如何使用eval向data.table添加列 [英] How to add columns to data.table using eval

问题描述

我有一个数据表的观察和模型是是和否。为了简单起见，我只假设组。我浪费计算一些分类统计，我想控制选择哪一个。我知道如何使用eval，并将其保存在另一个data.table，但我想添加到现有的data.table，因为我每个组只有一行。

首先，我为每个组创建应急表。

  DT  categorical< obs == category [1]& mod == category [1]），
b = sum（obs == category [2]& mod == category [1]），
c = sum obs == category [1]& mod == category [2]），
d = sum（obs == category [2]& mod == category [2]），by = groupBy] 
  

然后定义统计

  my_exprs = quote（list（
n = a + b + c + d，
s =（a + c）/（a + b + c + d），
r = （a + b）/（a + b + c + d）））
  

以下行，它将给我一个新的data.table：

  statList < -  c（n，s ）
w = which（names（my_exprs）％in％statList）
 categorical [，eval（my_exprs [c（1，w）]），by = groupBy] 
  

如何使用：=在这个例子中，将结果添加到我的旧DT，这里称为分类？我做了以下，并得到错误消息：

 分类[，`：=`（eval（my_exprs [c ）]）），by = groupBy] 
 
 
在`[.data.table`（分类，，`：=`（eval（my_exprs [c（1，w）] ）），：
在`：=`（col1 = val1，col2 = val2，...）形式中，所有参数必须命名
  

感谢，

解决方案

我无法重现您的示例，保留 my_exprs ，但定义

  my_newcols = as.call在  

：//stackoverflow.com/questions/22595765/data-table-joins-select-all-columns-in-the-i-argument/22596160#22596160> Arun的回答。

或者，您可以在开始时使用：= 构建表达式：

  my_newcols = quote（`：=`（n = a + b + c + d，s = a + c））
  pre> 
I have a data table of observation and model of being yes and no. For simplicity I have assumed only to groups. I wast to calculate some categorical statistics which I want to have control over which one to be chosen. I know how to do it using eval and save it in another data.table but I want to add to the existing data.table as I have only one row for each group. Could anyone help me?

First I create the contingency table for each group.
 DT  <- data.table::data.table(obs = rep(c("yes","no"), 5), mod = c(rep("yes",5), rep("no", 5)), groupBy = c(1,1,1,1,1,2,1,1,2,1))
categorical <- DT[, .(a = sum(obs == category[1] & mod == category[1]),
                  b = sum(obs == category[2] & mod == category[1]),
                  c = sum(obs == category[1] & mod == category[2]),
                  d = sum(obs == category[2] & mod == category[2])), by = groupBy]
Then define the statistics 
my_exprs = quote(list(
 n    =  a+b+c+d,
 s    = (a+c)/(a+b+c+d),
 r    = (a+b)/(a+b+c+d))) 
If i use the following lines, it will give me a new data.table:
statList <- c("n","s")
w = which(names(my_exprs) %in% statList)
categorical[, eval(my_exprs[c(1,w)]), by = groupBy]
How to use := in this example to add the results to my old DT, here called categorical?! I did the following and got error message:
categorical[, `:=`(eval(my_exprs[c(1,w)])), by = groupBy]


Error in `[.data.table`(categorical, , `:=`(eval(my_exprs[c(1, w)])),  : 
 In `:=`(col1=val1, col2=val2, ...) form, all arguments must be named.
Thanks,
解决方案
I cannot reproduce your example, but it might work to keep your my_exprs, but define 
my_newcols = as.call(c(quote(`:=`), my_exprs))
as in Arun's answer. 

Alternately, you could just construct the expression with a := at the start:
my_newcols = quote(`:=`(n = a+b+c+d, s = a+c))


                        
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