R：使用xyplot中的线将特定变量级别的点连接起来

Question

I have a data frame df with the following variables: Test , A , p and D . I want to print A against p , grouping by variable D levels.

I am using xyplot to do so and type=('p','l') to plot the points and the connecting lines between points. This procedure connects all points of the same level of variable D . The problem is that I want to connect only the points from the same Test .

Any clue how this can be done? Or if it is possible to do it with xyplot ?

Example for data

    Test         A           p     D
95    32 0.0000000 0.010148395 55.04
96    32 0.2746429 0.018040352 55.04
97    32 1.0000000 0.019101864 55.04
271   72 0.0000000 0.005900593 22.64
272   72 0.1677419 0.006708547 22.64
273   72 0.4290323 0.009770698 22.64
274   72 1.0000000 0.010637487 22.64
275   73 0.0000000 0.005175419 22.64
276   73 0.2242424 0.006683234 22.64
277   73 0.3793939 0.009750174 22.64
278   73 1.0000000 0.012231502 22.64

This is the code I am using:

xyplot(A ~ p, data=df, groups=D, type=c("p","l"))

This is an example of what I would like to achieve. Maybe it is not possible with xyplot .

Example of what I want to achieve

Answer 1

Quite difficult to know for sure what you're asking. Do try to elaborate further with an example figure of what you want to achieve.

Anyway, here's a quick way using ggplot to show respective Ap plots for different levels of D and Test :

ggplot(df, aes(A, p)) + 
    geom_line() + 
    geom_point() + 
    facet_grid(D~Test)

Answer 2

I think I finally get to solve this problem.

With data originally posted and the code

xyplot(A ~ p, data=df, groups=D, type=c("p","l"))

I get a scatter plot where points through different Test are connected against my will like in the following figure .

I add to "cheat" R in order to get what I wanted: connect only points from the same Test . To do that I added rows to the original data frame with NA values at the end of each Test .

   Test    A     p     D
1    32    0  0.01 35.04
2    32 0.27 0.018 35.04
3    32    1 0.019 35.04
4    32 <NA>  <NA> 35.04
5    72    0 0.006 12.64
6    72 0.17 0.007 12.64
7    72 0.43  0.01 12.64
8    72    1 0.011 12.64
9    72 <NA>  <NA> 12.64
10   73    0 0.005 12.64
11   73 0.22 0.007 12.64
12   73 0.38  0.01 12.64
13   73    1 0.012 12.64
14   73 <NA>  <NA> 12.64

And the result is showed in this figure .

I hope this post can help others.

Best regards

Ricardo