制作问题可重现的最佳方法之一是使用内置数据集.然而，使用 data() 令人沮丧，因为没有提供有关数据集结构的信息.

One of the best ways to make a question reproducible is to use one of the built in data sets. Using data(), however, is frustrating because no information about the structure of the data set is provided.

如何快速查看可用数据集的结构?

How can I quickly view the structure of available data sets?

推荐答案

以下函数可能会有所帮助:

The following function may help:

dataStr <- function(fun=function(x) TRUE)
  str(
    Filter(
      fun,
      Filter(
        Negate(is.null),
        mget(data()$results[, "Item"], inh=T, ifn=list(NULL))
  ) ) )

它接受一个过滤函数，将其应用于所有数据集，并打印出匹配数据集的结构.例如，如果我们正在寻找矩阵:

It accepts a filtering function, applies it to all the data sets, and prints out the structure of the matching data sets. For example, if we're looking for matrices:

> dataStr(is.matrix)
List of 8
 $ WorldPhones          : num [1:7, 1:7] 45939 60423 64721 68484 71799 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:7] "1951" "1956" "1957" "1958" ...
  .. ..$ : chr [1:7] "N.Amer" "Europe" "Asia" "S.Amer" ...
 $ occupationalStatus   : 'table' int [1:8, 1:8] 50 16 12 11 2 12 0 0 19 40 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ origin     : chr [1:8] "1" "2" "3" "4" ...
  .. ..$ destination: chr [1:8] "1" "2" "3" "4" ...
 $ volcano              : num [1:87, 1:61] 100 101 102 103 104 105 105 106 107 108 ...
--- 5 entries omitted ---

或者对于数据框(也省略条目):

Or for data frames (also omitting entries):

> dataStr(is.data.frame)
List of 42
 $ BOD             :'data.frame': 6 obs. of  2 variables:
  ..$ Time  : num [1:6] 1 2 3 4 5 7
  ..$ demand: num [1:6] 8.3 10.3 19 16 15.6 19.8
  ..- attr(*, "reference")= chr "A1.4, p. 270"
 $ CO2             :Classes ‘nfnGroupedData’, ‘nfGroupedData’, ‘groupedData’ and 'data.frame':  84 obs. of  5 variables:
  ..$ Plant    : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ...
  ..$ Type     : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ...
  ..$ Treatment: Factor w/ 2 levels "nonchilled","chilled": 1 1 1 1 1 1 1 1 1 1 ...
  ..$ conc     : num [1:84] 95 175 250 350 500 675 1000 95 175 250 ...
  ..$ uptake   : num [1:84] 16 30.4 34.8 37.2 35.3 39.2 39.7 13.6 27.3 37.1 ...
--- 40 entries omitted ---

甚至对于简单的向量:

> dataStr(function(x) is.atomic(x) && is.vector(x) && !is.ts(x))
List of 4
 $ euro   : Named num [1:11] 13.76 40.34 1.96 166.39 5.95 ...
  ..- attr(*, "names")= chr [1:11] "ATS" "BEF" "DEM" "ESP" ...
 $ islands: Named num [1:48] 11506 5500 16988 2968 16 ...
  ..- attr(*, "names")= chr [1:48] "Africa" "Antarctica" "Asia" "Australia" ...
 $ precip : Named num [1:70] 67 54.7 7 48.5 14 17.2 20.7 13 43.4 40.2 ...
  ..- attr(*, "names")= chr [1:70] "Mobile" "Juneau" "Phoenix" "Little Rock" ...
 $ rivers : num [1:141] 735 320 325 392 524 ...