使用 ggplot2 绘制 4 个变量的条形图
Barplot using ggplot2 for 4 variables
我有这样的数据：
ID height S1 S2 S3
1 927 0.90695438 0.28872194 0.67114294
2 777 0.20981677 0.71783084 0.74498220
3 1659 0.35813799 0.92339744 0.44001698
4 174 0.44829914 0.67493949 0.11503942
5 1408 0.90642643 0.18593999 0.67564278
6 1454 0.38943930 0.34806716 0.73155952
7 2438 0.51745975 0.12351953 0.48398490
8 1114 0.12523909 0.10811622 0.17104804
9 1642 0.03014575 0.29795320 0.67584853
10 515 0.77180549 0.83819990 0.26298995
11 1877 0.32741508 0.99277109 0.34148083
12 2647 0.38947869 0.43713441 0.21024554
13 845 0.04105275 0.20256457 0.01631959
14 1198 0.36139663 0.96387150 0.37676288
15 2289 0.57097808 0.66038711 0.56230740
16 2009 0.68488024 0.29811683 0.67998461
17 618 0.97111675 0.11926219 0.74538877
18 1076 0.70195881 0.59975160 0.95007272
19 1082 0.01154550 0.12019055 0.16309071
20 2072 0.53553213 0.78843202 0.32475690
21 1610 0.83657146 0.36959607 0.13271604
22 2134 0.80686674 0.95632284 0.63729744
23 1617 0.08093264 0.91357666 0.33092961
24 2248 0.23890930 0.82333634 0.64907957
25 1263 0.96598986 0.31948216 0.30288836
26 518 0.03767233 0.87770033 0.07123327
27 2312 0.91640643 0.80035100 0.66239047
28 2646 0.72622658 0.61135664 0.75960356
29 1650 0.20077621 0.07242114 0.55336017
30 837 0.84020075 0.42158771 0.53927210
31 1467 0.39666235 0.34446560 0.84959232
32 2786 0.39270226 0.75173569 0.65322596
33 1049 0.47255689 0.21875132 0.95088576
34 2863 0.58365691 0.29213397 0.61722305
35 2087 0.35238717 0.35595337 0.49284063
36 2669 0.02847401 0.63196192 0.97600657
37 545 0.99508793 0.89253107 0.49034522
38 1890 0.95755846 0.74403278 0.65517230
39 2969 0.55165118 0.45722242 0.59880179
40 395 0.10195396 0.03609544 0.94756902
41 995 0.23791515 0.56851452 0.36801151
42 2596 0.86009766 0.43901589 0.87818701
43 2334 0.73826129 0.60048445 0.45487507
44 2483 0.49731226 0.95138276 0.49646702
45 1812 0.57992109 0.26943131 0.46061562
46 1476 0.01618339 0.65883839 0.61790820
47 2342 0.47212988 0.07647121 0.60414349
48 2653 0.04238973 0.07128521 0.78587960
49 627 0.46315442 0.37033152 0.55526847
50 925 0.62999477 0.29710220 0.76897834
51 995 0.67324929 0.55107827 0.40428567
52 600 0.08703467 0.36989059 0.51071981
53 711 0.14358380 0.84568953 0.52353644
54 828 0.90847850 0.62079070 0.99279921
55 1776 0.12253259 0.39914002 0.42964742
56 764 0.72886279 0.29966153 0.99601125
57 375 0.95037718 0.38111984 0.78660025
58 694 0.04335591 0.70113494 0.51591063
59 1795 0.01959930 0.94686529 0.50268797
60 638 0.19907246 0.77282832 0.91163748
61 1394 0.50508626 0.21955016 0.26441590
62 1943 0.92638876 0.71611036 0.17385687
63 2882 0.13840169 0.66421796 0.40033126
64 2031 0.16919458 0.70625020 0.53835738
65 1338 0.60662738 0.27962799 0.24496437
66 1077 0.81587669 0.71225050 0.37585096
67 1370 0.84338121 0.66094211 0.58025355
68 1339 0.78807719 0.04101269 0.20895531
69 739 0.01902087 0.06114149 0.80133001
70 2085 0.69808750 0.27976169 0.63880242
71 1240 0.81509312 0.30196772 0.73633076
72 987 0.56840006 0.95661083 0.43881241
73 1720 0.48006288 0.38981872 0.57981238
74 2901 0.16137012 0.37178879 0.25604401
75 1987 0.08925623 0.84314249 0.46371823
