改掉 Tapply 瘾君子的习惯

发布于 2024-08-05 08:51:20 字数 1876 浏览 9 评论 0 原文

我通过玩弄的方式学习了 R,并且我开始认为我正在滥用 tapply 函数。是否有更好的方法来执行以下某些操作?诚然,它们确实有效,但随着它们变得越来越复杂,我想知道我是否失去了更好的选择。我正在寻找一些批评,在这里:

tapply(var1, list(fac1, fac2), mean, na.rm=T)

tapply(var1, fac1, sum, na.rm=T) / tapply(var2, fac1, sum, na.rm=T)

cumsum(tapply(var1, fac1, sum, na.rm=T)) / sum(var1)

更新:这是一些示例数据...

     var1    var2 fac1           fac2
1      NA  275.54   10      (266,326]
2      NA  565.89   10      (552,818]
3      NA  815.41    6      (552,818]
4      NA  281.77    6      (266,326]
5      NA  640.24   NA      (552,818]
6      NA   78.42   NA     [78.4,266]
7      NA 1027.06   NA (818,1.55e+03]
8      NA  355.20   NA      (326,552]
9      NA  464.52   NA      (326,552]
10     NA 1397.11   10 (818,1.55e+03]
11     NA  229.82   NA     [78.4,266]
12     NA  542.77   NA      (326,552]
13     NA  829.32   NA (818,1.55e+03]
14     NA  284.78   NA      (266,326]
15     NA  194.97   10     [78.4,266]
16     NA  672.55    8      (552,818]
17     NA  348.01   10      (326,552]
18     NA 1550.79    9 (818,1.55e+03]
19 101.98  101.98    4     [78.4,266]
20     NA  292.80    6      (266,326]

更新数据转储:

structure(list(var1 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, 101.98, NA), var2 = c(275.54, 
565.89, 815.41, 281.77, 640.24, 78.42, 1027.06, 355.2, 464.52, 
1397.11, 229.82, 542.77, 829.32, 284.78, 194.97, 672.55, 348.01, 
1550.79, 101.98, 292.8), fac1 = c(10L, 10L, 6L, 6L, NA, NA, NA, 
NA, NA, 10L, NA, NA, NA, NA, 10L, 8L, 10L, 9L, 4L, 6L), fac2 = structure(c(2L, 
4L, 4L, 2L, 4L, 1L, 5L, 3L, 3L, 5L, 1L, 3L, 5L, 2L, 1L, 4L, 3L, 
5L, 1L, 2L), .Label = c("[78.4,266]", "(266,326]", "(326,552]", 
"(552,818]", "(818,1.55e+03]"), class = "factor")), .Names = c("var1", 
"var2", "fac1", "fac2"), row.names = c(NA, -20L), class = "data.frame")

I've learned R by toying, and I'm starting to think that I'm abusing the tapply function. Are there better ways to do some of the following actions? Granted, they work, but as they get more complex I wonder if I'm losing out on better options. I'm looking for some criticism, here:

tapply(var1, list(fac1, fac2), mean, na.rm=T)

tapply(var1, fac1, sum, na.rm=T) / tapply(var2, fac1, sum, na.rm=T)

cumsum(tapply(var1, fac1, sum, na.rm=T)) / sum(var1)

Update: Here's some example data...

     var1    var2 fac1           fac2
1      NA  275.54   10      (266,326]
2      NA  565.89   10      (552,818]
3      NA  815.41    6      (552,818]
4      NA  281.77    6      (266,326]
5      NA  640.24   NA      (552,818]
6      NA   78.42   NA     [78.4,266]
7      NA 1027.06   NA (818,1.55e+03]
8      NA  355.20   NA      (326,552]
9      NA  464.52   NA      (326,552]
10     NA 1397.11   10 (818,1.55e+03]
11     NA  229.82   NA     [78.4,266]
12     NA  542.77   NA      (326,552]
13     NA  829.32   NA (818,1.55e+03]
14     NA  284.78   NA      (266,326]
15     NA  194.97   10     [78.4,266]
16     NA  672.55    8      (552,818]
17     NA  348.01   10      (326,552]
18     NA 1550.79    9 (818,1.55e+03]
19 101.98  101.98    4     [78.4,266]
20     NA  292.80    6      (266,326]

Update data dump:

structure(list(var1 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, 101.98, NA), var2 = c(275.54, 
565.89, 815.41, 281.77, 640.24, 78.42, 1027.06, 355.2, 464.52, 
1397.11, 229.82, 542.77, 829.32, 284.78, 194.97, 672.55, 348.01, 
1550.79, 101.98, 292.8), fac1 = c(10L, 10L, 6L, 6L, NA, NA, NA, 
NA, NA, 10L, NA, NA, NA, NA, 10L, 8L, 10L, 9L, 4L, 6L), fac2 = structure(c(2L, 
4L, 4L, 2L, 4L, 1L, 5L, 3L, 3L, 5L, 1L, 3L, 5L, 2L, 1L, 4L, 3L, 
5L, 1L, 2L), .Label = c("[78.4,266]", "(266,326]", "(326,552]", 
"(552,818]", "(818,1.55e+03]"), class = "factor")), .Names = c("var1", 
"var2", "fac1", "fac2"), row.names = c(NA, -20L), class = "data.frame")

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喜爱皱眉﹌ 2024-08-12 08:51:20

对于第 1 部分,我更喜欢聚合,因为它以更像 R 的每行一个观察的格式保存数据。

聚合(var1,列表(fac1,fac2),平均值,na.rm=T)

For part 1 I prefer aggregate because it keeps the data in a more R-like one observation per row format.

aggregate(var1, list(fac1, fac2), mean, na.rm=T)

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