fdth (version 1.1-3)

summary.fdt: Summary and Print Methods for fdt Objects

Description

S3 methods to return (and print) a data.frame (the frequency distribution table - fdt) for fdt.default and fdt.multiple objects.

Usage

## S3 method for class 'fdt.default':
summary(object, columns=1:6, round=2,
    format.classes=FALSE, pattern="\%09.3e", \dots)
  ## S3 method for class 'fdt.multiple':
summary(object, columns=1:6, round=2,
    format.classes=FALSE, pattern="\%09.3e", \dots)
  ## S3 method for class 'fdt.default':
print(x, \dots)
  ## S3 method for class 'fdt.multiple':
print(x, \dots)

Arguments

object

A fdt object.

x

A fdt object.

columns

A vector of integers to select colums of the data.frame table.

round

Rounds the fractionary columns of fdt to the specified number of decimal places (default 2).

format.classes

Logical, if TRUE the first column of the data.frame table will be formated using regular expression. The default is "%09.3e".

pattern

Same as fmt in sprintf.

...

Potential further arguments (require by generic).

Value

• A single data.frame for fdt.default or multiple data.frames for fdt.multiple.

Details

The methods print and show are wrappers for the method summary. It is possible to select what columns of the table (a data.frame) will be shown, as well as the pattern of the first column. The columns are: 1 = Class limits, 2 = f (absolut frequency), 3 = rf (relative frequency), 4 = rf(%) (relative frequency, %), 5 = cf (cumulative frequency), 6 = cf(%) (cumulative frequency, %). The available parameters offer an easy and powerful way to format the fdt for publications and other purposes.

Examples

library (fdth)

#======================
# Vectors: univariated
#======================
set.seed(1)
x <- rnorm(n=1e3, mean=5, sd=1)

d <- fdt(x)
str(d)

d
summary(d) # the same
print(d)   # the same
show(d)    # the same
summary(d, format=TRUE)                   # It can not be what you want to publications!
summary(d, format=TRUE, pattern='%.2f')   # Huumm ..., good, but ... Can it be better?
summary(d,
        col=c(1:2, 4, 6),
        format=TRUE, pattern='%.2f')      # Yes, it can!

range(x)                                  # To know x
summary(fdt(x, start=1, end=9, h=1),
        col=c(1:2, 4, 6),
        format=TRUE, pattern='%d')        # Is it nice now?

d[['table']]                              # Stores the feq. dist. table (fdt)
d[['breaks']]                             # Stores the breaks of fdt
d[['breaks']]['start']                    # Stores the left value of the first class
d[['breaks']]['end']                      # Stores the right value of the last class
d[['breaks']]['h']                        # Stores the class interval
as.logical(d[['breaks']]['right'])        # Stores the right option

#=============================================
# Data.frames: multivariated with categorical
#=============================================
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))

d <- fdt(mdf)
d

str(d)
summary(d) # the same
print(d)   # the same
show(d)    # the same
summary(d, format=TRUE)
summary(d, format=TRUE, pattern='%05.2f') # regular expression
summary(d, col=c(1:2, 4, 6), format=TRUE, pattern='%05.2f')

print(d, col=c(1:2, 4, 6))
print(d, col=c(1:2, 4, 6), format=TRUE, pattern='%05.2f')

levels(mdf$X1)
summary(fdt(mdf, k=5, by='X1'))

levels(mdf$X2)
summary(fdt(mdf, breaks='FD', by='X2'), round=3)

summary(fdt(mdf, k=5, by='X2'), format=TRUE, round=3)

summary(fdt(iris, k=5), format=TRUE, patter='%04.2f')

levels(iris$Species)
summary(fdt(iris, k=5, by='Species'), format=TRUE, patter='%04.2f')

#=========================
# Matrices: multivariated
#=========================
summary(fdt(state.x77), col=c(1:2, 4, 6), format=TRUE)

summary(fdt(volcano, right=TRUE), col=c(1:2, 4, 6), round=3, format=TRUE,
  pattern='%05.1f')