使用data.table在多次融化期间命名变量 [英] Name variables during multiple melt with data.table
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问题描述
我有以下data.table 我要在其上执行多列合并：
I have the following data.table that I want to perform a multiple column melt upon:
# Load library
library(data.table)
# Dummy data set
dt <- data.table(a = 1:10,
t_alpha = runif(10),
t_beta = runif(10),
t_gamma = runif(10),
s_alpha = runif(10),
s_beta = runif(10),
s_gamma = runif(10))
# Look at data table
dt
#> a t_alpha t_beta t_gamma s_alpha s_beta s_gamma
#> 1: 1 0.73315322 0.7777962 0.13258401 0.12841353 0.20865995 0.8967482
#> 2: 2 0.10161042 0.9691244 0.23506277 0.35130324 0.36672933 0.9247026
#> 3: 3 0.95234142 0.7002526 0.07104051 0.85558314 0.39467530 0.8982107
#> 4: 4 0.48967202 0.3951288 0.72376459 0.58978334 0.47201394 0.8508710
#> 5: 5 0.22997537 0.3487354 0.58831312 0.63917860 0.12685815 0.5616682
#> 6: 6 0.01138277 0.0449675 0.79384717 0.28983485 0.98793013 0.6574457
#> 7: 7 0.32324941 0.3446745 0.66394161 0.16357679 0.14828451 0.2019661
#> 8: 8 0.78644407 0.4460397 0.76992857 0.78703793 0.46623055 0.3081812
#> 9: 9 0.90938120 0.4526063 0.47948163 0.03182248 0.63600496 0.3598600
#> 10: 10 0.11345349 0.1732653 0.59240218 0.95541944 0.06640378 0.9475107
所以，我继续融化，就像这样：
So, I go ahead and melt, like so:
# Groups of columns to melt
m <- list(names(dt)[grepl("t_", names(dt))],
names(dt)[grepl("s_", names(dt))])
# Perform melt
dt2 <- melt(dt, measure = m, value.name = c("t", "s"))
给出，
# Examine results
dt2
#> a variable t s
#> 1: 1 1 0.73315322 0.12841353
#> 2: 2 1 0.10161042 0.35130324
#> 3: 3 1 0.95234142 0.85558314
#> 4: 4 1 0.48967202 0.58978334
#> 5: 5 1 0.22997537 0.63917860
#> 6: 6 1 0.01138277 0.28983485
#> 7: 7 1 0.32324941 0.16357679
#> 8: 8 1 0.78644407 0.78703793
#> 9: 9 1 0.90938120 0.03182248
#> 10: 10 1 0.11345349 0.95541944
#> 11: 1 2 0.77779618 0.20865995
#> 12: 2 2 0.96912444 0.36672933
#> 13: 3 2 0.70025264 0.39467530
#> 14: 4 2 0.39512877 0.47201394
#> 15: 5 2 0.34873538 0.12685815
#> 16: 6 2 0.04496750 0.98793013
#> 17: 7 2 0.34467455 0.14828451
#> 18: 8 2 0.44603969 0.46623055
#> 19: 9 2 0.45260634 0.63600496
#> 20: 10 2 0.17326532 0.06640378
#> 21: 1 3 0.13258401 0.89674825
#> 22: 2 3 0.23506277 0.92470265
#> 23: 3 3 0.07104051 0.89821074
#> 24: 4 3 0.72376459 0.85087097
#> 25: 5 3 0.58831312 0.56166816
#> 26: 6 3 0.79384717 0.65744574
#> 27: 7 3 0.66394161 0.20196612
#> 28: 8 3 0.76992857 0.30818121
#> 29: 9 3 0.47948163 0.35986003
#> 30: 10 3 0.59240218 0.94751075
#> a variable t s
太好了！
现在，请注意一个额外的列，变量。这对应于我的 t 和 s 的每一列。具体而言，1 = alpha，2 = beta，3 =γ。我可以按以下方式修复此变量：
Now, notice an extra column, variable. That corresponds to each of my columns for t and s. Specifically, 1 = alpha, 2 = beta, and 3 = gamma. I can fix this variable as follows:
# Fix variable names
v_names <- c("alpha", "beta", "gamma")
dt2$variable <- v_names[dt2$variable]
生产中，
# Examine results
dt2
#> a variable t s
#> 1: 1 alpha 0.73315322 0.12841353
#> 2: 2 alpha 0.10161042 0.35130324
#> 3: 3 alpha 0.95234142 0.85558314
#> 4: 4 alpha 0.48967202 0.58978334
#> 5: 5 alpha 0.22997537 0.63917860
#> 6: 6 alpha 0.01138277 0.28983485
#> 7: 7 alpha 0.32324941 0.16357679
#> 8: 8 alpha 0.78644407 0.78703793
#> 9: 9 alpha 0.90938120 0.03182248
#> 10: 10 alpha 0.11345349 0.95541944
#> 11: 1 beta 0.77779618 0.20865995
#> 12: 2 beta 0.96912444 0.36672933
#> 13: 3 beta 0.70025264 0.39467530
#> 14: 4 beta 0.39512877 0.47201394
#> 15: 5 beta 0.34873538 0.12685815
#> 16: 6 beta 0.04496750 0.98793013
#> 17: 7 beta 0.34467455 0.14828451
#> 18: 8 beta 0.44603969 0.46623055
#> 19: 9 beta 0.45260634 0.63600496
#> 20: 10 beta 0.17326532 0.06640378
#> 21: 1 gamma 0.13258401 0.89674825
#> 22: 2 gamma 0.23506277 0.92470265
#> 23: 3 gamma 0.07104051 0.89821074
#> 24: 4 gamma 0.72376459 0.85087097
#> 25: 5 gamma 0.58831312 0.56166816
#> 26: 6 gamma 0.79384717 0.65744574
#> 27: 7 gamma 0.66394161 0.20196612
#> 28: 8 gamma 0.76992857 0.30818121
#> 29: 9 gamma 0.47948163 0.35986003
#> 30: 10 gamma 0.59240218 0.94751075
#> a variable t s
由 reprex软件包（v0.3.0）
Created on 2019-08-09 by the reprex package (v0.3.0)
这是我想要的结果。我的问题是，我可以执行此操作（即，重新命名变量列中的值）在期间吗？还是我只需要然后修补吗？
This is my desired result. My question is, can I perform this operation (i.e., renaming of the values in the variable column) during the melt or do I just have to patch it up afterwards?
推荐答案
在 pivot_longer 中，这是开发版 tidyr
library(tidyr)# ‘0.8.3.9000’
library(dplyr)
dt %>%
pivot_longer(-a, names_to= c(".value", "variable"), names_sep = "_")
# A tibble: 30 x 4
# a variable t s
# <int> <chr> <dbl> <dbl>
# 1 1 alpha 0.592 0.0634
# 2 1 beta 0.316 0.339
# 3 1 gamma 0.760 0.751
# 4 2 alpha 0.936 0.445
# 5 2 beta 0.232 0.00250
# 6 2 gamma 0.0111 0.406
# 7 3 alpha 0.0950 0.102
# 8 3 beta 0.426 0.775
# 9 3 gamma 0.321 0.811
#10 4 alpha 0.884 0.0526
# … with 20 more rows
注意：由于没有 set.seed
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