使用 tidyr 收集多个日期/值列 [英] Gather multiple date/value columns using tidyr
问题描述
我有一个数据集，其中包含(除其他外)多个带有日期和相应值(重复测量)的列.有没有办法把它变成一个长数据集，只包含(其他和)两列 - 一列用于 dates，另一列用于 values - 使用 tidyr?
I have a data set containing (amongst others) multiple columns with dates and corresponding values (repeated measurements). Is there a way to turn this into a long data set containing (the others and) only two columns - one for dates and one for values - using tidyr?
以下代码生成一个示例数据框:
The following code produces an example data frame:
df <- data.frame(
id = 1:10,
age = sample(100, 10),
date1 = as.Date('2015-09-22') - sample(100, 10),
value1 = sample(100, 10),
date2 = as.Date('2015-09-22') - sample(100, 10),
value2 = sample(100, 10),
date3 = as.Date('2015-09-22') - sample(100, 10),
value3 = sample(100, 10))
输入表可能(1.8x10^138中1的概率)如下所示:
The input table could (chance of 1 in 1.8x10^138) look like this:
id age date1 value1 date2 value2 date3 value3
1 1 32 2015-08-01 37 2015-07-15 38 2015-09-09 81
2 2 33 2015-07-22 16 2015-06-26 1 2015-09-12 58
...
10 10 64 2015-07-23 78 2015-08-25 70 2015-08-05 90
我最终想要的是这个:
id age date value
1 1 32 2015-08-01 37
2 1 32 2015-07-15 38
3 1 32 2015-09-09 81
4 2 33 2015-07-22 16
5 2 33 2015-06-26 1
...
30 10 64 2015-08-05 90
在 tidyr 或 reshape 中提供任何帮助将不胜感激.
Any help doing this in tidyr or reshape would be greatly appreciated.
推荐答案
应该有一些有效的方法，但这是一种方法.
There should be some efficient way, but this is one way.
单独处理日期和值，
#for date
df.date<-df%>%select(id, age,date1,date2, date3)%>%melt(id.var=c("id", "age"), value.name="date")
#for val
df.val<-df%>%select(id, age,value1,value2, value3)%>%melt(id.var=c("id", "age"), value.name="value")
现在加入，
df2<-full_join(df.date, df.val, by=c("id", "age"))
df2%>%select(-variable.x, -variable.y)
id age date value
1 1 40 2015-07-19 28
2 1 40 2015-07-19 49
3 1 40 2015-07-19 24
4 2 33 2015-06-27 99
5 2 33 2015-06-27 18
6 2 33 2015-06-27 26
7 3 75 2015-07-07 63
8 3 75 2015-07-07 74
9 3 75 2015-07-07 72
这篇关于使用 tidyr 收集多个日期/值列的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
