如何仅标记双标图中的一部分点？
How do I label only a subset of points in a biplot?
事实上，我正在使用 fviz_pca_biplot 生成双标图。以下代码提供了我的数据集和双标图的示例。我想标记点的子集，而不是所有点。例如，只有单一属的物种，如桉树。我无法弄清楚如何，甚至可能。谁能提出解决方案？
data <- structure(list(Specific.gravity = c(0.42, 0.43, 0.41, 0.35, 0.39,
1.04, 1.2, 1.23, 0.67, 0.57, 0.65, 1.24, 1.15, 0.48, 0.48, 0.55,
0.62, 0.57, 0.5, 0.54, 0.55, 0.51, 0.47, 0.63, 0.71, 0.38, 0.79,
0.78, 0.84, 0.73, 0.9, 0.41, 0.48, 0.8, 1, 0.56, 0.62, 0.62,
0.71, 0.65, 0.6, 0.55, 0.55, 0.97, 0.95, 1.2, 0.98, 0.81, 0.35,
0.37, 0, 0.72, 0.66, 0.75, 0.75, 0.66, 0.66, 0.69, 0.69, 0.6,
0.8, 0.72, 0.72, 0.48, 0.43, 1.29, 0.48, 0.53, 0.8, 0.43, 0.35,
0.98, 0.85, 0.87, 0.8, 0.85, 0.92, 1.31, 1.07, 1.04, 0.98, 0.76,
0.78, 0.72, 0.65, 0.98, 0.9, 1.13, 0.9, 0.8, 1.03, 0.77, 0.99,
0.82, 0.85, 0.68, 0.78, 1.1, 0.9, 0.66), Modulus.of.elasticity.Mpa = c(10552,
12100, 8620, 10000, 10300, 18500, 18500, 21500, 10830, 11060,
13000, 21500, 18500, 10000, 10000, 7240, 11189, 11200, 8300,
11300, 11327, 7894, 7900, 12600, 12620, 8130, 11860, 12100, 14000,
9356, 14000, 9500, 9520, 8480, 16580, 9100, 13900, 13900, 14906,
15000, 10974, 11000, 7816, 15600, 16300, 16300, 16775, 12100,
7170, 7200, 8920, 7375, 12300, 15600, 15600, 11900, 11900, 13000,
13000, 11700, 14900, 14900, 15300, 8480, 8500, 21500, 9230, 8200,
15760, 11700, 6423, 14560, 12710, 11860, 10640, 17000, 12280,
20550, 12970, 17200, 12454, 9875, 14151, 11720, 10940, 19000,
11000, 18500, 19000, 16505, 16000, 13450, 23000, 13000, 13000,
14020, 12100, 17000, 15230, 11572), Modulus.of.rupture.Mpa = c(66,
75.8, 53, 63, 68, 130, 130, 150, 77, 88, 99, 150, 130, 74, 74,
55, 92, 92, 66, 92, 92, 62, 61, 109, 109, 53, 121, 78, 94, 98,
94, 68, 68, 72, 127, 55, 114, 114, 116, 117, 86, 85, 67, 137,
149, 149, 165, 78, 55, 55, 66, 83, 118, 139, 139, 94, 94, 125,
125, 114, 139, 139, 132, 59, 59, 150, 80, 76, 123, 88, 47, 145,
109, 109, 105, 125, 117, 213, 130, 167, 76, 54, 125, 111, 105,
179, 101, 130, 132, 115, 125, 98, 150, 112, 99, 97, 78, 142,
114, 101), MOR.MOE = c(0.625473843821077, 0.626446280991736,
0.614849187935035, 0.63, 0.660194174757281, 0.702702702702703,
0.702702702702703, 0.697674418604651, 0.710987996306556, 0.795660036166365,
0.761538461538461, 0.697674418604651, 0.702702702702703, 0.74,
0.74, 0.759668508287293, 0.822236124765395, 0.821428571428571,
0.795180722891566, 0.814159292035398, 0.812218592743003, 0.785406637952876,
0.772151898734177, 0.865079365079365, 0.863708399366086, 0.651906519065191,
1.02023608768971, 0.644628099173554, 0.671428571428571, 1.04745617785378,
0.671428571428571, 0.715789473684211, 0.714285714285714, 0.849056603773585,
0.765983112183353, 0.604395604395604, 0.820143884892086, 0.820143884892086,
0.778210116731518, 0.78, 0.78367049389466, 0.772727272727273,
0.857215967246673, 0.878205128205128, 0.914110429447853, 0.914110429447853,
0.983606557377049, 0.644628099173554, 0.767085076708508, 0.763888888888889,
0.739910313901345, 1.12542372881356, 0.959349593495935, 0.891025641025641,
0.891025641025641, 0.789915966386555, 0.789915966386555, 0.961538461538462,
0.961538461538462, 0.974358974358974, 0.932885906040268, 0.932885906040268,
0.862745098039216, 0.695754716981132, 0.694117647058824, 0.697674418604651,
0.866738894907909, 0.926829268292683, 0.780456852791878, 0.752136752136752,
0.731745290362759, 0.995879120879121, 0.857592446892211, 0.919055649241147,
0.986842105263158, 0.735294117647059, 0.952768729641694, 1.03649635036496,
1.00231303006939, 0.970930232558139, 0.610245704191424, 0.546835443037975,
0.883329800014133, 0.947098976109215, 0.959780621572212, 0.942105263157895,
0.918181818181818, 0.702702702702703, 0.694736842105263, 0.696758558012723,
0.78125, 0.728624535315985, 0.652173913043478, 0.861538461538461,
0.761538461538461, 0.691868758915835, 0.644628099173554, 0.835294117647059,
0.748522652659225, 0.872796405115797)), row.names = c("Abies_amabilis",
"Abies_amabilis__a", "Abies_balsamea", "Abies_balsamea__a", "Abies_concolor",
"Acacia_acuminata", "Acacia_aneura", "Acacia_grasby", "Acacia_koa",
"Acacia_mearnsii", "Acacia_melanoxylon", "Acacia_papyrocarpa",
"Acacia_pruinocarpa", "Acer_macrophyllum", "Acer_macrophyllum__a",
"Acer_negundo", "Acer_nigrum", "Acer_nigrum__a", "Acer_pseudoplatanus",
"Acer_rubrum", "Acer_rubrum__a", "Acer_saccharinum", "Acer_saccharinum__a",
"Acer_saccharum", "Acer_saccharum__a", "Aesculus_octandra", "Afzelia_xylocarpa",
"Agonis_flexuosa", "Allocasuarina_decussata_", "Allocasuarina_fraseriana",
"Allocasuarina_huegeliana", "Alnus_sp", "Alnus_sp__a", "Arbutus_menziesii",
"Astronium_fraxinifolium", "Banksia_seminuda", "Betula_alleghaniensis",
"Betula_alleghaniensis__a", "Betula_lenta", "Betula_lenta__a",
"Betula_papyrifera", "Betula_papyrifera__a", "Betula_populifolia",
"Borassus_flabellifer", "Brosimum_paraense", "Brosimum_rubescens",
"Caesalpinia_ferrea", "Callistachys_lanceolata", "Calocedrus_decurrens",
"Calocedrus_decurrens__a", "Cardwellia_sublimis", "Carpinus_caroliniana",
"Carya_cordiformis", "Carya_glabra", "Carya_glabra__a", "Carya_illinoinensis",
"Carya_illinoinensis__a", "Carya_laciniosa", "Carya_laciniosa__a",
"Carya_myristiciformis", "Carya_ovata", "Carya_ovata__a", "Carya_tomentosa",
"Castanea_dentata", "Castanea_dentata__a", "Casuarina_pauper",
