Question

我想使用data.table作为aggregate()或ddply()的替代方法，因为这两种方法无法像希望的那样有效地扩展到大型对象。不幸的是，我还没有弄清楚如何让向量返回聚合函数在data.table的结果中生成多个列。例如：

# required packages
library(plyr)
library(data.table)

# simulated data
x <- data.table(value=rnorm(100), g=rep(letters[1:5], each=20))

# ddply output that I would like to get from data.table
ddply(data.frame(x), 'g', function(i) quantile(i$value))

 g        0%        25%          50%       75%     100%
 1 a -1.547495 -0.7842795  0.202456288 0.6098762 2.223530
 2 b -1.366937 -0.4418388 -0.085876995 0.7826863 2.236469
 3 c -2.064510 -0.6411390 -0.257526983 0.3213343 1.039053
 4 d -1.773933 -0.5493362 -0.007549273 0.4835467 2.116601
 5 e -0.780976 -0.2315245  0.194869630 0.6698881 2.207800

# not quite what I am looking for:
x[, quantile(value), by=g]

g           V1
1: a -1.547495345
2: a -0.784279536
3: a  0.202456288
4: a  0.609876241
5: a  2.223529739
6: b -1.366937074
7: b -0.441838791
8: b -0.085876995
9: b  0.782686277
10: b  2.236468703

基本上，ddply和aggregate的输出采用宽格式，而data.table的输出采用长格式。答案是重塑数据，还是我的data.table对象的其他参数？

Answer 1

尝试强制进入列表：

> x[, as.list(quantile(value)), by=g]
   g         0%          25%         50%       75%     100%
1: a -1.7507334 -0.632331909  0.07435249 0.7459778 1.428552
2: b -2.2043481 -0.005652353  0.10534325 0.5769475 1.241754
3: c -1.9313985 -1.120737610 -0.26116926 0.6953009 1.360017
4: d -0.7434664 -0.055232431  0.22062823 1.1864389 3.021124
5: e -2.0101657 -0.468674094  0.20209610 0.6286448 2.433152

从data.table聚合返回多个列

1 个答案: