如何聚合列表中的所有数据？
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【中文标题】如何聚合列表中的所有数据？【英文标题】：How to aggregate all data in a list? 【发布时间】：2020-07-20 17:45:05 【问题描述】：这是我的示例数据；
z1<-list(`Cluster 1` = structure(list(Day_1 = structure(c(Hour_1 = 0,
Hour_2 = 0, Hour_3 = 0, Hour_4 = 0, Hour_5 = 0, Hour_6 = 0, Hour_7 = 0,
Hour_8 = 0, Hour_9 = 0, Hour_10 = 0, Hour_11 = 0, Hour_12 = 0,
Hour_13 = 0, Hour_14 = 0, Hour_15 = 0, Hour_16 = 0, Hour_17 = 0,
Hour_18 = 0.041, Hour_19 = 0.673, Hour_20 = 0, Hour_21 = 0, Hour_22 = 0,
Hour_23 = 0.319, Hour_24 = 0.447), .Dim = 24L, .Dimnames = list(
c("Hour_1", "Hour_2", "Hour_3", "Hour_4", "Hour_5", "Hour_6",
"Hour_7", "Hour_8", "Hour_9", "Hour_10", "Hour_11", "Hour_12",
"Hour_13", "Hour_14", "Hour_15", "Hour_16", "Hour_17", "Hour_18",
"Hour_19", "Hour_20", "Hour_21", "Hour_22", "Hour_23", "Hour_24"
))), Day_2 = structure(c(Hour_1 = 1.07, Hour_2 = 0, Hour_3 = 0,
Hour_4 = 0, Hour_5 = 0, Hour_6 = 1.27, Hour_7 = 0.19, Hour_8 = 0,
Hour_9 = 0, Hour_10 = 0, Hour_11 = 0, Hour_12 = 0, Hour_13 = 0,
Hour_14 = 0, Hour_15 = 0, Hour_16 = 0, Hour_17 = 0, Hour_18 = 0,
Hour_19 = 0, Hour_20 = 0, Hour_21 = 0, Hour_22 = 0, Hour_23 = 0,
Hour_24 = 0), .Dim = 24L, .Dimnames = list(c("Hour_1", "Hour_2",
"Hour_3", "Hour_4", "Hour_5", "Hour_6", "Hour_7", "Hour_8", "Hour_9",
"Hour_10", "Hour_11", "Hour_12", "Hour_13", "Hour_14", "Hour_15",
"Hour_16", "Hour_17", "Hour_18", "Hour_19", "Hour_20", "Hour_21",
"Hour_22", "Hour_23", "Hour_24")))), .Dim = 2L, .Dimnames = list(
c("Day_1", "Day_2"))), `Cluster 2` = structure(list(Day_3 = structure(c(Hour_1 = 0,
Hour_2 = 0, Hour_3 = 0, Hour_4 = 0, Hour_5 = 0, Hour_6 = 0, Hour_7 = 0,
Hour_8 = 0, Hour_9 = 0, Hour_10 = 0, Hour_11 = 0, Hour_12 = 0,
Hour_13 = 0, Hour_14 = 0, Hour_15 = 0, Hour_16 = 0, Hour_17 = 0.189,
Hour_18 = 0.001, Hour_19 = 0, Hour_20 = 0, Hour_21 = 0, Hour_22 = 0,
Hour_23 = 0, Hour_24 = 0), .Dim = 24L, .Dimnames = list(c("Hour_1",
"Hour_2", "Hour_3", "Hour_4", "Hour_5", "Hour_6", "Hour_7", "Hour_8",
"Hour_9", "Hour_10", "Hour_11", "Hour_12", "Hour_13", "Hour_14",
"Hour_15", "Hour_16", "Hour_17", "Hour_18", "Hour_19", "Hour_20",
"Hour_21", "Hour_22", "Hour_23", "Hour_24"))), Day_4 = structure(c(Hour_1 = 0,
Hour_2 = 0.521, Hour_3 = 0.229, Hour_4 = 0, Hour_5 = 0, Hour_6 = 0,
Hour_7 = 0, Hour_8 = 0, Hour_9 = 0, Hour_10 = 0, Hour_11 = 0,
Hour_12 = 0, Hour_13 = 0, Hour_14 = 0, Hour_15 = 0, Hour_16 = 0,
Hour_17 = 0, Hour_18 = 0, Hour_19 = 0, Hour_20 = 0, Hour_21 = 0,
Hour_22 = 0, Hour_23 = 0, Hour_24 = 0), .Dim = 24L, .Dimnames = list(
c("Hour_1", "Hour_2", "Hour_3", "Hour_4", "Hour_5", "Hour_6",
"Hour_7", "Hour_8", "Hour_9", "Hour_10", "Hour_11", "Hour_12",
"Hour_13", "Hour_14", "Hour_15", "Hour_16", "Hour_17", "Hour_18",
"Hour_19", "Hour_20", "Hour_21", "Hour_22", "Hour_23", "Hour_24"
)))), .Dim = 2L, .Dimnames = list(c("Day_3", "Day_4"))))
例如，我可以用下面的代码聚合第一个列表元素(z1$`Cluster 1`$Day_1)；
agg<-lapply(c(2, 3, 4), function(xx) tapply(z1$`Cluster 1`$Day_1, as.integer(gl(24, xx, 24) ), FUN = sum))
但是当我尝试将此函数应用于所有列表元素时出现错误。
我应该怎么做才能在一个函数中聚合所有列表元素？
【问题讨论】：
【参考方案1】：您可能应该考虑重组数据，因为嵌套列表可能会变得过于复杂。
这是对当前表单中的数据执行此操作的一种方法。
lapply(z1, function(x) lapply(x, function(y)
lapply(c(2, 3, 4), function(xx)
tapply(y, as.integer(gl(24, xx, 24)), FUN = sum))))
#$`Cluster 1`
#$`Cluster 1`$Day_1
#$`Cluster 1`$Day_1[[1]]
# 1 2 3 4 5 6 7 8 9 10 11 12
#0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.041 0.673 0.000 0.766
#$`Cluster 1`$Day_1[[2]]
# 1 2 3 4 5 6 7 8
#0.000 0.000 0.000 0.000 0.000 0.041 0.673 0.766
#$`Cluster 1`$Day_1[[3]]
# 1 2 3 4 5 6
#0.000 0.000 0.000 0.000 0.714 0.766
#...
#...
【讨论】：
【参考方案2】：使用rapply。
res <- rapply(z1, function(x)
lapply(2:4, function(xx) tapply(x, as.integer(gl(24, xx, 24)), sum)), how="list")
res[[1]]
# $Day_1
# $Day_1[[1]]
# 1 2 3 4 5 6 7 8 9 10 11 12
# 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.041 0.673 0.000 0.766
#
# $Day_1[[2]]
# 1 2 3 4 5 6 7 8
# 0.000 0.000 0.000 0.000 0.000 0.041 0.673 0.766
#
# $Day_1[[3]]
# 1 2 3 4 5 6
# 0.000 0.000 0.000 0.000 0.714 0.766
#
#
# $Day_2
# $Day_2[[1]]
# 1 2 3 4 5 6 7 8 9 10 11 12
# 1.07 0.00 1.27 0.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
#
# $Day_2[[2]]
# 1 2 3 4 5 6 7 8
# 1.07 1.27 0.19 0.00 0.00 0.00 0.00 0.00
#
# $Day_2[[3]]
# 1 2 3 4 5 6
# 1.07 1.46 0.00 0.00 0.00 0.00
【讨论】：
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