F 1.21951220 33.5477178 F
39 F 40.84051724 4.3388430 F
40 F 36.96120690 2.4586777 F
41 F 35.02155172 3.3264463 F
42 F 44.71982759 0.8677686 F
43 F 52.47844828 0.8677686 F
44 F 4.41379310 2.0247934 F
45 F 1.45358090 7.2314050 F
46 F 0.25615763 17.6446281 F
47 F 5.08222812 1.1570248 F
48 F 0.25615763 30.8057851 F
49 F 3.26790451 5.7851240 F
50 F 3.84084881 4.4834711 F
51 F 2.02652520 8.8223140 F
52 F 5.17771883 2.0247934 F
53 F 0.05941645 12.5826446 F
54 F1 68.20857863 2.7593361 F
55 F1 64.42388562 2.3236515 F
56 F1 72.91645498 3.3402490 F
57 F1 60.63919260 2.1784232 F
58 F1 59.12531539 3.1950207 F
59 F1 56.09756097 4.2116183 F
60 F1 51.55592935 3.7759336 F
61 F1 50.04205214 2.4688797 F
62 F1 49.28511354 11.0373444 F
63 F1 68.96551724 0.8677686 F
64 F1 76.79352531 0.5785124 F
65 F1 79.59555352 2.8925620 F
66 F1 55.38793103 0.8677686 F
67 F1 51.50862069 1.3016529 F
68 F1 53.44827586 5.9297521 F
69 F1 49.56896552 1.1570248 F
70 F1 43.75000000 0.7231405 F
71 F1 44.71982759 7.9545455 F
72 G 31.69856459 2.0000000 G
73 G 61.60287081 4.0000000 G
74 G 53.22966507 8.0000000 G
75 G 8.97129187 12.0000000 G
76 G 10.16746411 6.0000000 G
77 G 9.56937799 5.0000000 G
78 G 8.97129187 5.0000000 G
任何帮助,将不胜感激