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  • R-table和tapply函数

    table可统计数据的频数

    tapply可根据因子、向量和要计算的函数计算

    > class<-c(1,2,3,2,1,2,1,3)

    > class
    [1] 1 2 3

    > c(81,65,72,88,73,91,56,90)->student
    > class
    [1] 1 2 3 2 1 2 1 3

    >factor(class)->class


    > tapply(student,class,mean)
           1        2        3
    70.00000 81.33333 81.00000
    > tapply(student,class,min)
     1  2  3
    56 65 72


    > tapply(student,class,max)
     1  2  3
    81 91 90
    > table(class)
    class
    1 2 3
    3 3 2
    >  

    Apply a Function Over a Ragged Array

    Description

    Apply a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors.

    Usage

    tapply(X, INDEX, FUN = NULL, ..., simplify = TRUE)

    Arguments

    X

    an atomic object, typically a vector.

    INDEX

    list of factors, each of same length as X. The elements are coerced to factors by as.factor.

    FUN

    the function to be applied, or NULL. In the case of functions like +%*%, etc., the function name must be backquoted or quoted. If FUN is NULL, tapply returns a vector which can be used to subscript the multi-way array tapply normally produces.

    ...

    optional arguments to FUN: the Note section.

    simplify

    If FALSEtapply always returns an array of mode "list". If TRUE (the default), then if FUN always returns a scalar, tapply returns an array with the mode of the scalar.

    Value

    If FUN is not NULL, it is passed to match.fun, and hence it can be a function or a symbol or character string naming a function.

    When FUN is present, tapply calls FUN for each cell that has any data in it. If FUN returns a single atomic value for each such cell (e.g., functions mean or var) and when simplify is TRUE,tapply returns a multi-way array containing the values, and NA for the empty cells. The array has the same number of dimensions as INDEX has components; the number of levels in a dimension is the number of levels (nlevels()) in the corresponding component of INDEX. Note that if the return value has a class (e.g. an object of class "Date") the class is discarded.

    Note that contrary to S, simplify = TRUE always returns an array, possibly 1-dimensional.

    If FUN does not return a single atomic value, tapply returns an array of mode list whose components are the values of the individual calls to FUN, i.e., the result is a list with a dimattribute.

    When there is an array answer, its dimnames are named by the names of INDEX and are based on the levels of the grouping factors (possibly after coercion).

    For a list result, the elements corresponding to empty cells are NULL.

    Note

    Optional arguments to FUN supplied by the ... argument are not divided into cells. It is therefore inappropriate for FUN to expect additional arguments with the same length as X.

    References

    Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

    See Also

    the convenience functions by and aggregate (using tapply); applylapply with its versions sapplyand mapply.

    Examples

    require(stats) groups <- as.factor(rbinom(32, n = 5, prob = 0.4)) tapply(groups, groups, length) #- is almost the same as table(groups) ## contingency table from data.frame : array with named dimnames tapply(warpbreaks$breaks, warpbreaks[,-1], sum) tapply(warpbreaks$breaks, warpbreaks[, 3, drop = FALSE], sum) n <- 17; fac <- factor(rep(1:3, length = n), levels = 1:5) table(fac) tapply(1:n, fac, sum) tapply(1:n, fac, sum, simplify = FALSE) tapply(1:n, fac, range) tapply(1:n, fac, quantile) ## example of ... argument: find quarterly means tapply(presidents, cycle(presidents), mean, na.rm = TRUE) ind <- list(c(1, 2, 2), c("A", "A", "B")) table(ind) tapply(1:3, ind) #-> the split vector tapply(1:3, ind, sum)
    
    
    
    
    问题:

    有数万个数据,两列数据 一列为名称(A列 ) 一列为值(x列),一个名称可对应多个值,一个值可能有多个名称,具体问题如下所示
    A1 x1
    A2 x2
    A3 x3
    A4 x4
    A1 x5
    A2 x3
    A5 x6
    A1 x7

    想得到的结果,将A列名称唯一化,出现一个值对应多个值的列表,且想批量处理
    A1 x1 x5 x7
    A2 x2 x3
    A3 x3
    A4 x4
    A5 x6

    解决方案1:perl

    use strict;
    use warnings;

    my %hash;
    open OUT, "> lines.txt" or die"$!";

    while () {
    chomp;
    my ($line1,$line2) = split/s+/;
    push @{$hash{$line1}},$line2;
    }

    foreach my $key(sort keys %hash) {
    print OUT "$key @{$hash{$key}} ";
    }

    close OUT;
    __DATA__
    A1 x1
    A2 x2
    A3 x3
    A4 x4
    A1 x5
    A2 x3
    A5 x6

    A1 x7 
     
    解决方案2:R
    d = read.table("data.txt")
    tapply(d[,2], d[,1], print)
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  • 原文地址:https://www.cnblogs.com/awishfullyway/p/6633967.html
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