使用corrplot包绘制相关性图
加载所需R包
library(corrplot)
基本使用
corrplot(corr, method = c("circle", "square", "ellipse", "number", "shade", "color", "pie"),
type = c("full", "lower", "upper"), add = FALSE, col = NULL,
bg = "white", title = "", is.corr = TRUE, diag = TRUE,
outline = FALSE, mar = c(0, 0, 0, 0), addgrid.col = NULL,
addCoef.col = NULL, addCoefasPercent = FALSE,
order = c("original","AOE", "FPC", "hclust", "alphabet"),
hclust.method = c("complete", "ward", "ward.D", "ward.D2",
"single", "average", "mcquitty", "median", "centroid"),
addrect = NULL, rect.col = "black", rect.lwd = 2, tl.pos = NULL,
tl.cex = 1, tl.col = "red", tl.offset = 0.4, tl.srt = 90,
cl.pos = NULL, cl.lim = NULL, cl.length = NULL, cl.cex = 0.8,
cl.ratio = 0.15, cl.align.text = "c", cl.offset = 0.5, number.cex = 1,
number.font = 2, number.digits = NULL,
addshade = c("negative", "positive", "all"), shade.lwd = 1, shade.col = "white", p.mat = NULL,
sig.level = 0.05, insig = c("pch", "p-value", "blank", "n", "label_sig"),
pch = 4, pch.col = "black", pch.cex = 3, plotCI = c("n", "square", "circle", "rect"),
lowCI.mat = NULL, uppCI.mat = NULL, na.label = "?",
na.label.col = "black", win.asp = 1, ...)
使用示例
# 加载数据集
data(mtcars)
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
# 计算相关系数
M <- cor(mtcars)
M
## mpg cyl disp hp drat wt
## mpg 1.0000000 -0.8521620 -0.8475514 -0.7761684 0.68117191 -0.8676594
## cyl -0.8521620 1.0000000 0.9020329 0.8324475 -0.69993811 0.7824958
## disp -0.8475514 0.9020329 1.0000000 0.7909486 -0.71021393 0.8879799
## hp -0.7761684 0.8324475 0.7909486 1.0000000 -0.44875912 0.6587479
## drat 0.6811719 -0.6999381 -0.7102139 -0.4487591 1.00000000 -0.7124406
## wt -0.8676594 0.7824958 0.8879799 0.6587479 -0.71244065 1.0000000
## qsec 0.4186840 -0.5912421 -0.4336979 -0.7082234 0.09120476 -0.1747159
## vs 0.6640389 -0.8108118 -0.7104159 -0.7230967 0.44027846 -0.5549157
## am 0.5998324 -0.5226070 -0.5912270 -0.2432043 0.71271113 -0.6924953
## gear 0.4802848 -0.4926866 -0.5555692 -0.1257043 0.69961013 -0.5832870
## carb -0.5509251 0.5269883 0.3949769 0.7498125 -0.09078980 0.4276059
## qsec vs am gear carb
## mpg 0.41868403 0.6640389 0.59983243 0.4802848 -0.55092507
## cyl -0.59124207 -0.8108118 -0.52260705 -0.4926866 0.52698829
## disp -0.43369788 -0.7104159 -0.59122704 -0.5555692 0.39497686
## hp -0.70822339 -0.7230967 -0.24320426 -0.1257043 0.74981247
## drat 0.09120476 0.4402785 0.71271113 0.6996101 -0.09078980
## wt -0.17471588 -0.5549157 -0.69249526 -0.5832870 0.42760594
## qsec 1.00000000 0.7445354 -0.22986086 -0.2126822 -0.65624923
## vs 0.74453544 1.0000000 0.16834512 0.2060233 -0.56960714
## am -0.22986086 0.1683451 1.00000000 0.7940588 0.05753435
## gear -0.21268223 0.2060233 0.79405876 1.0000000 0.27407284
## carb -0.65624923 -0.5696071 0.05753435 0.2740728 1.00000000
## 设置不同系列颜色
col1 <- colorRampPalette(c("#7F0000", "red", "#FF7F00", "yellow", "white",
"cyan", "#007FFF", "blue","#00007F"))
col2 <- colorRampPalette(c("#67001F", "#B2182B", "#D6604D", "#F4A582",
"#FDDBC7", "#FFFFFF", "#D1E5F0", "#92C5DE",
"#4393C3", "#2166AC", "#053061"))
col3 <- colorRampPalette(c("red", "white", "blue"))
col4 <- colorRampPalette(c("#7F0000", "red", "#FF7F00", "yellow", "#7FFF7F",
"cyan", "#007FFF", "blue", "#00007F"))
wb <- c("white", "black")
# methold参数设定不同展示方式
corrplot(M) #默认methold="circle"
image.png
corrplot(M, method = "ellipse")
image.png
corrplot(M, method = "pie")
image.png
corrplot(M, method = "color")
image.png
corrplot(M, method = "number")
image.png
# col = "black"设定颜色为黑色, cl.pos = "n"设定颜色图例不展示
corrplot(M, method = "number", col = "black", cl.pos = "n")
image.png
# order参数设定不同展示顺序，默认order="orginal"以原始顺序展示
corrplot(M, order = "AOE")
image.png
# addCoef.col = "grey"添加相关系数并设定颜色为grey
corrplot(M, order = "AOE", addCoef.col = "grey")
image.png
# col = col1(20)设定20种颜色
corrplot(M, order = "AOE", col = col1(20), addCoef.col = "grey")
image.png
corrplot(M, order = "AOE", col = col1(10), addCoef.col = "grey")
image.png
