edd*_*ddi 15 r dplyr data.table
我不确定使用哪个函数来执行以下操作:
library(data.table)
dt = data.table(a = 1:4, b = 1:2)
dt[, rep(a[1], 3), by = b]
# b V1
#1: 1 1
#2: 1 1
#3: 1 1
#4: 2 2
#5: 2 2
#6: 2 2
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双方summarise并mutate不满意这个长度:
library(dplyr)
df = data.frame(a = 1:4, b = 1:2)
df %.% group_by(b) %.% summarise(rep(a[1], 3))
#Error: expecting a single value
df %.% group_by(b) %.% mutate(rep(a[1], 3))
#Error: incompatible size (3), expecting 2 (the group size) or 1
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tal*_*lat 13
在dplyr0.2版中,您可以使用do运算符执行此操作:
> df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3)))
#Source: local data frame [6 x 2]
#Groups: b
#
# b a
#1 1 1
#2 1 1
#3 1 1
#4 2 2
#5 2 2
#6 2 2
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虽然@ beginneR的答案确实有效,但它似乎并不是data.table行为的真正替代品.考虑:
df <- data.frame(a = 1, b = rep(1:1e4, 2))
dt <- data.table(df)
microbenchmark(times=5,
dt[, rep(a[1], 3), by = b],
df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3)))
)
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有dplyr实施> 200X慢.
Unit: milliseconds
expr min lq median uq
dt[, rep(a[1], 3), by = b] 13.14318 13.70248 14.60524 15.26676
df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3))) 3269.40731 3359.11614 3583.19430 3736.67162
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也许有更好的方法来做到这一点,do不需要调用data.frame每个do?此外,语法有点涉及到非常简单的东西data.table.
否则,根据Hadley的问题链接,似乎预计将dplyr在3.1中实现,这看起来是下一个版本.