2

Using the data.frame below (Source: http://eric.univ-lyon2.fr/~ricco/tanagra/fichiers/en_Tanagra_PLSR_Software_Comparison.pdf)

Data 

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)

and this

Code 

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

I got this

Result

enter image description here

The dependent (y) variable here is symboling, like price, is function of all other independent variables for the cars (diesel, twodoors, sportsstyle, wheelbase, length, width, height, curbweight, enginesize,horsepower, horse_per_weight)

Question

Any help to create the plot above using ggplot2 but with arrows instead of lines similar to this plot will be highly appreciated?

Cyrus Mohammadian
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shiny
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1 Answers1

2
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")))

enter image description here

Cyrus Mohammadian
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  • Thanks for your time and help. I got this error `Error in rownames(h) : object 'h' not found` – shiny Aug 27 '16 at 02:24
  • i would check your workflow , there is no object h there....you may have mixed it up with the previous question answer – Cyrus Mohammadian Aug 27 '16 at 03:42
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    Thanks. In your answer, there is `h` in this line of the code `theme_bw() +geom_text(aes(label=rownames(h),` – shiny Aug 27 '16 at 03:44
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    my bad, i changed ``h`` to ``data``! try it again and let me know if there are any lingering issues! – Cyrus Mohammadian Aug 27 '16 at 03:47
  • There is still `h` in the code above `colour=ifelse(rownames(h)!='symboling', 'orange','blue')))+` Even after changing both to `data`, I got this error `Error in eval(expr, envir, enclos) : object 'x' not found` – shiny Aug 27 '16 at 03:51
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    see edits, if there any `` h`` just replace with ``data`` – Cyrus Mohammadian Aug 27 '16 at 03:52
  • I have changed any `h` to `data` and I changed `dat` to `data` in `geom_path(data=dat,aes(x,y), colour = "darkgrey")+`. Still, I'm getting this error `Error in eval(expr, envir, enclos) : object 'x' not found` – shiny Aug 27 '16 at 03:56
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    @aelwan Ok i think i fixed it now. I forgot to add the function to draw the circle (and its associated data). Also make sure that the ``geom_path`` data call is set to ``dat`` and not ``data`` -I just cleared my workspace so it should work. – Cyrus Mohammadian Aug 27 '16 at 04:03
  • If I had to use `pls` package instead of the `plsdepot` and I want to get the the correlation between variables and components. You got them through converting `df.plsdepot$cor.xyt` to data.frame. In the `pls` package, I can plot these correlation as follows `library(pls) Y <- as.matrix(df[,14]) X <- as.matrix(df[,1:11]) df.pls <- mvr(Y ~ X, ncomp = 3, method = "oscorespls", scale = T) plot(df.pls, "correlation")` but I don't know how to get these values into data.frame. Any suggestions will be highly appreciated? – shiny Aug 28 '16 at 03:14
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    @aelwan I would suggest starting a new question post, i'm not sure myself – Cyrus Mohammadian Aug 28 '16 at 05:48
  • Thanks for your suggestion. I posted it here http://stackoverflow.com/questions/39188663/correlation-between-variables-and-components-using-pls-package – shiny Aug 28 '16 at 06:42