# 更改order = "FPC"
corrplot(M, order = "FPC", col = col2(200))
image.png
corrplot(M, order = "FPC", col = col2(20), addCoef.col = "grey")
image.png
corrplot(M, order = "FPC", col = col2(10), addCoef.col = "grey")
image.png
# 更改order = "hclust"
corrplot(M, order = "hclust", col = col3(100))
image.png
corrplot(M, order = "hclust", col = col3(10))
image.png
## 设定col = wb
corrplot(M, col = wb, order = "AOE", outline = TRUE, cl.pos = "n")
image.png
## bg = "gold2"设置背景色
corrplot(M, col = wb, bg = "gold2", order = "AOE", cl.pos = "n")
image.png
# 多图组和
## circle + ellipse
# type参数设定展示类型，默认type="full"展示全部
corrplot(M, order = "AOE", type = "upper")
image.png
# tl.pos = "d"设定文本标签展示在对角线
corrplot(M, order = "AOE", type = "upper", tl.pos = "d")
# add = TRUE在已有的图形上添加其他图形
corrplot(M, add = TRUE, type = "lower", method = "ellipse", order = "AOE",
diag = FALSE, tl.pos = "n", cl.pos = "n")
image.png
# tl.pos = "n"不展示文本标签, cl.pos = "n"不展示颜色图例，diag = FALSE不展示对角线的相关系数
corrplot(M, order = "AOE", type = "lower", method = "ellipse",
diag = FALSE, tl.pos = "n", cl.pos = "n")
image.png
## circle + square
corrplot(M, order = "AOE",type = "upper", tl.pos = "d")
corrplot(M, add = TRUE, type = "lower", method = "square", order = "AOE",
diag = FALSE, tl.pos = "n", cl.pos = "n")
image.png
## circle + colorful number
corrplot(M, order = "AOE", type = "upper", tl.pos = "d")
corrplot(M, add = TRUE, type = "lower", method = "number", order = "AOE",
diag = FALSE, tl.pos = "n", cl.pos = "n")
image.png
## circle + black number
corrplot(M, order = "AOE", type = "upper", tl.pos = "tp")
corrplot(M, add = TRUE, type = "lower", method = "number", order = "AOE",
col = "black", diag = FALSE, tl.pos = "n", cl.pos = "n")
image.png
## order is hclust and draw rectangles
corrplot(M, order = "hclust")
image.png
# addrect参数添加矩形方框
corrplot(M, order = "hclust", addrect = 2)
image.png
corrplot(M, order = "hclust", addrect = 3, rect.col = "red")
image.png
corrplot(M, order = "hclust", addrect = 4, rect.col = "blue")
image.png
# hclust.method = "ward.D2"设定聚类方法
corrplot(M, order = "hclust", hclust.method = "ward.D2", addrect = 4)
image.png
## visualize a matrix in [0, 1]
# cl.lim = c(0,1)设定图例颜色范围
corrplot(abs(M), order = "AOE", cl.lim = c(0,1))
image.png
corrplot(abs(M), order = "AOE", col = col1(20), cl.lim = c(0,1))
image.png
## text-labels and plot type
# tl.srt参数设定文本标签摆放角度
corrplot(M, order = "AOE", tl.srt = 45)
image.png
corrplot(M, order = "AOE", tl.srt = 60)
image.png
corrplot(M, order = "AOE", tl.pos = "d", cl.pos = "n")
image.png
corrplot(M, order = "AOE", type = "upper")
image.png
# diag = FALSE不展示对角线的相关系数
corrplot(M, order = "AOE", type = "upper", diag = FALSE)
image.png
corrplot(M, order = "AOE", type = "lower", cl.pos = "b")
image.png
corrplot(M, order = "AOE", type = "lower", cl.pos = "b", diag = FALSE)
image.png
#### color-legend
# cl.ratio参数设定颜色图例的宽度, cl.align设定图例文本的对齐方式
corrplot(M, order = "AOE", cl.ratio = .1, cl.align = "l")
image.png
corrplot(M, order = "AOE", cl.ratio = .2, cl.align = "l") #居左
image.png
corrplot(M, order = "AOE", cl.ratio = .2, cl.align = "c") #居中
image.png
corrplot(M, order = "AOE", cl.ratio = .2, cl.align = "r") #居右
image.png
# cl.pos设定颜色图例的位置,tl.pos设定文本标签位置
corrplot(M, order = "AOE", cl.pos = "b")
image.png
corrplot(M, order = "AOE", cl.pos = "b", tl.pos = "d")
image.png
corrplot(M, order = "AOE", cl.pos = "n")
image.png
sessionInfo()
## R version 3.5.1 (2018-07-02)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: OS X El Capitan 10.11.3
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
##
## locale:
## [1] zh_CN.UTF-8/zh_CN.UTF-8/zh_CN.UTF-8/C/zh_CN.UTF-8/zh_CN.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] corrplot_0.84
##
## loaded via a namespace (and not attached):
## [1] compiler_3.5.1 backports_1.1.2 magrittr_1.5 rprojroot_1.3-2
## [5] tools_3.5.1 htmltools_0.3.6 yaml_2.2.0 Rcpp_0.12.18
## [9] stringi_1.2.4 rmarkdown_1.10 knitr_1.20 stringr_1.3.1
## [13] digest_0.6.16 evaluate_0.11
