将长数据表重塑为宽数据表列表
我的问题是这里提出的问题的扩展
如何将数据从长格式重塑为宽格式，因此我将以类似的方式对其进行表述。
不同的是，我想将一个长数据表重新排列成一个list宽数据表。
dat <- data.table(
sim = rep(c(1,2), each=4),
time = rep(1:4, 2),
value1 = rnorm(8),
value2 = rnorm(8)
)
dat
sim time value1 value2
1 1 1 0.3407 0.5167
2 1 2 -0.7033 0.8416
3 1 3 -0.3795 -0.4717
4 1 4 -0.7460 0.8479
5 2 1 0.8981 -0.7163
6 2 2 -0.3347 -0.6849
7 2 3 0.5013 0.8941
8 2 4 -0.1745 0.0795
我想重塑它，以便我有一个list名为value1，value2...value99等的宽数据表...
l = list()
l[["value1"]]
sim 1 2 3 4
1 1 0.3407 -0.7033 -0.3795 -0.7460
5 2 -0.8981 -0.3347 -0.5013 -0.1745
l[["value2"]]
sim 1 2 3 4
1 1 0.5167 0.8416 -0.4717 0.8479
5 2 -0.7163 -0.6849 0.8941 0.0795
回答
两种变体。
数据表
library(data.table)
tmp <- dcast(melt(as.data.table(dat), id = c("sim", "time")), sim + variable ~ time)
tmp <- split(tmp, tmp$variable)
tmp <- lapply(tmp, set, i = NULL, j = "variable", value = NULL)
tmp
# $value1
# sim 1 2 3 4
# <num> <num> <num> <num> <num>
# 1: 1 1.0458737762 -0.4845954 0.1891288 0.05100633
# 2: 2 -0.0002406689 1.8093820 -0.8253280 1.14547045
# $value2
# sim 1 2 3 4
# <num> <num> <num> <num> <num>
# 1: 1 0.03157319 -0.8352058 -0.06876365 0.7467717
# 2: 2 -0.42551873 -0.7720822 0.15276411 0.9885968
我也经常使用magrittr::%>%with data.table，所以可以转换成
library(data.table)
library(magrittr) # if %>% is not already available
as.data.table(dat) %>%
melt(., id = c("sim", "time")) %>%
dcast(., sim + variable ~ time) %>%
split(., .$variable) %>%
lapply(., set, i = NULL, j = "variable", value = NULL)
# $value1
# sim 1 2 3 4
# <num> <num> <num> <num> <num>
# 1: 1 1.0458737762 -0.4845954 0.1891288 0.05100633
# 2: 2 -0.0002406689 1.8093820 -0.8253280 1.14547045
# $value2
# sim 1 2 3 4
# <num> <num> <num> <num> <num>
# 1: 1 0.03157319 -0.8352058 -0.06876365 0.7467717
# 2: 2 -0.42551873 -0.7720822 0.15276411 0.9885968
整理宇宙
library(dplyr)
library(tidyr) # pivot_longer, pivot_wider
dat %>%
pivot_longer(., -c(sim, time)) %>%
pivot_wider(., names_from = time, values_from = value) %>%
split(., .$name) %>%
lapply(., select, -name)
# $value1
# # A tibble: 2 x 5
# sim `1` `2` `3` `4`
# <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 1 1.05 -0.485 0.189 0.0510
# 2 2 -0.000241 1.81 -0.825 1.15
# $value2
# # A tibble: 2 x 5
# sim `1` `2` `3` `4`
# <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 1 0.0316 -0.835 -0.0688 0.747
# 2 2 -0.426 -0.772 0.153 0.989