DataFrame-class {IRanges}R Documentation

External Data Frame

Description

The DataFrame extends the DataTable virtual class and supports the storage of any type of object (with length and [ methods) as columns.

Details

On the whole, the DataFrame behaves very similarly to data.frame, in terms of construction, subsetting, splitting, combining, etc. The most notable exception is that the row names are optional. This means calling rownames(x) will return NULL if there are no row names. Of course, it could return seq_len(nrow(x)), but returning NULL informs, for example, combination functions that no row names are desired (they are often a luxury when dealing with large data).

As DataFrame derives from Sequence, it is possible to set an annotation string. Also, another DataFrame can hold metadata on the columns.

Accessors

In the following code snippets, x is a DataFrame.

dim(x): Get the length two integer vector indicating in the first and second element the number of rows and columns, respectively.
dimnames(x), dimnames(x) <- value: Get and set the two element list containing the row names (character vector of length nrow(x) or NULL) and the column names (character vector of length ncol(x)).

Subsetting

In the following code snippets, x is a DataFrame.

x[i,j,drop]: Behaves very similarly to the [.data.frame method, except i can be a logical Rle object and subsetting by matrix indices is not supported. Indices containing NA's are also not supported.
x[i,j] <- value: Behaves very similarly to the [<-.data.frame method.
x[[i]]: Behaves very similarly to the [[.data.frame method, except arguments j and exact are not supported. Column name matching is always exact. Subsetting by matrices is not supported.
x[[i]] <- value: Behaves very similarly to the [[<-.data.frame method, except argument j is not supported.

Constructor

DataFrame(..., row.names = NULL): Constructs a DataFrame in similar fashion to data.frame. Each argument in ... is coerced to a DataFrame and combined column-wise. No special effort is expended to automatically determine the row names from the arguments. The row names should be given in row.names; otherwise, there are no row names. This is by design, as row names are normally undesirable when data is large.

Splitting and Combining

In the following code snippets, x is a DataFrame.

split(x, f, drop = FALSE): Splits x into a CompressedSplitDataFrameList, according to f, dropping elements corresponding to unrepresented levels if drop is TRUE.
rbind(...): Creates a new DataFrame by combining the rows of the DataFrame objects in .... Very similar to rbind.data.frame, except in the handling of row names. If all elements have row names, they are concatenated and made unique. Otherwise, the result does not have row names. Currently, factors are not handled well (their levels are dropped). This is not a high priority until there is an XFactor class.
cbind(...): Creates a new DataFrame by combining the columns of the DataFrame objects in .... Very similar to cbind.data.frame, except row names, if any, are dropped. Consider the DataFrame as an alternative that allows one to specify row names.

Coercion

as(from, "DataFrame"): By default, constructs a new DataFrame with from as its only column. If from is a matrix or data.frame, all of its columns become columns in the new DataFrame. If from is a list, each element becomes a column, recycling as necessary. Note that for the DataFrame to behave correctly, each column object must support element-wise subsetting via the [ method and return the number of elements with length. It is recommended to use the DataFrame constructor, rather than this interface.
as.list(x): Coerces x, a DataFrame, to a list.
as.data.frame(x, row.names=NULL, optional=FALSE): Coerces x, a DataFrame, to a data.frame. Each column is coerced to a data.frame and then column bound together. If row.names is NULL, they are retrieved from x, if it has any. Otherwise, they are inferred by the data.frame constructor.

NOTE: conversion of x to a data.frame is not supported if x contains any list, SimpleList, or CompressedList columns.

as(from, "data.frame"): Coerces a DataFrame to a data.frame by calling as.data.frame(from).

Author(s)

Michael Lawrence

See Also

DataTable, Sequence, and RangedData, which makes heavy use of this class.

Examples

  score <- c(1L, 3L, NA)
  counts <- c(10L, 2L, NA)
  row.names <- c("one", "two", "three")
  
  df <- DataFrame(score) # single column
  df[["score"]]
  df <- DataFrame(score, row.names = row.names) #with row names
  rownames(df)
  
  df <- DataFrame(vals = score) # explicit naming
  df[["vals"]]
  
  # a data.frame
  sw <- DataFrame(swiss)
  as.data.frame(sw) # swiss, without row names
  # now with row names
  sw <- DataFrame(swiss, row.names = rownames(swiss))
  as.data.frame(sw) # swiss

  # subsetting
    
  sw[] # identity subset
  sw[,] # same

  sw[NULL] # no columns
  sw[,NULL] # no columns
  sw[NULL,] # no rows

  ## select columns
  sw[1:3]
  sw[,1:3] # same as above
  sw[,"Fertility"]
  sw[,c(TRUE, FALSE, FALSE, FALSE, FALSE, FALSE)]

  ## select rows and columns
  sw[4:5, 1:3]
  
  sw[1] # one-column DataFrame
  ## the same
  sw[, 1, drop = FALSE]
  sw[, 1] # a (unnamed) vector
  sw[[1]] # the same
  sw[["Fertility"]]

  sw[["Fert"]] # should return 'NULL'
  
  sw[1,] # a one-row DataFrame
  sw[1,, drop=TRUE] # a list

  ## duplicate row, unique row names are created
  sw[c(1, 1:2),]

  ## indexing by row names  
  sw["Courtelary",]
  subsw <- sw[1:5,1:4]
  subsw["C",] # partially matches

  ## row and column names
  cn <- paste("X", seq_len(ncol(swiss)), sep = ".")
  colnames(sw) <- cn
  colnames(sw)
  rn <- seq(nrow(sw))
  rownames(sw) <- rn
  rownames(sw)

  ## column replacement

  df[["counts"]] <- counts
  df[["counts"]]
  df[[3]] <- score
  df[["X"]]
  df[[3]] <- NULL # deletion

  ## split

  sw <- DataFrame(swiss)
  swsplit <- split(sw, sw[["Education"]])
  
  ## rbind

  do.call(rbind, as.list(swsplit))

  ## cbind

  cbind(DataFrame(score), DataFrame(counts))

[Package IRanges version 1.6.16 Index]