折叠数据框 [英] Collapse data frame

问题描述

如何折叠我的数据框，其中许多观测值包含多行，但几个不同变量中的每个变量最多只有一个值？

How can I collapse my data frame where many observations have multiple rows but at most only one value for each of several different variables?

这就是我所拥有的：

id  title info                 var1     var2        var3
1   foo   Some string here     string 1     
1   foo   Some string here              string 2 
1   foo   Some string here                          string 3
2   bar   A different string   string 4 string 5    
2   bar   A different string                        string 6
3   baz   Something else       string 7             string 8

这就是我想要的：

id  title info                  var1        var2        var3
1   foo   Some string here      string 1    string 2    string 3
2   bar   A different string    string 4    string 5    string 6
3   baz   Something else        string 7                string 8

我想我已经拥有了

ddply(merged, .(id, title, info), summarize, var1 = max(var1), var2 = max(var2), var3 = max(var3))

但是问题在于，还有更多的var1-var3变量，它们是通过编程生成的。结果，我需要一种方法，根据变量名列表以编程方式插入 var1 = max（var1）等。

But the problem is that there are many more of the var1-var3 variables, and they are programmatically generated. As a result, I need a way to insert var1 = max(var1), etc. programmatically, based on an list of the variable names.

推荐答案

实现此目标的许多可能方法，有两种

Many possible ways achieving this, here are two

定义一些帮助函数

Myfunc <- function(x) x[x != '']

使用 data.table

library(data.table)
setDT(df)[, lapply(.SD, Myfunc), by = list(id, title, info)]
#    id title               info     var1     var2     var3
# 1:  1   foo   Some string here string 1 string 2 string 3
# 2:  2   bar A different string string 4 string 5 string 6
# 3:  3   baz     Something else string 7       NA string 8

或类似地与 dplyr

library(dplyr)
df %>%
  group_by(id, title, info) %>%
  summarise_each(funs(Myfunc))

# Source: local data table [3 x 6]
# Groups: id, title
# 
#   id title               info     var1     var2     var3
# 1  1   foo   Some string here string 1 string 2 string 3
# 2  2   bar A different string string 4 string 5 string 6
# 3  3   baz     Something else string 7       NA string 8

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