plot: Plot fdt.default and fdt.multiple objects

In fdth: Frequency Distribution Tables, Histograms and Polygons

Plot fdt.default and fdt.multiple objects

Description

S3 methods for fdt.default and fdt.multiple objects. It is possible to plot histograms and polygons (absolute, relative and cumulative).

Usage

## S3 methods  
## S3 method for class 'fdt.default'
plot(x,
     type=c('fh', 'fp', 
            'rfh', 'rfp', 
            'rfph', 'rfpp', 
            'd',
            'cdh', 'cdp', 
            'cfh', 'cfp', 
            'cfph', 'cfpp'),
     v=FALSE,
     v.round=2,
     v.pos=3,
     xlab="Class limits",
     xlas=0,
     ylab=NULL,
     col="gray",
     xlim=NULL,
     ylim=NULL,
     main=NULL,
     x.round=2, ...)

## S3 method for class 'fdt.multiple'
plot(x,
     type=c('fh', 'fp', 
            'rfh', 'rfp', 
            'rfph', 'rfpp', 
            'd',
            'cdh', 'cdp', 
            'cfh', 'cfp', 
            'cfph', 'cfpp'),
     v=FALSE,
     v.round=2,
     v.pos=3,
     xlab="Class limits",
     xlas=0,
     ylab=NULL, 
     col="gray",
     xlim=NULL,
     ylim=NULL,
     main=NULL,
     main.vars=TRUE,
     x.round=2, 
     grouped=FALSE,
     args.legend=NULL, ...)

## S3 method for class 'fdt_cat.default'
plot(x,
     type=c('fb', 'fp', 'fd',
            'rfb', 'rfp', 'rfd',
            'rfpb', 'rfpp', 'rfpd',
            'cfb', 'cfp', 'cfd',
            'cfpb', 'cfpp', 'cfpd',
            'pa'),
     v=FALSE,
     v.round=2,
     v.pos=3,
     xlab=NULL,
     xlas=0,
     ylab=NULL,
     y2lab=NULL,
     y2cfp=seq(0, 100, 25),
     col=gray(.4),
     xlim=NULL,
     ylim=NULL,
     main=NULL,
     box=FALSE, ...)

## S3 method for class 'fdt_cat.multiple'
plot(x,
     type=c('fb', 'fp', 'fd',
            'rfb', 'rfp', 'rfd',
            'rfpb', 'rfpp', 'rfpd',
            'cfb', 'cfp', 'cfd',
            'cfpb', 'cfpp', 'cfpd',
            'pa'),
     v=FALSE,
     v.round=2,
     v.pos=3,
     xlab=NULL,
     xlas=0,
     ylab=NULL, 
     y2lab=NULL,
     y2cfp=seq(0, 100, 25),
     col=gray(.4),
     xlim=NULL,
     ylim=NULL,
     main=NULL,
     main.vars=TRUE,
     box=FALSE, ...)

Arguments

x	A ‘⁠fdt⁠’ object.
type	the type of the plot: ‘⁠fb:⁠’ absolute frequency barplot, ‘⁠fh:⁠’ absolute frequency histogram, ‘⁠fp:⁠’ absolute frequency polygon, ‘⁠fd:⁠’ absolute frequency dotchart, ‘⁠rfb:⁠’ relative frequency barplot, ‘⁠rfh:⁠’ relative frequency histogram, ‘⁠rfp:⁠’ relative frequency polygon, ‘⁠rfd:⁠’ relative frequency dotchart, ‘⁠rfpb:⁠’ relative frequency (%) barplot, ‘⁠rfph:⁠’ relative frequency (%) histogram, ‘⁠rfpp:⁠’ relative frequency (%) polygon, ‘⁠rfpd:⁠’ relative frequency (%) dotchart, ‘⁠d:⁠’ density, ‘⁠cdh:⁠’ cumulative density histogram, ‘⁠cdp:⁠’ cumulative density polygon, ‘⁠cfb:⁠’ cumulative frequency barplot, ‘⁠cfh:⁠’ cumulative frequency histogram, ‘⁠cfp:⁠’ cumulative frequency polygon, ‘⁠cfd:⁠’ cumulative frequency dotchart, ‘⁠cdpb:⁠’ cumulative frequency (%) barplot, ‘⁠cdph:⁠’ cumulative frequency (%) histogram, ‘⁠cfpp:⁠’ cumulative frequency (%) polygon, ‘⁠cfpd:⁠’ cumulative frequency (%) dotchart. ‘⁠pa:⁠’ pareto chart.
v	logical flag: should the values be added to the plot?
v.round	if v=TRUE, it rounds the values to the specified number of decimal places (default 0).
v.pos	if v=TRUE, a position specifier for the text. Values of 1, 2, 3 and 4, respectively indicate positions below, to the left of, above and to the right of the coordinates (default 3).
xlab	a label for the ‘⁠x⁠’ axis.
xlas	an integer which controls the orientation of the ‘⁠x⁠’ axis labels: ‘⁠0:⁠’ parallel to the axes, ‘⁠2:⁠’ perpendicular to the axes.
ylab	a label for the ‘⁠y⁠’ axis.
y2lab	a label for the ‘⁠y2⁠’ axis.
y2cfp	a cumulative percent frequency for the ‘⁠y2⁠’ axis. The default is seq(0, 100, 25).
col	a vector of colors.
xlim	the ‘⁠x⁠’ limits of the plot.
ylim	the ‘⁠y⁠’ limits of the plot.
main	title of the plot(s). This option has priority over ‘⁠main.vars⁠’, i.e., if any value is provided, the variable names will not be used as title of the plot(s). For fdt.multiple, the value should be a vector of characters, in this case, the R's recycling rule will be used.
main.vars	logical flag: should the variables names be added as title of each plot (default TRUE)?
x.round	a numeric value to round the ‘⁠x⁠’ ticks: ‘⁠0:⁠’ parallel to the axes, ‘⁠1:⁠’ horizontal, ‘⁠2:⁠’ perpendicular to the axes, ‘⁠3:⁠’ vertical.
box	if TRUE (the default), a box will be placed on the graphic. Only for categorical variables.
grouped	if TRUE, the lines of polygon types will be plotted on the same graphic. It works only if the by argument is used.
args.legend	list of additional arguments to be passed to legend; names of the list are used as argument names. Only used if grouped=TRUE. The default is NULL.
...	optional plotting parameters.

Details

The result is a single histogram or polygon (absolute, relative or cumulative) for fdt.default or a set of histograms or polygons (absolute, relative or cumulative) for fdt.multiple objects. Both ‘⁠default and multiple⁠’ try to compute the maximum number of histograms that will fit on one page, then it draws a matrix of histograms. More than one graphical device may be opened to show all histograms.

The result is a single bar plot, polygon, dot chart (absolute, relative or cumulative) and Pareto chart for fdt_cat.default or a set of the same graphs for fdt_cat.multiple objects. Both ‘⁠default and multiple⁠’ try to compute the maximum number of histograms that will fit on one page, then it draws a matrix of graphs listed above. More than one graphical device may be opened to show all graphs.

Author(s)

Faria, J. C.
Allaman, I. B
Jelihovschi, E. G.

Examples

library(fdth)

#===============================
# Vectors: univariate numerical
#===============================
x <- rnorm(n=1e3,
           mean=5,
           sd=1)

(ft <- fdt(x))

# Histograms
plot(ft)  # Absolute frequency histogram

plot(ft,
     main='My title')

plot(ft,
     x.round=3,
     col='darkgreen')

plot(ft,
     xlas=2)

plot(ft,
     x.round=3,
     xlas=2,
     xlab=NULL)

plot(ft,
     v=TRUE, 
     cex=.8,
     x.round=3,
     xlas=2,
     xlab=NULL,
     col=rainbow(11))

plot(ft,
     type='fh')    # Absolute frequency histogram

plot(ft,
     type='rfh')   # Relative frequency histogram

plot(ft,
     type='rfph')  # Relative frequency (%) histogram

plot(ft,
     type='cdh')   # Cumulative density histogram

plot(ft,
     type='cfh')   # Cumulative frequency histogram

plot(ft,
     type='cfph')  # Cumulative frequency (%) histogram

# Polygons
plot(ft,
     type='fp')    # Absolute frequency polygon

plot(ft,
     type='rfp')   # Relative frequency polygon

plot(ft,
     type='rfpp')  # Relative frequency (%) polygon

plot(ft,
     type='cdp')   # Cumulative density polygon

plot(ft,
     type='cfp')   # Cumulative frequency polygon

plot(ft,
     type='cfpp')  # Cumulative frequency (%) polygon

# Density
plot(ft,
     type='d')     # Density

# Theoretical curve and fdt
x <- rnorm(1e5,
           mean=5,
           sd=1)

plot(fdt(x,
         k=100), 
     type='d', 
     col=heat.colors(100))

curve(dnorm(x,
            mean=5,
            sd=1),
      col='darkgreen',
      add=TRUE,
      lwd=3)


#=================================
# Vectors: univariate categorical
#=================================
x <- sample(letters[1:5],
            1e3,
            rep=TRUE)

(ft.c <- fdt_cat(x))

# Barplot: the default
plot(ft.c)

# Barplot
plot(ft.c,
     type='fb')

# Polygon
plot(ft.c,
     type='fp')

# Dotchart
plot(ft.c,
     type='fd')

# Pareto chart
plot(ft.c,
     type='pa')

#======================================================
# Data.frames: multivariate with categorical variables
#======================================================
mdf <- data.frame(X1=rep(LETTERS[1:4], 25),
                  X2=as.factor(rep(1:10, 10)),
                  Y1=c(NA, NA, rnorm(96, 10, 1), NA, NA),
                  Y2=rnorm(100, 60, 4),
                  Y3=rnorm(100, 50, 4),
                  Y4=rnorm(100, 40, 4),
                  stringsAsFactors=TRUE)

str(mdf)

# Histograms
(ft <- fdt(mdf,
           na.rm=TRUE))

plot(ft,
     v=TRUE,
     cex=.8)

plot(ft,
     col='darkgreen',
     ylim=c(0, 40))

plot(ft,
     col=rainbow(8), 
     ylim=c(0, 40),
     main=LETTERS[1:4])

plot(ft,
     type='fh')

plot(ft,
     type='rfh')

plot(ft,
     type='rfph')

plot(ft,
     type='cdh')

plot(ft,
     type='cfh')

plot(ft,
     type='cfph')

# Polygons
plot(ft,
     v=TRUE,
     type='fp')

plot(ft,
     type='rfp')

plot(ft,
     type='rfpp')

plot(ft,
     type='cdp')

plot(ft,
     type='cfp')

plot(ft,
     type='cfpp') 

# Density
plot(ft,
     type='d')     

levels(mdf$X1)

plot(fdt(mdf,
         k=5,
         by='X1',
         na.rm=TRUE),
     ylim=c(0, 12))

levels(mdf$X2)

plot(fdt(mdf,
         breaks='FD', 
         by='X2',
         na.rm=TRUE))

plot(fdt(mdf,
         k=5,
         by='X2',
         na.rm=TRUE))  # It is difficult to compare

plot(fdt(mdf,
         k=5,
         by='X2',
         na.rm=TRUE),
     ylim=c(0, 8))  # Easy

plot(fdt(iris,
         k=5))

plot(fdt(iris,
         k=5),
     col=rainbow(5))

plot(fdt(iris, 
         k=5,
         by='Species'),
     v=TRUE)

ft <- fdt(iris,
          k=10)

plot(ft)

plot(ft,
     type='d')

# Categorical data 
(ft.c <- fdt_cat(mdf))
plot(ft.c)

plot(ft.c,
     type='fd',
     pch=19)

#========================
# Matrices: multivariate
#========================
plot(fdt(state.x77))

plot(fdt(volcano))

fdth documentation built on May 12, 2026, 1:08 a.m.