"Cedrela_odorata", "Celtis_occidentalis", "Centrolobium_microchaete",
"Chamaecyparis_lawsoniana", "Chamaecyparis_thvoides", "Chloroxylon_swietenia",
"Cocos_nucifera", "Cordia_dodecandra", "Cornus_florida", "Corymbia_calophylla",
"Dalbergia_latifolia", "Dalbergia_melanoxylon", "Dalgergia_retusa",
"Diospyros_crassiflora", "Diospyros_kursii", "Diospyros_melanida",
"Diospyros_virginiana", "Entandrophragma_cylindricum", "Erythroxylon_mexicanum",
"Eucalyptus_astringens", "Eucalyptus_camaldulensis", "Eucalyptus_clelandii",
"Eucalyptus_diversicolor__a", "Eucalyptus_globulus", "Eucalyptus_gomphocephala",
"Eucalyptus_jacksonii", "Eucalyptus_maculata", "Eucalyptus_marginata",
"Eucalyptus_patens", "Eucalyptus_regnans", "Eucalyptus_rudis",
"Eucalyptus_wandoo", "Euxylophora_paraensis", "Fagus_grandifolia_or_Fagus_americana"
), class = "data.frame")
res.pca <- prcomp(data, scale = T, center = T)
fviz_pca_biplot(res.pca)
来自 fviz_pca_biplot() 的对象是 ggplot 对象。这意味着您可以使用以 +.
开头的附加命令来添加它
使用您的数据并从 res.pca 对象开始。
library(tidyverse)
首先删除所有标签。
p<- fviz_pca_biplot(res.pca, label = "none")
然后从绘图对象中获取标签。
plotnames <- p$data$name %>% as.character()
然后使用一些逻辑使大部分为空，但保留要添加到图形中的那些。
mylabels <- sapply(plotnames, function(x) ifelse(is.na(str_locate(x,"Eucalyptus")[1]), "", x)) %>% as.vector()
最后，将新标签向量添加到原始绘图对象
p + geom_text(aes(label = mylabels))
事实上，我正在使用 fviz_pca_biplot 生成双标图。以下代码提供了我的数据集和双标图的示例。我想标记点的子集，而不是所有点。例如，只有单一属的物种，如桉树。我无法弄清楚如何，甚至可能。谁能提出解决方案？
data <- structure(list(Specific.gravity = c(0.42, 0.43, 0.41, 0.35, 0.39,
1.04, 1.2, 1.23, 0.67, 0.57, 0.65, 1.24, 1.15, 0.48, 0.48, 0.55,
0.62, 0.57, 0.5, 0.54, 0.55, 0.51, 0.47, 0.63, 0.71, 0.38, 0.79,
0.78, 0.84, 0.73, 0.9, 0.41, 0.48, 0.8, 1, 0.56, 0.62, 0.62,
0.71, 0.65, 0.6, 0.55, 0.55, 0.97, 0.95, 1.2, 0.98, 0.81, 0.35,
0.37, 0, 0.72, 0.66, 0.75, 0.75, 0.66, 0.66, 0.69, 0.69, 0.6,
0.8, 0.72, 0.72, 0.48, 0.43, 1.29, 0.48, 0.53, 0.8, 0.43, 0.35,
0.98, 0.85, 0.87, 0.8, 0.85, 0.92, 1.31, 1.07, 1.04, 0.98, 0.76,
0.78, 0.72, 0.65, 0.98, 0.9, 1.13, 0.9, 0.8, 1.03, 0.77, 0.99,
0.82, 0.85, 0.68, 0.78, 1.1, 0.9, 0.66), Modulus.of.elasticity.Mpa = c(10552,
12100, 8620, 10000, 10300, 18500, 18500, 21500, 10830, 11060,
13000, 21500, 18500, 10000, 10000, 7240, 11189, 11200, 8300,
11300, 11327, 7894, 7900, 12600, 12620, 8130, 11860, 12100, 14000,
9356, 14000, 9500, 9520, 8480, 16580, 9100, 13900, 13900, 14906,
15000, 10974, 11000, 7816, 15600, 16300, 16300, 16775, 12100,
7170, 7200, 8920, 7375, 12300, 15600, 15600, 11900, 11900, 13000,
13000, 11700, 14900, 14900, 15300, 8480, 8500, 21500, 9230, 8200,
15760, 11700, 6423, 14560, 12710, 11860, 10640, 17000, 12280,
