[R] about multi-optimal points

[Ulrik Stervbo]

HI lily,

for the colouring of individual points you can set the colour aesthetic.
The ID is numeric so ggplot applies a colour scale. If we cast ID to a
factor we get the appropriate colouring.

test_df <- data.frame(ID = 1:20, v1 = rnorm(20), v2 = rnorm(20), v3 =
rnorm(20))

ggplot(data=test_df, aes(x=v1,y=v2, colour = as.factor(ID))) +
geom_point()+ theme_bw()+
  xlab('Variable 1')+ ylab('Variable 2')

How to choose a number of samples from the dataset you can use the subset
function to select by some variable:
sub_test_df1 <- subset(test_df, ID < 5)

ggplot(data=sub_test_df1, aes(x=v1,y=v2, colour = as.factor(ID))) +
geom_point()+ theme_bw()+
  xlab('Variable 1')+ ylab('Variable 2')

Or sample a number of random rows using samle() if this is your intention.
sub_test_df2 <- test_df[sample(x = 1:nrow(test_df), size = 10), ]

ggplot(data=sub_test_df2, aes(x=v1,y=v2, colour = as.factor(ID))) +
geom_point()+ theme_bw()+
  xlab('Variable 1')+ ylab('Variable 2')

HTH
Ulrik

On Fri, 25 Aug 2017 at 21:38 lily li <chocold12 at gmail.com> wrote:

> Hi R users,
>
> I have some sets of variables and put them into one dataframe, like in the
> following. How to choose a specific set of pareto front, such as 10 from
> the current datasets (which contains more than 100 sets)? And how to show
> the 10 points on one figure with different colors? I can put all the points
> on one figure though, and have the code below. I drew two ggplots to show
> their correlations, but I want v1 and v3 to be as close as 1, v2 to be as
> close as 0. Thanks very much.
>
> DF
>
> ID    v1     v2     v3
> 1    0.8     0.1    0.7
> 2    0.85   0.3    0.6
> 3    0.9     0.21  0.7
> 4    0.95   0.22  0.8
> 5    0.9     0.3    0.7
> 6    0.8     0.4    0.76
> 7    0.9     0.3    0.77
> ...
>
> fig1 = ggplot(data=DF, aes(x=v1,y=v2))+ geom_point()+ theme_bw()+
> xlab('Variable 1')+ ylab('Variable 2')
> print(fig1)
>
> fig2 = ggplot(data=DF, aes(x=v1,y=v3)+ geom_point()+ theme_bw()+
> xlab('Variable 1')+ ylab('Variable 3')
> print(fig2)
>
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