我喜欢 reshape2 软件包，因为它使生活变得轻松自如。通常，Hadley在其先前的软件包中进行了改进，以启用简化的，运行速度更快的代码。我想我应该给 tidyr 打个招呼，从我的阅读中我认为gather与 reshape2 的melt非常相似。但是在阅读了文档之后，我无法获得gather来完成与melt相同的任务。
数据 View
这是数据 View (帖子末尾为dput形式的实际数据):
teacher yr1.baseline pd yr1.lesson1 yr1.lesson2 yr2.lesson1 yr2.lesson2 yr2.lesson3
1 3 1/13/09 2/5/09 3/6/09 4/27/09 10/7/09 11/18/09 3/4/10
2 7 1/15/09 2/5/09 3/3/09 5/5/09 10/16/09 11/18/09 3/4/10
3 8 1/27/09 2/5/09 3/3/09 4/27/09 10/7/09 11/18/09 3/5/10
代码
这是
melt格式的代码，我尝试过gather。如何使gather与melt做相同的事情？library(reshape2); library(dplyr); library(tidyr)
dat %>%
melt(id=c("teacher", "pd"), value.name="date")
dat %>%
gather(key=c(teacher, pd), value=date, -c(teacher, pd))
所需的输出
teacher pd variable date
1 3 2/5/09 yr1.baseline 1/13/09
2 7 2/5/09 yr1.baseline 1/15/09
3 8 2/5/09 yr1.baseline 1/27/09
4 3 2/5/09 yr1.lesson1 3/6/09
5 7 2/5/09 yr1.lesson1 3/3/09
6 8 2/5/09 yr1.lesson1 3/3/09
7 3 2/5/09 yr1.lesson2 4/27/09
8 7 2/5/09 yr1.lesson2 5/5/09
9 8 2/5/09 yr1.lesson2 4/27/09
10 3 2/5/09 yr2.lesson1 10/7/09
11 7 2/5/09 yr2.lesson1 10/16/09
12 8 2/5/09 yr2.lesson1 10/7/09
13 3 2/5/09 yr2.lesson2 11/18/09
14 7 2/5/09 yr2.lesson2 11/18/09
15 8 2/5/09 yr2.lesson2 11/18/09
16 3 2/5/09 yr2.lesson3 3/4/10
17 7 2/5/09 yr2.lesson3 3/4/10
18 8 2/5/09 yr2.lesson3 3/5/10
数据
dat <- structure(list(teacher = structure(1:3, .Label = c("3", "7",
"8"), class = "factor"), yr1.baseline = structure(1:3, .Label = c("1/13/09",
"1/15/09", "1/27/09"), class = "factor"), pd = structure(c(1L,
1L, 1L), .Label = "2/5/09", class = "factor"), yr1.lesson1 = structure(c(2L,
1L, 1L), .Label = c("3/3/09", "3/6/09"), class = "factor"), yr1.lesson2 = structure(c(1L,
2L, 1L), .Label = c("4/27/09", "5/5/09"), class = "factor"),
yr2.lesson1 = structure(c(2L, 1L, 2L), .Label = c("10/16/09",
"10/7/09"), class = "factor"), yr2.lesson2 = structure(c(1L,
1L, 1L), .Label = "11/18/09", class = "factor"), yr2.lesson3 = structure(c(1L,
1L, 2L), .Label = c("3/4/10", "3/5/10"), class = "factor")), .Names = c("teacher",
"yr1.baseline", "pd", "yr1.lesson1", "yr1.lesson2", "yr2.lesson1",
"yr2.lesson2", "yr2.lesson3"), row.names = c(NA, -3L), class = "data.frame")
最佳答案
您的gather行应如下所示:
dat %>% gather(variable, date, -teacher, -pd)
这说:“收集除
teacher和pd之外的所有变量，将新键列称为'variable'和将新值列称为'date'。”作为说明，请从
help(gather)页面中注意以下内容: ...: Specification of columns to gather. Use bare variable names.
Select all variables between x and z with ‘x:z’, exclude y
with ‘-y’. For more options, see the select documentation.
由于这是省略号，因此要收集的列的规范将作为单独的(裸名)参数给出。我们希望收集
teacher和pd以外的所有列，因此我们使用-。关于r - 比较聚集(tidyr)以融化(reshape2)，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/26536251/