R語言中繪製彩色相關性矩陣
阿新 • • 發佈:2019-01-25
> data(mtcars)
> #首先匯入資料集mtcars
> corr <- cor(mtcars)
> #將資料集中的每個列的相關係數統計出來並儲存在一個corr的引數中
> corr
> #檢視corr資料結果,統計出來的相互之間的相關係數
mpg cyl disp hp drat wt qsec vs am
mpg 1.0000000 -0.8521620 -0.8475514 -0.7761684 0.68117191 -0.8676594 0.41868403 0.6640389 0.59983243
cyl -0.8521620 1.0000000 0.9020329 0.8324475 -0.69993811 0.7824958 -0.59124207 -0.8108118 -0.52260705
disp -0.8475514 0.9020329 1.0000000 0.7909486 -0.71021393 0.8879799 -0.43369788 -0.7104159 -0.59122704
hp -0.7761684 0.8324475 0.7909486 1.0000000 -0.44875912 0.6587479 -0.70822339 -0.7230967 -0.24320426
drat 0.6811719 -0.6999381 -0.7102139 -0.4487591 1.00000000 -0.7124406 0.09120476 0.4402785 0.71271113
wt -0.8676594 0.7824958 0.8879799 0.6587479 -0.71244065 1.0000000 -0.17471588 -0.5549157 -0.69249526
qsec 0.4186840 -0.5912421 -0.4336979 -0.7082234 0.09120476 -0.1747159 1.00000000 0.7445354 -0.22986086
vs 0.6640389 -0.8108118 -0.7104159 -0.7230967 0.44027846 -0.5549157 0.74453544 1.0000000 0.16834512
am 0.5998324 -0.5226070 -0.5912270 -0.2432043 0.71271113 -0.6924953 -0.22986086 0.1683451 1.00000000
gear 0.4802848 -0.4926866 -0.5555692 -0.1257043 0.69961013 -0.5832870 -0.21268223 0.2060233 0.79405876
carb -0.5509251 0.5269883 0.3949769 0.7498125 -0.09078980 0.4276059 -0.65624923 -0.5696071 0.05753435
gear carb
mpg 0.4802848 -0.55092507
cyl -0.4926866 0.52698829
disp -0.5555692 0.39497686
hp -0.1257043 0.74981247
drat 0.6996101 -0.09078980
wt -0.5832870 0.42760594
qsec -0.2126822 -0.65624923
vs 0.2060233 -0.56960714
am 0.7940588 0.05753435
gear 1.0000000 0.27407284
carb 0.2740728 1.00000000
> install.packages("corrplot")
>#安裝corrplot包,全稱是Correlation R Plot
trying URL 'http://cran.rstudio.com/bin/windows/contrib/3.1/corrplot_0.73.zip'
Content type 'application/zip' length 2680438 bytes (2.6 Mb)
opened URL
downloaded 2.6 Mb
package ‘corrplot’ successfully unpacked and MD5 sums checked
The downloaded binary packages are in
C:\Users\chn-fzj\AppData\Local\Temp\Rtmp6lhx90\downloaded_packages
> require(corrplot)
Loading required package: corrplot
> corrplot(corr)
> corrplot(corr,method="shade",shade.col=NA,tl.col="black",tl.srt=45)
>#兩個命令的主要差異在於:method引數設定的不一樣,其他引數只是修改字型顏色和傾斜等等 >#method引數主要包括以下幾種:"circle", "square", "ellipse", "number", "shade", "color", "pie" > par(mfrow=c(4,2)) > corrplot(corr,method="circle")
> corrplot(corr,method="square")
> corrplot(corr,method="ellipse")
> corrplot(corr,method="number")
> corrplot(corr,method="shade")
> corrplot(corr,method="color")
> corrplot(corr,method="pie")
#本案例用到的包是corrplot #用到的命令是corrplot() #用到的資料集是mtcars #個人的偏好的method是“number”,效果見下圖:
> corrplot(corr,method="shade",shade.col=NA,tl.col="black",tl.srt=45)
>#兩個命令的主要差異在於:method引數設定的不一樣,其他引數只是修改字型顏色和傾斜等等 >#method引數主要包括以下幾種:"circle", "square", "ellipse", "number", "shade", "color", "pie" > par(mfrow=c(4,2)) > corrplot(corr,method="circle")
#本案例用到的包是corrplot #用到的命令是corrplot() #用到的資料集是mtcars #個人的偏好的method是“number”,效果見下圖: