# Select 2d spaces with variable associated measures displayed in scatterplot matrix Measures object is a matrix or data.frame with measures (columns) for variable pairs (rows) and rownames of the two variates separated by separator ```r ## Default S3 method: 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 ## Returns 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")` ## Examples ```r if(interactive()){ ## Not run: 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) ## End(Not run) } ``` ## See Also `l_ng_plots`, `l_ng_plots.measures`, `l_ng_plots.scagnostics`, `measures1d`, `measures2d`, `scagnostics2d`, `l_ng_ranges`

l_ng_plots.default function