20550, 12970, 17200, 12454, 9875, 14151, 11720, 10940, 19000,
11000, 18500, 19000, 16505, 16000, 13450, 23000, 13000, 13000,
14020, 12100, 17000, 15230, 11572), Modulus.of.rupture.Mpa = c(66,
75.8, 53, 63, 68, 130, 130, 150, 77, 88, 99, 150, 130, 74, 74,
55, 92, 92, 66, 92, 92, 62, 61, 109, 109, 53, 121, 78, 94, 98,
94, 68, 68, 72, 127, 55, 114, 114, 116, 117, 86, 85, 67, 137,
149, 149, 165, 78, 55, 55, 66, 83, 118, 139, 139, 94, 94, 125,
125, 114, 139, 139, 132, 59, 59, 150, 80, 76, 123, 88, 47, 145,
109, 109, 105, 125, 117, 213, 130, 167, 76, 54, 125, 111, 105,
179, 101, 130, 132, 115, 125, 98, 150, 112, 99, 97, 78, 142,
114, 101), MOR.MOE = c(0.625473843821077, 0.626446280991736,
0.614849187935035, 0.63, 0.660194174757281, 0.702702702702703,
0.702702702702703, 0.697674418604651, 0.710987996306556, 0.795660036166365,
0.761538461538461, 0.697674418604651, 0.702702702702703, 0.74,
0.74, 0.759668508287293, 0.822236124765395, 0.821428571428571,
0.795180722891566, 0.814159292035398, 0.812218592743003, 0.785406637952876,
0.772151898734177, 0.865079365079365, 0.863708399366086, 0.651906519065191,
1.02023608768971, 0.644628099173554, 0.671428571428571, 1.04745617785378,
0.671428571428571, 0.715789473684211, 0.714285714285714, 0.849056603773585,
0.765983112183353, 0.604395604395604, 0.820143884892086, 0.820143884892086,
0.778210116731518, 0.78, 0.78367049389466, 0.772727272727273,
0.857215967246673, 0.878205128205128, 0.914110429447853, 0.914110429447853,
0.983606557377049, 0.644628099173554, 0.767085076708508, 0.763888888888889,
0.739910313901345, 1.12542372881356, 0.959349593495935, 0.891025641025641,
0.891025641025641, 0.789915966386555, 0.789915966386555, 0.961538461538462,
0.961538461538462, 0.974358974358974, 0.932885906040268, 0.932885906040268,
0.862745098039216, 0.695754716981132, 0.694117647058824, 0.697674418604651,
0.866738894907909, 0.926829268292683, 0.780456852791878, 0.752136752136752,
0.731745290362759, 0.995879120879121, 0.857592446892211, 0.919055649241147,
0.986842105263158, 0.735294117647059, 0.952768729641694, 1.03649635036496,
1.00231303006939, 0.970930232558139, 0.610245704191424, 0.546835443037975,
0.883329800014133, 0.947098976109215, 0.959780621572212, 0.942105263157895,
0.918181818181818, 0.702702702702703, 0.694736842105263, 0.696758558012723,
0.78125, 0.728624535315985, 0.652173913043478, 0.861538461538461,
0.761538461538461, 0.691868758915835, 0.644628099173554, 0.835294117647059,
0.748522652659225, 0.872796405115797)), row.names = c("Abies_amabilis",
"Abies_amabilis__a", "Abies_balsamea", "Abies_balsamea__a", "Abies_concolor",
