data.frame               package:base               R Documentation

_D_a_t_a _F_r_a_m_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function creates data frames, tightly coupled collections of
     variables which share many of the properties of matrices and of
     lists, used as the fundamental data structure by most of R's
     modeling software.

_U_s_a_g_e:

     data.frame(..., row.names = NULL, check.rows = FALSE,
                check.names = TRUE,
                stringsAsFactors = default.stringsAsFactors())

     default.stringsAsFactors()

_A_r_g_u_m_e_n_t_s:

     ...: these arguments are of either the form 'value' or 'tag =
          value'.  Component names are created based on the tag (if
          present) or the deparsed argument itself.

row.names: 'NULL' or a single integer or character string specifying a
          column to be used as row names, or a character or integer
          vector giving the row names for the data frame.

check.rows: if 'TRUE' then the rows are checked for consistency of
          length and names.

check.names: logical.  If 'TRUE' then the names of the variables in the
          data frame are checked to ensure that they are syntactically
          valid variable names and are not duplicated. If necessary
          they are adjusted (by 'make.names') so that they are.

stringsAsFactors: logical: should character vectors be converted to
          factors?  The 'factory-fresh' default is 'TRUE', but this can
          be changed by setting 'options(stringsAsFactors = FALSE)'.

_D_e_t_a_i_l_s:

     A data frame is a list of variables of the same length with unique
     row names, given class '"data.frame"'.  If there are zero
     variables, the row names determine the number of rows.

     Duplicate column names are allowed, but you need to use
     'check.names=FALSE' for 'data.frame' to generate such a data
     frame.  However, not all operations on data frames will preserve
     duplicated column names: for example matrix-like subsetting will
     force column names in the result to be unique.

     'data.frame' converts each of its arguments to a data frame by
     calling 'as.data.frame(optional=TRUE)'.  As that is a generic
     function, methods can be written to change the behaviour of
     arguments according to their classes: R comes with many such
     methods. Character variables passed to 'data.frame' are converted
     to factor columns unless protected by 'I'.  If a list or data
     frame or matrix is passed to 'data.frame' it is as if each
     component or column had been passed as a separate argument (except
     for matrices of class '"model.matrix"' and those protected by
     'I').

     Objects passed to 'data.frame' should have the same number of
     rows, but atomic vectors, factors and character vectors protected
     by 'I' will be recycled a whole number of times if necessary.

     If row names are not supplied in the call to 'data.frame', the row
     names are taken from the first component that has suitable names,
     for example a named vector or a matrix with rownames or a data
     frame. (If that component is subsequently recycled, the names are
     discarded with a warning.)  If 'row.names' was supplied as 'NULL'
     or no suitable component was found the row names are the integer
     sequence starting at one (and such row names are considered to be
     'automatic', and not preserved by 'as.matrix').

     If row names are supplied of length one and the data frame has a
     single row, the 'row.names' is taken to specify the row names and
     not a column (by name or number).

     Names are removed from vector inputs not protected by 'I'.

     'default.stringsAsFactors' is a utility that takes
     'getOption("stringsAsFactors")' and ensures the result is 'TRUE'
     or 'FALSE' (or throws an error if the value is not 'NULL').

_V_a_l_u_e:

     A data frame, a matrix-like structure whose columns may be of
     differing types (numeric, logical, factor and character and so
     on).

     How the names of the data frame are created is complex, and the
     rest of this paragraph is only the basic story.  If the arguments
     are all named and simple objects (not lists, matrices of data
     frames) then the argument names give the column names.  For an
     unnamed simple argument, a deparsed version of the argument is
     used as the name (with an enclosing 'I(...)' removed).  For a
     named matrix/list/data frame argument with ore than one named
     column, the names of the columns are the name of the argument
     followed by a dot and the column name inside the argument: if the
     argument is unnamed, the argument's column names are used.  For a
     named or unnamed matrix/list/data frame argument that contains a
     single column, the column name in the result is the column name in
     the argument.  Finally, the names are adjusted to be unique and
     syntactically valid unless 'check.names = FALSE'.

_N_o_t_e:

     In versions of R prior to 2.4.0 'row.names' had to be character:
     to ensure compatibility with earlier versions of R, supply a
     character vector as the 'row.names' argument.

_R_e_f_e_r_e_n_c_e_s:

     Chambers, J. M. (1992) _Data for models._ Chapter 3 of
     _Statistical Models in S_ eds J. M. Chambers and T. J. Hastie,
     Wadsworth & Brooks/Cole.

_S_e_e _A_l_s_o:

     'I', 'plot.data.frame', 'print.data.frame', 'row.names', 'names'
     (for the column names), '[.data.frame' for subsetting methods,
     'Math.data.frame' etc, about _Group_ methods for 'data.frame's;
     'read.table', 'make.names'.

_E_x_a_m_p_l_e_s:

     L3 <- LETTERS[1:3]
     (d <- data.frame(cbind(x=1, y=1:10), fac=sample(L3, 10, replace=TRUE)))

     ## The same with automatic column names:
     data.frame(cbind(  1,   1:10),     sample(L3, 10, replace=TRUE))

     is.data.frame(d)

     ## do not convert to factor, using I() :
     (dd <- cbind(d, char = I(letters[1:10])))
     rbind(class=sapply(dd, class), mode=sapply(dd, mode))

     stopifnot(1:10 == row.names(d))# {coercion}

     (d0  <- d[, FALSE]) # NULL data frame with 10 rows
     (d.0 <- d[FALSE, ]) # <0 rows> data frame  (3 cols)
     (d00 <- d0[FALSE,])  # NULL data frame with 0 rows

