R 扩展与dcast

我有一张这样的桌子

> head(dt2)
  Weight Height   Fitted interval limit    value
1   65.6  174.0 71.91200     pred   lwr 53.73165
2   80.7  193.5 91.63237     pred   lwr 73.33198
3   72.6  186.5 84.55326     pred   lwr 66.31751
4   78.8  187.2 85.26117     pred   lwr 67.02004
5   74.8  181.5 79.49675     pred   lwr 61.29244
6   86.4  184.0 82.02501     pred   lwr 63.80652

> head(reshape2::dcast(dt2, 
         Weight + Height + Fitted + interval ~ limit, 
         fun.aggregate = mean))
  Weight Height   Fitted interval      lwr      upr
1   42.0  153.4 51.07920     conf 49.15463 53.00376
2   42.0  153.4 51.07920     pred 32.82122 69.33717
3   43.2  160.0 57.75378     conf 56.35240 59.15516
4   43.2  160.0 57.75378     pred 39.54352 75.96404
5   44.8  149.5 47.13512     conf 44.87642 49.39382
6   44.8  149.5 47.13512     pred 28.83891 65.43133

我希望它像这样

> head(dt2)
  Weight Height   Fitted interval limit    value
1   65.6  174.0 71.91200     pred   lwr 53.73165
2   80.7  193.5 91.63237     pred   lwr 73.33198
3   72.6  186.5 84.55326     pred   lwr 66.31751
4   78.8  187.2 85.26117     pred   lwr 67.02004
5   74.8  181.5 79.49675     pred   lwr 61.29244
6   86.4  184.0 82.02501     pred   lwr 63.80652

> head(reshape2::dcast(dt2, 
         Weight + Height + Fitted + interval ~ limit, 
         fun.aggregate = mean))
  Weight Height   Fitted interval      lwr      upr
1   42.0  153.4 51.07920     conf 49.15463 53.00376
2   42.0  153.4 51.07920     pred 32.82122 69.33717
3   43.2  160.0 57.75378     conf 56.35240 59.15516
4   43.2  160.0 57.75378     pred 39.54352 75.96404
5   44.8  149.5 47.13512     conf 44.87642 49.39382
6   44.8  149.5 47.13512     pred 28.83891 65.43133

但是使用

tidyr:：spread

，我该怎么做呢

我用的是

> tidyr::spread(dt2, limit, value)

但是得到了错误

Error: Duplicate identifiers for rows (1052, 1056), (238, 242), (1209, 1218), (395, 404), (839, 1170), (25, 356), (1173, 1203, 1215), (359, 389, 401), (1001, 1200), (187, 386), (906, 907), (92, 93), (930, 1144), (116, 330), (958, 1171), (144, 357), (902, 1018), (88, 204), (960, 1008), (146, 194), (1459, 1463), (645, 649), (1616, 1625), (802, 811), (1246, 1577), (432, 763), (1580, 1610, 1622), (766, 796, 808), (1408, 1607), (594, 793), (1313, 1314), (499, 500), (1337, 1551), (523, 737), (1365, 1578), (551, 764), (1309, 1425), (495, 611), (1367, 1415), (553, 601)

随机10行：：

> dt[sample(nrow(dt), 10), ]
     Weight Height   Fitted interval limit    value
1253   52.2  162.5 60.28203     conf   upr 61.51087
426    49.1  158.8 56.54022     pred   upr 74.75756
1117   78.4  184.5 82.53066     conf   lwr 80.98778
1171   85.9  166.4 64.22611     conf   lwr 63.21254
948    61.4  177.8 75.75494     conf   lwr 74.66393
384    90.9  172.7 70.59731     pred   lwr 52.41828
289    75.9  172.7 70.59731     pred   lwr 52.41828
3      44.8  149.5 47.13512     pred   lwr 28.83891
774    87.3  182.9 80.91258     pred   upr 99.12445
772    86.4  175.3 73.22669     pred   upr 91.40919

---

假设您从如下数据开始：

mydf
#   Weight Height  Fitted interval limit    value
# 1     42  153.4 51.0792     conf   lwr 49.15463
# 2     42  153.4 51.0792     pred   lwr 32.82122
# 3     42  153.4 51.0792     conf   upr 53.00376
# 4     42  153.4 51.0792     pred   upr 69.33717
# 5     42  153.4 51.0792     conf   lwr 60.00000
# 6     42  153.4 51.0792     pred   lwr 90.00000

注意分组列（1到5）第5行和第6行中的重复。这基本上就是“tidyr”告诉你的。第一行和第五行是重复的，第二行和第六行也是重复的

tidyr::spread(mydf, limit, value)
# Error: Duplicate identifiers for rows (1, 5), (2, 6)

正如@Jaap所建议的，解决方案是首先“总结”数据。由于“tidyr”仅用于重塑数据（与“重塑2”不同，后者聚合并重塑数据），因此在更改数据表单之前，需要使用“dplyr”执行聚合。在这里，我用“值”列的

summary

实现了这一点

如果您在

summary

步骤停止执行，您会发现原来的6行数据集“缩小”为4行。现在，

spread

将按预期工作

mydf %>% 
  group_by(Weight, Height, Fitted, interval, limit) %>% 
  summarise(value = mean(value)) %>% 
  spread(limit, value)
# Source: local data frame [2 x 6]
# 
#   Weight Height  Fitted interval      lwr      upr
#    (dbl)  (dbl)   (dbl)    (chr)    (dbl)    (dbl)
# 1     42  153.4 51.0792     conf 54.57731 53.00376
# 2     42  153.4 51.0792     pred 61.41061 69.33717

这与

dcast

的预期输出与

fun.aggregate=mean

匹配

reshape2::dcast(mydf, Weight + Height + Fitted + interval ~ limit, fun.aggregate = mean)
#   Weight Height  Fitted interval      lwr      upr
# 1     42  153.4 51.0792     conf 54.57731 53.00376
# 2     42  153.4 51.0792     pred 61.41061 69.33717

---

样本数据：

 mydf <- structure(list(Weight = c(42, 42, 42, 42, 42, 42), Height = c(153.4, 
     153.4, 153.4, 153.4, 153.4, 153.4), Fitted = c(51.0792, 51.0792,         
     51.0792, 51.0792, 51.0792, 51.0792), interval = c("conf", "pred",        
     "conf", "pred", "conf", "pred"), limit = structure(c(1L, 1L,             
     2L, 2L, 1L, 1L), .Label = c("lwr", "upr"), class = "factor"),            
         value = c(49.15463, 32.82122, 53.00376, 69.33717, 60,          
         90)), .Names = c("Weight", "Height", "Fitted", "interval",     
     "limit", "value"), row.names = c(NA, 6L), class = "data.frame")   

---

mydf以下是
数据。表
是
dplyr
的替代方案。使用阿南达回答中的
mydf

library(data.table)
library(magrittr)
library(tidyr)

DT <- data.table(mydf)

如果此
limit==…
看起来太难编码，您可以先聚合为长格式，然后扩展
。这是因为一旦聚合，就不会有重复

DT[, .(value = mean(value)), by = .(Weight, Height, Fitted, interval, limit)] %>%
  spread(key = "limit", value = "value")

两者都能让你明白

#   Weight Height  Fitted interval      lwr      upr
#1:     42  153.4 51.0792     conf 54.57731 53.00376
#2:     42  153.4 51.0792     pred 61.41061 69.33717

您的示例在
limit
中不包含
upr
，在
interval
中也不包含
conf
，这意味着您的预期结果是不可再现的。为什么不将其保留为长格式，只进行聚合？请参阅base R、dplyr和data.table。虽然我已经用dcast完成了这项工作，但我想用tidyr完成这项工作只是为了学习@mtoto这只是我的数据集的一部分，我将对其进行编辑，为您提供一个随机样本，以确保再现性。这应该是有效的：
dt2%>%groupby（interval，limit）%%>%summary_each（funs（mean））%%>%spread（limit，value，-c（1:3））
按interval和limit进行汇总，只给了我两行。谢谢，实际上我说的是
dplyr
和
tidyr
。我已经用
reformae2
解决了这个问题，但我想知道如何使用这些特定的包。无论如何谢谢你！谢谢我在考虑如何处理聚合函数。我想Hadely希望将
tidyr
与
dplyr
一起使用。这是一个很好的答案，让我了解了
dcast
和
spread
之间的区别。非常感谢。