"Acacia_acuminata", "Acacia_aneura", "Acacia_grasby", "Acacia_koa",
"Acacia_mearnsii", "Acacia_melanoxylon", "Acacia_papyrocarpa",
"Acacia_pruinocarpa", "Acer_macrophyllum", "Acer_macrophyllum__a",
"Acer_negundo", "Acer_nigrum", "Acer_nigrum__a", "Acer_pseudoplatanus",
"Acer_rubrum", "Acer_rubrum__a", "Acer_saccharinum", "Acer_saccharinum__a",
"Acer_saccharum", "Acer_saccharum__a", "Aesculus_octandra", "Afzelia_xylocarpa",
"Agonis_flexuosa", "Allocasuarina_decussata_", "Allocasuarina_fraseriana",
"Allocasuarina_huegeliana", "Alnus_sp", "Alnus_sp__a", "Arbutus_menziesii",
"Astronium_fraxinifolium", "Banksia_seminuda", "Betula_alleghaniensis",
"Betula_alleghaniensis__a", "Betula_lenta", "Betula_lenta__a",
"Betula_papyrifera", "Betula_papyrifera__a", "Betula_populifolia",
"Borassus_flabellifer", "Brosimum_paraense", "Brosimum_rubescens",
"Caesalpinia_ferrea", "Callistachys_lanceolata", "Calocedrus_decurrens",
"Calocedrus_decurrens__a", "Cardwellia_sublimis", "Carpinus_caroliniana",
"Carya_cordiformis", "Carya_glabra", "Carya_glabra__a", "Carya_illinoinensis",
"Carya_illinoinensis__a", "Carya_laciniosa", "Carya_laciniosa__a",
"Carya_myristiciformis", "Carya_ovata", "Carya_ovata__a", "Carya_tomentosa",
"Castanea_dentata", "Castanea_dentata__a", "Casuarina_pauper",
"Cedrela_odorata", "Celtis_occidentalis", "Centrolobium_microchaete",
"Chamaecyparis_lawsoniana", "Chamaecyparis_thvoides", "Chloroxylon_swietenia",
"Cocos_nucifera", "Cordia_dodecandra", "Cornus_florida", "Corymbia_calophylla",
"Dalbergia_latifolia", "Dalbergia_melanoxylon", "Dalgergia_retusa",
"Diospyros_crassiflora", "Diospyros_kursii", "Diospyros_melanida",
"Diospyros_virginiana", "Entandrophragma_cylindricum", "Erythroxylon_mexicanum",
"Eucalyptus_astringens", "Eucalyptus_camaldulensis", "Eucalyptus_clelandii",
"Eucalyptus_diversicolor__a", "Eucalyptus_globulus", "Eucalyptus_gomphocephala",
"Eucalyptus_jacksonii", "Eucalyptus_maculata", "Eucalyptus_marginata",
"Eucalyptus_patens", "Eucalyptus_regnans", "Eucalyptus_rudis",
"Eucalyptus_wandoo", "Euxylophora_paraensis", "Fagus_grandifolia_or_Fagus_americana"
), class = "data.frame")
res.pca <- prcomp(data, scale = T, center = T)
fviz_pca_biplot(res.pca)
来自 fviz_pca_biplot() 的对象是 ggplot 对象。这意味着您可以使用以 +.
使用您的数据并从 res.pca 对象开始。
library(tidyverse)
首先删除所有标签。
p<- fviz_pca_biplot(res.pca, label = "none")
然后从绘图对象中获取标签。
plotnames <- p$data$name %>% as.character()
然后使用一些逻辑使大部分为空，但保留要添加到图形中的那些。
mylabels <- sapply(plotnames, function(x) ifelse(is.na(str_locate(x,"Eucalyptus")[1]), "", x)) %>% as.vector()
最后，将新标签向量添加到原始绘图对象
p + geom_text(aes(label = mylabels))