76 1876 0.16268237 0.84723500 0.16861486
77 2571 0.02672845 0.31933115 0.61389453
78 2325 0.70962948 0.13250605 0.95810262
79 2503 0.76101818 0.61710912 0.47819473
80 279 0.85747478 0.79130451 0.75115933
81 1381 0.43726582 0.33804871 0.02058322
82 1800 0.41713645 0.90544760 0.17096903
83 2760 0.58564949 0.19755671 0.63996650
84 2949 0.82496758 0.79408518 0.16497848
85 118 0.79313923 0.75460289 0.35472278
86 1736 0.32615257 0.91139485 0.18642647
87 2201 0.95793194 0.32268770 0.89765616
88 750 0.65301961 0.08616947 0.23778386
89 906 0.45867582 0.91120045 0.98494348
90 2202 0.60602188 0.95517383 0.02133074
我想使用 ggplot2 制作条形图，如下所示：
在 above-mentioned 数据集中，高度应该在 y-axis 上，S1、S2、S3 应该代表每个样本的颜色。
我已经尝试了 base R 函数 barplot，它给了我以下输出。请给我任何建议。
barplot(t(as.matrix(examp[,3:5])),col=rainbow(3))
我不清楚你到底想策划什么。你说你想要 y 轴上的高度，但你显示的示例都是 'filled to the top'，这意味着每个 ID 的高度相同。此外，尚不清楚与每个样本相关的数字代表什么。我猜它们应该是条形高度的相对权重。
假设您确实想要示例中的实心条形图，并且条形的相对大小由样本值决定，您可以这样做：
library(tidyr)
library(dplyr)
library(ggplot2)
df %>%
mutate(ID = reorder(ID, S3/(S3 + S2 + S1))) %>%
pivot_longer(3:5, names_to = "Sample", values_to = "Value") %>%
ggplot(aes(ID, Value * height, fill = Sample)) +
geom_col(position = "fill", color = NA) +
labs(y = "Height") +
theme_classic() +
scale_fill_manual(values = c("red", "green", "blue"))
备选
df %>%
arrange(order(height)) %>%
group_by(height) %>%
summarize(across(everything(), mean)) %>%
pivot_longer(3:5, names_to = "Sample", values_to = "Value") %>%
ggplot(aes(height, Value, fill = Sample, colour = Sample)) +
geom_smooth(method = loess, formula = y ~ x, linetype = 2, alpha = 0.2) +
theme_bw()
我有这样的数据：
ID height S1 S2 S3
1 927 0.90695438 0.28872194 0.67114294
2 777 0.20981677 0.71783084 0.74498220
3 1659 0.35813799 0.92339744 0.44001698
4 174 0.44829914 0.67493949 0.11503942
5 1408 0.90642643 0.18593999 0.67564278
6 1454 0.38943930 0.34806716 0.73155952
7 2438 0.51745975 0.12351953 0.48398490
8 1114 0.12523909 0.10811622 0.17104804
9 1642 0.03014575 0.29795320 0.67584853
10 515 0.77180549 0.83819990 0.26298995
11 1877 0.32741508 0.99277109 0.34148083
12 2647 0.38947869 0.43713441 0.21024554
13 845 0.04105275 0.20256457 0.01631959
14 1198 0.36139663 0.96387150 0.37676288
15 2289 0.57097808 0.66038711 0.56230740
16 2009 0.68488024 0.29811683 0.67998461
17 618 0.97111675 0.11926219 0.74538877
18 1076 0.70195881 0.59975160 0.95007272
19 1082 0.01154550 0.12019055 0.16309071
20 2072 0.53553213 0.78843202 0.32475690
21 1610 0.83657146 0.36959607 0.13271604
22 2134 0.80686674 0.95632284 0.63729744
23 1617 0.08093264 0.91357666 0.33092961
24 2248 0.23890930 0.82333634 0.64907957
25 1263 0.96598986 0.31948216 0.30288836
26 518 0.03767233 0.87770033 0.07123327
27 2312 0.91640643 0.80035100 0.66239047
28 2646 0.72622658 0.61135664 0.75960356
29 1650 0.20077621 0.07242114 0.55336017
30 837 0.84020075 0.42158771 0.53927210
31 1467 0.39666235 0.34446560 0.84959232
32 2786 0.39270226 0.75173569 0.65322596
33 1049 0.47255689 0.21875132 0.95088576
34 2863 0.58365691 0.29213397 0.61722305
35 2087 0.35238717 0.35595337 0.49284063
36 2669 0.02847401 0.63196192 0.97600657
37 545 0.99508793 0.89253107 0.49034522
