將描述性統計信息添加到分組數據集中

Question

我有一張表，其中描述性統計信息是使用從pastecs包創建的。然而，挑戰是我必須將這些結合到一個列表中，然後，我無法將它列入清單。我發現R list to data frame線程，但我必須創建一個臨時data.frame來完成這項工作。我處理的實際數據很大，並且不能真正允許創建臨時數據框。

以下是我的代碼： [您將需要pastecs包。它已經裝在我的系統。]

dput(df) 
structure(list(group = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 
4L), .Label = c("A", "B", "C", "D"), class = "factor"), dt = c(60, 
60, 63, 59, 63, 67, 71, 64, 65, 66, 68, 66, 71, 67, NA, 68, 56, 
NA, 60, 61, 63, 64, 63, 59)), .Names = c("group", "dt"), row.names = c(NA, 
-24L), class = "data.frame") 

#Convert to data.table 
data.table::setDT(df) 
df1<-df[,.(newvar = list(stat.desc(dt))),by=group] 

b<-data.frame(matrix(unlist(df1$newvar,use.names = TRUE), nrow=nrow(df1), byrow=T),stringsAsFactors = FALSE) 
names(b)<- names(df1$newvar[[1]]) 

df1$newvar<-NULL 
df1<-cbind(df1,b) 
rm(b) 

這裏的b是臨時表，與我不舒服。

預期輸出：

structure(list(group = structure(1:4, .Label = c("A", "B", "C", 
"D"), class = "factor"), nbr.val = c(4, 8, 6, 4), nbr.null = c(0, 
0, 0, 0), nbr.na = c(0, 0, 2, 0), min = c(59, 63, 56, 59), max = c(63, 
71, 71, 64), range = c(4, 8, 15, 5), sum = c(242, 530, 383, 249 
), median = c(60, 66, 64, 63), mean = c(60.5, 66.25, 63.8333333333333, 
62.25), SE.mean = c(0.866025403784439, 0.881354477089505, 2.32975916733421, 
1.10867789130417), CI.mean.0.95 = c(2.75607934655562, 2.08407217077572, 
5.9888365969565, 3.5283078589307), var = c(3, 6.21428571428571, 
32.5666666666667, 4.91666666666667), std.dev = c(1.73205080756888, 
2.49284690951645, 5.70672118354022, 2.21735578260835), coef.var = c(0.0286289389680806, 
0.0376278778794936, 0.0894003318570269, 0.0356201732145919)), .Names = c("group", 
"nbr.val", "nbr.null", "nbr.na", "min", "max", "range", "sum", 
"median", "mean", "SE.mean", "CI.mean.0.95", "var", "std.dev", 
"coef.var"), row.names = c(NA, -4L), class = "data.frame") 

對不起，如果這是太基本。我正在尋找更快的方法（即沒有中間表，最好是使用data.table的解決方案）。

謝謝你的時間。

Answer 1

stat.desc的輸出是帶有行名稱的data.frame。通過使用keep.rownames = TRUE參數它都可以在一個單一的代碼行完成轉換，要一個data.table（以產生一個長形），然後dcast到預期寬輸出：

library(data.table) 
library(pastecs) 
df <- structure(list(group = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 
    4L), .Label = c("A", "B", "C", "D"), class = "factor"), dt = c(60, 
    60, 63, 59, 63, 67, 71, 64, 65, 66, 68, 66, 71, 67, NA, 68, 56, 
    NA, 60, 61, 63, 64, 63, 59)), .Names = c("group", "dt"), row.names = c(NA, 
    -24L), class = "data.frame") 

#Convert to data.table 
dt <- data.table(df) 
# stat.desc returns data.frame with row.names - convert to DT and keep row names 
dt_melt <- dt[, data.table(stat.desc(.SD), keep.rownames = TRUE), by = .(group)] 
# Cast to wide format with group as ID variable and each row name as a column 
out <- dcast(dt_melt, group~rn, value.var = "dt") 

的輸出是：

group CI.mean.0.95 SE.mean coef.var max  mean median min nbr.na nbr.null nbr.val range std.dev sum  var 
1:  A  2.756079 0.8660254 0.02862894 63 60.50000  60 59  0  0  4  4 1.732051 242 3.000000 
2:  B  2.084072 0.8813545 0.03762788 71 66.25000  66 63  0  0  8  8 2.492847 530 6.214286 
3:  C  5.988837 2.3297592 0.08940033 71 63.83333  64 56  2  0  6 15 5.706721 383 32.566667 
4:  D  3.528308 1.1086779 0.03562017 64 62.25000  63 59  0  0  4  5 2.217356 249 4.916667