[英]R: Gather repeated columns
Sample data: 样本数据:
df1 <- structure(list(Name = structure(c(3L, 2L, 1L), .Label = c("Bob",
"Joe", "Mike"), class = "factor"), Location = structure(c(1L,
1L, 2L), .Label = c("CA", "WA"), class = "factor"), Title = structure(c(2L,
3L, 1L), .Label = c("CEO", "Manager", "VP"), class = "factor"),
Class = structure(c(1L, 2L, 2L), .Label = c("Class1", "Class2"
), class = "factor"), Month = c(1, 2, 3), Class.1 = structure(c(3L,
2L, 1L), .Label = c("Class1", "Class2", "Class4"), class = "factor"),
Month.1 = c(3, 3, 2), Objective = structure(1:3, .Label = c("Obj1",
"Obj2", "Obj3"), class = "factor"), Month.2 = c(2, 7, 7),
Category = c("x", "y", "z"), Objective.1 = structure(c(3L,
2L, 1L), .Label = c("Obj1", "Obj7", "Obj9"), class = "factor"),
Month.3 = c(4, 5, 5), Category2 = c("z", "r", "q")), .Names = c("Name",
"Location", "Title", "Class", "Month", "Class.1", "Month.1",
"Objective", "Month.2", "Category", "Objective.1", "Month.3",
"Category2"), class = "data.frame", row.names = c(NA, -3L))
Name Location Title Class Month Class.1 Month.1 Objective Month.2 Category Objective.1 Month.3 Category2
1 Mike CA Manager Class1 1 Class4 3 Obj1 2 x Obj9 4 z
2 Joe CA VP Class2 2 Class2 3 Obj2 7 y Obj7 5 r
3 Bob WA CEO Class2 3 Class1 2 Obj3 7 z Obj1 5 q
I want to gather into the form with one row per observation: 我想收集每个观察一行的表格:
Name Location Title Variable(Class/Objective) Value
I've tried some of the similar examples on stack using gather
, spread
, etc., but I can't figure out how to keep the Class-Month and Objective-Month groups together. 我已经尝试了使用
gather
, spread
等在堆栈上的一些类似示例,但我无法弄清楚如何将Class-Month和Objective-Month组保持在一起。
In my real data set, there are 100 columns with 8 ID columns. 在我的真实数据集中,有100列,有8个ID列。 And instead of just Class-Month, or Objective-Month pairs, the first half of the columns are in groups of four, and the second half are in groups of 8. An example of a group of four would be Class-Month-Cost-Date.
而不仅仅是Class-Month或Objective-Month对,列的前半部分是四个一组,后半部分是8个组。一组四个的例子是Class-Month-Cost -日期。
Sample output for Mike: Mike的示例输出:
Name Location Title Variable Value Value.2
1 Mike CA Manager Class1 1 <NA>
2 Mike CA Manager Class4 3 <NA>
3 Mike CA Manager Obj1 2 x
4 Mike CA Manager Obj9 4 z
Repeated values are fine, but you'll need to specify which ones group together (in the example, "Class" and "Objective") to get the OP's output: 重复的值很好,但是您需要指定哪些组合在一起(在示例中,“Class”和“Objective”)以获得OP的输出:
library(data.table)
melt(setDT(df1),
meas = patterns("Class|Objective", "Month", "Category")
)[order(Name)]
Name Location Title variable value1 value2 value3
1: Bob WA CEO 1 Class2 3 z
2: Bob WA CEO 2 Class1 2 q
3: Bob WA CEO 3 Obj3 7 NA
4: Bob WA CEO 4 Obj1 5 NA
5: Joe CA VP 1 Class2 2 y
6: Joe CA VP 2 Class2 3 r
7: Joe CA VP 3 Obj2 7 NA
8: Joe CA VP 4 Obj7 5 NA
9: Mike CA Manager 1 Class1 1 x
10: Mike CA Manager 2 Class4 3 z
11: Mike CA Manager 3 Obj1 2 NA
12: Mike CA Manager 4 Obj9 4 NA
It won't matter if you have identically repeating column names or use check.names=TRUE
to disambiguate since patterns
just matches patterns in the names. 如果您具有相同的重复列名称或使用
check.names=TRUE
消除歧义并不重要,因为patterns
只匹配名称中的模式。 See ?regex
for more on how to specify patterns if needed. 有关如何根据需要指定模式的更多信息,请参阅
?regex
。
Other arguments to melt
(see ?melt.data.table
) can be used to give customized names to the columns in the result (instead of "value1", "value2", ...). 其他
melt
参数(参见?melt.data.table
)可用于为结果中的列提供自定义名称(而不是“value1”,“value2”,...)。
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