[R] evaluation of categorical and opinion data

[Petr PIKAL]

Dear all.

I have some data and I seek the way to start their evaluation. The values 
are from survey of different persons and their opinion about various 
methods (metoda) and instrument (uzel). I am not sure where to start. I 
would like to end with combination of method (metoda) and instrument 
(uzel) sorted to let say three categories according to knowledge (znalost) 
and influence (vliv)

knowledge high, influence high - explain it to others
knowledge high, influence low - explain it to others
knowledge low, influence high - start some research
knowledge low, influence low - start some do nothing

I thought about vcd or image or filled contour to see what is amount of 
knowledge or influence 

xt<-xtabs(vliv~metoda+uzel, data=komplet.ag)
filled.contour(1:8, 1:nrow(xt), t(as.matrix(xt)))

Although it shows me colour scale from no knowledge to max knowledge, it 
is rather unconvenient as it does not show names of methods and 
instruments. I can make selections according to values of variable znalost 
or vliv but I would like also to see the whole picture.

If anybody has some insight into such matter, where to look, what 
procedures/graphical function I could use I would be thankful.

Below you can find some data.

Regards
Petr

dput(komplet.ag)
structure(list(metoda = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 
12L), .Label = c("filtrab", "findex", "fluid", "ia", "merpov", 
"mokr", "smac", "spolej", "tpd", "velik", "visk", "zeta"), class = 
"factor"), 
    uzel = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
    5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
    6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 
    8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L), .Label = c("kalc", 
    "mleti", "doprava", "mokrmlyn", "povrch", "filtrace", "suseni", 
    "mikro"), class = "factor"), vliv = c(4, 4.5, 5.75, 5, 5, 
    4, 3.25, 4.5, 4.5, 4.5, 5, 3.25, 4, 3.75, 3.5, 4.5, 4.5, 
    4, 2.5, 4.75, 3, 2.75, 3, 1.5, 3.25, 3.5, 3.25, 5.5, 2.25, 
    3.25, 2, 2.25, 1, 1.5, 2.25, 1, 4, 3.66666666666667, 3.33333333333333, 

    NaN, 3.66666666666667, 4, 2.33333333333333, 4.33333333333333, 
    1, 4.33333333333333, 3.33333333333333, 1.66666666666667, 
    4.5, 4, 2.5, NaN, 5, 3, 4.5, 5, 5, 3.5, 3.5, 4, 2.5, 3.5, 
    2.5, NaN, 2, 3.5, 3.5, 2.5, 3, 2.5, 3, 4, 4, 4, 4, NaN, 4, 
    4, 2, 4, 2, 1, 4, 3, 4.75, 5, 3.75, 4, 4.5, 4, 2.33333333333333, 
    4.25, 2.5, 4.25, 3, 2.66666666666667), znalost = c(4.125, 
    2.5625, 5.375, 4.125, 4.75, 2.5625, 3.5, 3.1875, 1, 5.0625, 
    3.5, 1, 4.125, 2.5625, 4.4375, 2.875, 3.1875, 2.5625, 2.25, 
    3.1875, 1, 2.5625, 3.5, 1, 2.25, 1, 3.5, 2.875, 2.25, 1, 
    2.25, 2.25, 1, 1, 1, 1, 2.66666666666667, 3.08333333333333, 
    4.33333333333333, NaN, 3.08333333333333, 3.08333333333333, 
    2.66666666666667, 3.08333333333333, 1, 5.58333333333333, 
    2.66666666666667, 1, 2.25, 2.25, 3.5, NaN, 4.125, 2.875, 
    3.5, 5.375, 2.25, 4.125, 2.25, 4.125, 3.5, 2.25, 3.5, NaN, 
    2.25, 2.25, 2.25, 2.25, 1, 2.25, 3.5, 4.125, 1, 1, 1, NaN, 
    2.25, 1, 1, 2.25, 1, 1, 1, 1, 2.875, 2.25, 2.875, 1, 2.25, 
    2.875, 1.83333333333333, 2.25, 1, 2.25, 2.25, 1.83333333333333
    )), .Names = c("metoda", "uzel", "vliv", "znalost"), row.names = c(NA, 

-96L), class = "data.frame")