将多列折叠为一列并生成索引变量 [英] collapse mulitple columns into one column and generate an index variable

问题描述

我有三个日期列，如下所示

I have three date columns as shown below

       Id Date1       Date2         Date3
       12 2005-12-22  NA            NA
       11 2009-10-11  NA            NA
       29 NA          2005-04-11    NA
       45 NA          NA            2008-11-06
       39 NA          NA            2006-01-02
       44 NA          2005-04-16    NA

我正在尝试折叠三个日期列到一个日期列，并创建一个索引变量，如果日期1列中有一个日期值，则创建2；如果日期2列中有一个日期，则创建2；如果在日期3列中有一个日期，则创建一个索引变量

I am trying to collapse the three Date columns in to one Date column and create an index variable 1 if there was a Date value in Date1 column, 2 if there was a Date in Date2 column and 3 if there was a Date in Date3 column

       Id Date        Index
       12 2005-12-22  1
       11 2009-10-11  1
       29 2005-04-11  2
       45 2008-11-06  3       
       39 2006-01-02  3
       44 2005-04-16  2

我可以使用大量的ifelse语句来做到这一点，我想知道是否有人知道一种有效的方法吗？

I can do this using a massive ifelse statement i was wondering if anybody knew an efficient method of doing this ?

推荐答案

这是重塑从宽到长格式。如果 d 是您的data.frame：

This is a classic use of reshape to go from "wide" to "long" format. If d is your data.frame:

d2 <- reshape(d, idvar = "Id", v.names = "Date", timevar = "Index",
              varying = c("Date1", "Date2", "Date3"), direction = "long")

结果：

> d2
     Id Index       Date
12.1 12     1 2005-12-22
11.1 11     1 2009-10-11
29.1 29     1       <NA>
45.1 45     1       <NA>
39.1 39     1       <NA>
44.1 44     1       <NA>
12.2 12     2       <NA>
11.2 11     2       <NA>
29.2 29     2 2005-04-11
45.2 45     2       <NA>
39.2 39     2       <NA>
44.2 44     2 2005-04-16
12.3 12     3       <NA>
11.3 11     3       <NA>
29.3 29     3       <NA>
45.3 45     3 2008-11-06
39.3 39     3 2006-01-02
44.3 44     3       <NA>

如果您不希望所有 NA 值（在上方）可以子集：

If you don't want all the NA values (above) you can subset:

> d2[!is.na(d2$Date),]
     Id Index       Date
12.1 12     1 2005-12-22
11.1 11     1 2009-10-11
29.2 29     2 2005-04-11
44.2 44     2 2005-04-16
45.3 45     3 2008-11-06
39.3 39     3 2006-01-02

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