Last chance! 50% off unlimited learning
Sale ends in
Mplot
plots data from (a list of) matrices.
Msplit
splits a matrix in a list according to factors (or unique values).
Mcommon
creates a list of matrices that have only common variables.
Msummary
and Mdescribe
create suitable summaries of all columns of a matrix or list.
Mplot (M, ..., x = 1, select = NULL, which = select,
subset = NULL, ask = NULL,
legend = list(x = "center"), pos.legend = NULL,
xyswap = FALSE, rev = "") Msummary (M, ...,
select = NULL, which = select,
subset = NULL)
Mdescribe (M, ...,
select = NULL, which = select,
subset = NULL)
Msplit (M, split = 1, subset = NULL)
Mcommon (M, ..., verbose = FALSE)
Function Msplit
returns a list with the matrices, split according to
the factors; the names of the elements is set by the factor's name.
It is similar to the R-function split.
Function Mcommon
returns a list with the matrices, which only have
the common variables.
Function Msummary
returns a data.frame with summary values (minimum,
first quantile, median, mean, 3rd quantile, maximum) for each
column of the input (variable). If there are more than one object to be summarised, or
if M is a list of objects, the name of the object is in the second column.
Function Mdescribe
returns a data.frame with summary values (number of data,
number of missing values, number of unique values, mean value, the standard deviation,
the minimum, the p = 0.05, 0.1, 0.5, 0.9, 0.95 quantiles, and the maximum) for each
column of the input (variable). If there are more than one object to be summarised, or
if M is a list of objects, the name of the object is in the second column.
Matrix or data.frame to be plotted, or treated. For Mplot
, M
can be
a list with matrices or data.frames.
Name or number of the column to be used as the x-values.
Which variable/columns to be selected. This is added for
consistency with the R-function subset
.
The name(s) or the index to the variables that should be
plotted or selected. Default = all variables, except time
.
Logical expression indicating elements or rows to keep in
select
: missing values are taken as FALSE
Logical; if TRUE
, the user is asked before
each plot, if NULL
the user is only asked if more than one
page of plots is necessary and the current graphics device is set
interactive, see par(ask)
and
dev.interactive
.
A list
with parameters for the legend
to be added. If FALSE
, then no legend will be drawn.
The position of the legend, a number. The default
is to put the legend in the last figure.
Also allowed is pos.legend = 0
,
which will create a new figure with only the legend.
If TRUE
, then the x- and y-values will be swapped.
a character string which contains "x" if the x axis is to be reversed, "y" if the y axis is to be reversed and "xy" or "yx" if both axes are to be reversed.
The name or number of the column with the factor according to which the matrix will be split.
If TRUE
will write output to the screen.
Additional arguments passed to the methods. For Mplot
:
can also be extra matrices to plot.
The arguments after ... must be matched exactly.
Karline Soetaert <karline.soetaert@nioz.nl>
# save plotting parameters
pm <- par("mfrow")
## =======================================================================
## Create three dummy matrices
## =======================================================================
M1 <- matrix(nrow = 10, ncol = 5, data = 1:50)
colnames(M1) <- LETTERS[1:5]
M2 <- M1[, c(1, 3, 4, 5, 2)]
M2[ ,-1] <- M2[,-1] /2
colnames(M2)[3] <- "CC" # Different name
M3 <- matrix(nrow = 5, ncol = 4, data = runif(20)*10)
M3[,1] <- sort(M3[,1])
colnames(M3) <- colnames(M1)[-3]
# show them
head(M1); head(M2); head(M3)
Msummary(M1)
Msummary(M1, M2, M3)
# plot all columns of M3 - will change mfrow
Mplot(M3, type = "b", pch = 18, col = "red")
# plot results of all three data sets
Mplot(M1, M2, M3, lwd = 2, mtext = "All variables versus 1st column",
legend = list(x = "top", legend = c("M1", "M2", "M3")))
## =======================================================================
## Plot a selection or only common elements
## =======================================================================
Mplot(M1, M2, M3, x = "B", select = c("A", "E"), pch = c(NA, 16, 1),
type = c("l", "p", "b"), col = c("black", "red", "blue"),
legend = list(x = "right", legend = c("M1", "M2", "M3")))
Mplot(Mcommon(M1, M2, M3), lwd = 2, mtext = "common variables",
legend = list(x = "top", legend = c("M1", "M2", "M3")))
Mdescribe(Mcommon(M1, M2, M3))
## =======================================================================
## The iris and Orange data set
## =======================================================================
# Split the matrix according to the species
Irislist <- Msplit(iris, split = "Species")
names(Irislist)
Mdescribe(Irislist, which = "Sepal.Length")
Mdescribe(iris, which = "Sepal.Length", subset = Species == "setosa")
# legend in a separate plot
Mplot(Irislist, type = "p", pos.legend = 0,
legend = list(x = "center", title = "species"))
Mplot(Msplit(Orange,1), lwd = 2,
legend = list(x = "topleft", title = "tree nr"))
Msummary(Msplit(Orange,1))
# reset plotting parameters
par(mfrow = pm)
Run the code above in your browser using DataLab