Measures object is a matrix or data.frame with measures (columns) for variable pairs (rows) and rownames of the two variates separated by separator

# S3 method for default
l_ng_plots(measures, data, separator = ":", ...)

Arguments

measures

matrix or data.frame with measures (columns) for variable pairs (rows) and rownames of the two variates separated by separator

data

data frame for scatterplot

separator

a string that separates the variable pair string into the individual variables

...

arguments passed on to configure the scatterplot

Value

named list with plots-, graph-, plot-, navigator-, and context handle. The list also contains the environment of the the function call in env.

Details

For more information run: l_help("learn_R_display_graph.html#l_ng_plots")

See also

Examples

if(interactive()){ if (FALSE) { n <- 100 dat <- data.frame( A = rnorm(n), B = rnorm(n), C = rnorm(n), D = rnorm(n), E = rnorm(n) ) m2d <- data.frame( cov = with(dat, c(cov(A,B), cov(A,C), cov(B,D), cov(D,E), cov(A,E))), measure_1 = c(1, 3, 2, 1, 4), row.names = c('A:B', 'A:C', 'B:D', 'D:E', 'A:E') ) # or m2d <- as.matrix(m2d) nav <- l_ng_plots(measures=m2d, data=dat) # only one measure m <- m2d[,1] names(m) <- row.names(m2d) nav <- l_ng_plots(measures=m, data=dat) m2d[c(1,2),1] # one d measures m1d <- data.frame( mean = sapply(dat, mean), median = sapply(dat, median), sd = sapply(dat, sd), q1 = sapply(dat, function(x)quantile(x, probs=0.25)), q3 = sapply(dat, function(x)quantile(x, probs=0.75)), row.names = names(dat) ) nav <- l_ng_plots(m1d, dat) ## more involved q1 <- function(x)as.vector(quantile(x, probs=0.25)) # be careful that the vector names are correct nav <- l_ng_plots(sapply(oliveAcids, q1), oliveAcids) } }