l_hist
is a generic function for creating interactive histogram displays
that can be linked with loon's other displays.
l_hist(x, ...) # S3 method for default l_hist( x, yshows = c("frequency", "density"), by = NULL, on, layout = c("grid", "wrap", "separate"), connectedScales = c("cross", "row", "column", "both", "x", "y", "none"), origin = NULL, binwidth = NULL, showStackedColors = TRUE, showBinHandle = FALSE, color = l_getOption("color"), active = TRUE, selected = FALSE, xlabel = NULL, showLabels = TRUE, showScales = FALSE, showGuides = TRUE, parent = NULL, ... ) # S3 method for factor l_hist( x, showFactors = length(unique(x)) < 25L, factorLabelAngle, factorLabelSize = 12, factorLabelColor = l_getOption("foreground"), factorLabelY = 0, ... ) # S3 method for character l_hist( x, showFactors = length(unique(x)) < 25L, factorLabelAngle, factorLabelSize = 12, factorLabelColor = l_getOption("foreground"), factorLabelY = 0, ... ) # S3 method for data.frame l_hist(x, ...) # S3 method for matrix l_hist(x, ...) # S3 method for list l_hist(x, ...) # S3 method for table l_hist(x, ...) # S3 method for array l_hist(x, ...)
x  vector with numerical data to perform the binning on x, 

...  named arguments to modify the histogram plot states or layouts, see details. 
yshows  one of "frequency" (default) or "density" 
by  loon plot can be separated by some variables into multiple panels.
This argument can take a 
on  if the 
layout  layout facets as 
connectedScales  Determines how the scales of the facets are to be connected depending
on which

origin  numeric scalar to define the binning origin 
binwidth  a numeric scalar to specify the binwidth
If NULL 
showStackedColors  if TRUE (default) then bars will be coloured according to colours of the points; if FALSE, then the bars will be a uniform colour except for highlighted points. 
showBinHandle  If 
color  colour fills of bins; colours are repeated
until matching the number x.
Default is found using 
active  a logical determining whether points appear or not
(default is 
selected  a logical determining whether points appear selected at first
(default is 
xlabel  label to be used on the horizontal axis. If NULL, an attempt at a meaningful label
inferred from 
showLabels  logical to determine whether axes label (and title) should be presented. 
showScales  logical to determine whether numerical scales should be presented on both axes. 
showGuides  logical to determine whether to present background guidelines to help determine locations. 
parent  a valid Tk parent widget path. When the parent widget is
specified (i.e. not 
showFactors  whether to show the factor labels (unique strings in 
factorLabelAngle  is the angle of rotation (in degrees) for the factor labels. If not specified, an angle of 0 is chosen if there are fewer than 10 labels; labels are rotated 90 degrees if there are 10 or more. This can also be a numeric vector of length equal to the number of factor labels. 
factorLabelSize  is the font size for the factor labels (default 12). 
factorLabelColor  is the colour to be used for the factor labels.
(default is 
factorLabelY  either a single number, or a numeric vector of length equal to the number of factor labels, determining the y coordinate(s) for the factor labels. 
if the argument by
is not set, a loon
widget will be returned;
else an l_facet
object (a list) will be returned and each element is
a loon
widget displaying a subset of interest.
For more information run: l_help("learn_R_display_hist")
Note that when changing the yshows
state from
'frequency'
to 'density'
you might have to use
l_scaleto_world
to show the complete histogram in the plotting
region.
Some arguments to modify layouts can be passed through,
e.g. "separate", "byrow", etc.
Check l_facet
to see how these arguments work.
Turn interactive loon plot static loonGrob
, grid.loon
, plot.loon
.
Other loon interactive states:
l_info_states()
,
l_plot()
,
l_serialaxes()
,
l_state_names()
,
names.loon()
if(interactive()){ h < l_hist(iris$Sepal.Length) names(h) h["xlabel"] < "Sepal length" h["showOutlines"] < FALSE h["yshows"] h["yshows"] < "density" l_scaleto_plot(h) h["showStackedColors"] < TRUE h['color'] < iris$Species h["showStackedColors"] < FALSE h["showOutlines"] < TRUE h["showGuides"] < FALSE # link another plot with the previous plot h['linkingGroup'] < "iris_data" h2 < with(iris, l_hist(Petal.Width, linkingGroup="iris_data", showStackedColors = TRUE)) # Get an R (grid) graphics plot of the current loon plot plot(h) # or with more control about grid parameters grid.loon(h) # or to save the grid data structure (grob) for later use hg < loonGrob(h) }