Question

使用下面的df <- read.table(text = c(" diesel twodoors sportsstyle wheelbase length width height curbweight enginesize horsepower horse_per_weight conscity price symboling 0 1 0 97 172 66 56 2209 109 85 0.0385 8.7 7975 2 0 0 0 100 177 66 54 2337 109 102 0.0436 9.8 13950 2 0 0 0 116 203 72 57 3740 234 155 0.0414 14.7 34184 -1 0 1 1 103 184 68 52 3016 171 161 0.0534 12.4 15998 3 0 0 0 101 177 65 54 2765 164 121 0.0438 11.2 21105 0 0 1 0 90 169 65 52 2756 194 207 0.0751 13.8 34028 3 1 0 0 105 175 66 54 2700 134 72 0.0267 7.6 18344 0 0 0 0 108 187 68 57 3020 120 97 0.0321 12.4 11900 0 0 0 1 94 157 64 51 1967 90 68 0.0346 7.6 6229 1 0 1 0 95 169 64 53 2265 98 112 0.0494 9.0 9298 1 1 0 0 96 166 64 53 2275 110 56 0.0246 6.9 7898 0 0 1 0 100 177 66 53 2507 136 110 0.0439 12.4 15250 2 0 1 1 94 157 64 51 1876 90 68 0.0362 6.4 5572 1 0 0 0 95 170 64 54 2024 97 69 0.0341 7.6 7349 1 0 1 1 95 171 66 52 2823 152 154 0.0546 12.4 16500 1 0 0 0 103 175 65 60 2535 122 88 0.0347 9.8 8921 -1 0 0 0 113 200 70 53 4066 258 176 0.0433 15.7 32250 0 0 0 0 95 165 64 55 1938 97 69 0.0356 7.6 6849 1 1 0 0 97 172 66 56 2319 97 68 0.0293 6.4 9495 2 0 0 0 97 172 66 56 2275 109 85 0.0374 8.7 8495 2"), header = T)（来源：http://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/en_Tanagra_PLSR_Software_Comparison.pdf）

数据

library(plsdepot)
df.plsdepot = plsreg1(df[, 1:11], df[, 14, drop = FALSE], comps = 3)
plot(df.plsdepot, comps = c(1, 2))

和这个

代码

symboling

我得到了这个

结果

此处的从属（y）变量diesel与价格一样，是汽车所有其他自变量的函数（twodoors，sportsstyle，wheelbase，{ {1}}，length，width，height，curbweight，enginesize，horsepower，horse_per_weight）

问题

使用ggplot2创建上图的任何帮助，但使用箭头而不是类似于 plot 的行将受到高度赞赏？

Answer 1

df <- read.table(text = c("
diesel  twodoors    sportsstyle wheelbase   length  width   height  curbweight  enginesize  horsepower  horse_per_weight    conscity    price   symboling
                          0   1   0   97  172 66  56  2209    109 85  0.0385  8.7 7975    2
                          0   0   0   100 177 66  54  2337    109 102 0.0436  9.8 13950   2
                          0   0   0   116 203 72  57  3740    234 155 0.0414  14.7    34184   -1
                          0   1   1   103 184 68  52  3016    171 161 0.0534  12.4    15998   3
                          0   0   0   101 177 65  54  2765    164 121 0.0438  11.2    21105   0
                          0   1   0   90  169 65  52  2756    194 207 0.0751  13.8    34028   3
                          1   0   0   105 175 66  54  2700    134 72  0.0267  7.6 18344   0
                          0   0   0   108 187 68  57  3020    120 97  0.0321  12.4    11900   0
                          0   0   1   94  157 64  51  1967    90  68  0.0346  7.6 6229    1
                          0   1   0   95  169 64  53  2265    98  112 0.0494  9.0 9298    1
                          1   0   0   96  166 64  53  2275    110 56  0.0246  6.9 7898    0
                          0   1   0   100 177 66  53  2507    136 110 0.0439  12.4    15250   2
                          0   1   1   94  157 64  51  1876    90  68  0.0362  6.4 5572    1
                          0   0   0   95  170 64  54  2024    97  69  0.0341  7.6 7349    1
                          0   1   1   95  171 66  52  2823    152 154 0.0546  12.4    16500   1
                          0   0   0   103 175 65  60  2535    122 88  0.0347  9.8 8921    -1
                          0   0   0   113 200 70  53  4066    258 176 0.0433  15.7    32250   0
                          0   0   0   95  165 64  55  1938    97  69  0.0356  7.6 6849    1
                          1   0   0   97  172 66  56  2319    97  68  0.0293  6.4 9495    2
                          0   0   0   97  172 66  56  2275    109 85  0.0374  8.7 8495    2"), header = T)

library(plsdepot)
library(ggplot2)
df.plsdepot = plsreg1(df[, 1:11], df[, 14, drop = FALSE], comps = 3)
data<-df.plsdepot$cor.xyt
data<-as.data.frame(data)

#Function to draw circle
circleFun <- function(center = c(0,0),diameter = 1, npoints = 100){
    r = diameter / 2
    tt <- seq(0,2*pi,length.out = npoints)
    xx <- center[1] + r * cos(tt)
    yy <- center[2] + r * sin(tt)
    return(data.frame(x = xx, y = yy))
}

dat <- circleFun(c(0,0),2,npoints = 100)

ggplot(data=data, aes(t1,t2))+
  ylab("")+xlab("")+ggtitle("Circle of Correlations                                                                     ")+
  theme_bw() +geom_text(aes(label=rownames(data), 
                            colour=ifelse(rownames(data)!='symboling', 'orange','blue')))+
  scale_color_manual(values=c("orange","#6baed6"))+
  scale_x_continuous(breaks = c(-1,-0.5,0,0.5,1))+
  scale_y_continuous(breaks = c(-1,-0.5,0,0.5,1))+
  coord_fixed(ylim=c(-1, 1),xlim=c(-1, 1))+xlab("axis 1")+ 
  ylab("axis 2")+ theme(axis.line.x = element_line(color="darkgrey"),
                        axis.line.y = element_line(color="darkgrey"))+
  geom_path(data=dat,aes(x,y), colour = "darkgrey")+
  theme(legend.title=element_blank())+
  theme(axis.ticks = element_line(colour = "grey"))+
  theme(axis.title = element_text(colour = "darkgrey"))+
  theme(axis.text = element_text(color="darkgrey"))+
  theme(legend.position='none')+
  theme(plot.title = element_text(color="#737373")) +
  theme(panel.grid.minor = element_blank()) +
  annotate("segment",x=0, y=0, xend= 0.60, yend= 0.20, color="orange",
           arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.25, yend= -0.35, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= 0.45, yend= 0.75, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= 0.37 , yend=-0.02, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.80, yend= 0.30, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.75, yend= 0.60, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.67, yend= 0.60, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.59, yend= -0.13, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.59, yend= 0.70, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= -0.39, yend= 0.80, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= 0.04, yend= 0.93, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))+
  annotate("segment",x=0, y=0, xend= 0.70, yend= 0.40, color="#6baed6",
           alpha=0.3,arrow=arrow(length=unit(0.3,"cm")))

用ggplot2绘制偏最小二乘回归双标图

1 个答案: