| print.fdt | R Documentation | 
S3 methods to return a data.frame (the frequency distribution table - fdt) 
for fdt.default and fdt.multiple objects; data.frame (the frequency
distribution table - fdt_cat) for fdt_cat.default and fdt_cat.multiple
objects.
## S3 methods
## S3 method for class 'fdt.default'
print(x,
      columns=1:6,
      round=2,
      format.classes=FALSE,
      pattern='%09.3e',
      row.names=FALSE,
      right=TRUE, ...)
## S3 method for class 'fdt.multiple'
print(x,
      columns=1:6,
      round=2,
      format.classes=FALSE,
      pattern='%09.3e',
      row.names=FALSE,
      right=TRUE, ...)
## S3 method for class 'fdt_cat.default'
print(x,
      columns=1:6,
      round=2,
      row.names=FALSE,
      right=TRUE, ...)
## S3 method for class 'fdt_cat.multiple'
print(x,
      columns=1:6,
      round=2,
      row.names=FALSE,
      right=TRUE, ...)
x | 
 a ‘fdt’ object.  | 
columns | 
 a   | 
round | 
 rounds ‘fdt’ columns to the specified number of decimal places (default 2).  | 
format.classes | 
 logical, if   | 
pattern | 
 same as   | 
row.names | 
 logical (or character vector), indicating whether (or what)
row names should be printed. The default is   | 
right | 
 logical, indicating whether or not strings should be right-aligned. The default is right-alignment.  | 
... | 
 potential further arguments (require by generic).  | 
For print.fdt, 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,
for print.fdt_cat it is only possible to select what columns of the table 
(a data.frame) will be shown. The columns are:
‘Class limits’
‘f’ - absolute frequency
‘rf’ - relative frequency
‘rf(%)’ - relative frequency, %
‘cf’ - cumulative frequency
‘cf(%)’ - cumulative frequency, %
The available parameters offer an easy and powerful way to format the ‘fdt’ for publications and other purposes.
A single data.frame for fdt.default and fdt.default or multiple
data.frames for fdt.multiple and fdt_cat.multiple.
Faria, J. C. 
Allaman, I. B 
Jelihovschi, E. G.
library (fdth)
#======================
# Vectors: univariated
#======================
set.seed(1)
x <- rnorm(n=1e3,
           mean=5,
           sd=1)
ft <- fdt(x)
str(ft)
ft
print(ft) # the same
print(ft,
      format=TRUE)      # It can not be what you want to publications!
print(ft,
      format=TRUE,
      pattern='%.2f')   # Huumm ..., good, but ... Can it be better?
print(ft,
      col=c(1:2, 4, 6),
      format=TRUE, 
      pattern='%.2f')   # Yes, it can!
range(x)                 # To know x
print(fdt(x,
          start=1,
          end=9,
          h=1),
      col=c(1:2, 4, 6),
      format=TRUE,
      pattern='%d')     # Is it nice now?
ft[['table']]                        # Stores the feq. dist. table (fdt)
ft[['breaks']]                       # Stores the breaks of fdt
ft[['breaks']]['start']              # Stores the left value of the first class
ft[['breaks']]['end']                # Stores the right value of the last class
ft[['breaks']]['h']                  # Stores the class interval
as.logical(ft[['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),
                  stringsAsFactors=TRUE)
                  
(ft <- fdt_cat(mdf))
                  
print(ft)
(ft <- fdt(mdf,
         na.rm=TRUE))
print(ft)
str(ft)
print(ft, # the s
      format=TRUE)
print(ft,
      format=TRUE,
      pattern='%05.2f')  # regular expression
print(ft,
      col=c(1:2, 4, 6), 
      format=TRUE, 
      pattern='%05.2f')
print(ft,
      col=c(1:2, 4, 6))
print(ft,
      col=c(1:2, 4, 6),
      format=TRUE,
      pattern='%05.2f')
levels(mdf$X1)
print(fdt(mdf,
          k=5,
          by='X1',
         na.rm=TRUE))
levels(mdf$X2)
print(fdt(mdf,
          breaks='FD',
          by='X2',
          na.rm=TRUE),
      round=3)
print(fdt(mdf,
          k=5,
          by='X2',
          na.rm=TRUE),
      format=TRUE,
      round=3)
print(fdt(iris,
          k=5),
      format=TRUE,
      patter='%04.2f')
levels(iris$Species)
print(fdt(iris,
          k=5,
          by='Species'),
      format=TRUE, 
      patter='%04.2f')
#=========================
# Matrices: multivariated
#=========================
print(fdt(state.x77), 
      col=c(1:2, 4, 6),
      format=TRUE)
print(fdt(volcano,
          right=TRUE),
      col=c(1:2, 4, 6),
      round=3,
      format=TRUE,
      pattern='%05.1f')
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