38 1890 0.95755846 0.74403278 0.65517230
39 2969 0.55165118 0.45722242 0.59880179
40 395 0.10195396 0.03609544 0.94756902
41 995 0.23791515 0.56851452 0.36801151
42 2596 0.86009766 0.43901589 0.87818701
43 2334 0.73826129 0.60048445 0.45487507
44 2483 0.49731226 0.95138276 0.49646702
45 1812 0.57992109 0.26943131 0.46061562
46 1476 0.01618339 0.65883839 0.61790820
47 2342 0.47212988 0.07647121 0.60414349
48 2653 0.04238973 0.07128521 0.78587960
49 627 0.46315442 0.37033152 0.55526847
50 925 0.62999477 0.29710220 0.76897834
51 995 0.67324929 0.55107827 0.40428567
52 600 0.08703467 0.36989059 0.51071981
53 711 0.14358380 0.84568953 0.52353644
54 828 0.90847850 0.62079070 0.99279921
55 1776 0.12253259 0.39914002 0.42964742
56 764 0.72886279 0.29966153 0.99601125
57 375 0.95037718 0.38111984 0.78660025
58 694 0.04335591 0.70113494 0.51591063
59 1795 0.01959930 0.94686529 0.50268797
60 638 0.19907246 0.77282832 0.91163748
61 1394 0.50508626 0.21955016 0.26441590
62 1943 0.92638876 0.71611036 0.17385687
63 2882 0.13840169 0.66421796 0.40033126
64 2031 0.16919458 0.70625020 0.53835738
65 1338 0.60662738 0.27962799 0.24496437
66 1077 0.81587669 0.71225050 0.37585096
67 1370 0.84338121 0.66094211 0.58025355
68 1339 0.78807719 0.04101269 0.20895531
69 739 0.01902087 0.06114149 0.80133001
70 2085 0.69808750 0.27976169 0.63880242
71 1240 0.81509312 0.30196772 0.73633076
72 987 0.56840006 0.95661083 0.43881241
73 1720 0.48006288 0.38981872 0.57981238
74 2901 0.16137012 0.37178879 0.25604401
75 1987 0.08925623 0.84314249 0.46371823
76 1876 0.16268237 0.84723500 0.16861486
77 2571 0.02672845 0.31933115 0.61389453
78 2325 0.70962948 0.13250605 0.95810262
79 2503 0.76101818 0.61710912 0.47819473
80 279 0.85747478 0.79130451 0.75115933
81 1381 0.43726582 0.33804871 0.02058322
82 1800 0.41713645 0.90544760 0.17096903
83 2760 0.58564949 0.19755671 0.63996650
84 2949 0.82496758 0.79408518 0.16497848
85 118 0.79313923 0.75460289 0.35472278
86 1736 0.32615257 0.91139485 0.18642647
87 2201 0.95793194 0.32268770 0.89765616
88 750 0.65301961 0.08616947 0.23778386
89 906 0.45867582 0.91120045 0.98494348
90 2202 0.60602188 0.95517383 0.02133074
我想使用 ggplot2 制作条形图，如下所示：
在 above-mentioned 数据集中，高度应该在 y-axis 上，S1、S2、S3 应该代表每个样本的颜色。
我已经尝试了 base R 函数 barplot，它给了我以下输出。请给我任何建议。
barplot(t(as.matrix(examp[,3:5])),col=rainbow(3))
我不清楚你到底想策划什么。你说你想要 y 轴上的高度，但你显示的示例都是 'filled to the top'，这意味着每个 ID 的高度相同。此外，尚不清楚与每个样本相关的数字代表什么。我猜它们应该是条形高度的相对权重。
假设您确实想要示例中的实心条形图，并且条形的相对大小由样本值决定，您可以这样做：
library(tidyr)
library(dplyr)
library(ggplot2)
df %>%
mutate(ID = reorder(ID, S3/(S3 + S2 + S1))) %>%
pivot_longer(3:5, names_to = "Sample", values_to = "Value") %>%
ggplot(aes(ID, Value * height, fill = Sample)) +
geom_col(position = "fill", color = NA) +
labs(y = "Height") +
theme_classic() +
scale_fill_manual(values = c("red", "green", "blue"))
备选
df %>%
arrange(order(height)) %>%
group_by(height) %>%
summarize(across(everything(), mean)) %>%
pivot_longer(3:5, names_to = "Sample", values_to = "Value") %>%
ggplot(aes(height, Value, fill = Sample, colour = Sample)) +
geom_smooth(method = loess, formula = y ~ x, linetype = 2, alpha = 0.2) +
theme_bw()