在其他数据表中检查data.table值的频率 [英] Check frequency of data.table value in other data.table

问题描述

  library（data.table）
 DT1 < -  data.table（num = 1：6，group = c（A，B，B b，A，C））
 DT2   

我想向添加当 DT2 $ group 包含在中时， $ DT2 DT1 $ group 至少两次。因此，在上面的示例中， DT2 应为

  b $ b 1：A TRUE 
 2：B TRUE 
 3：C FALSE 
  



<

更新示例： DT2 c>实际上可能包含比 DT1 更多的组，因此这里有一个更新的示例：

  DT1 < -  data.table（num = 1：6，group = c（A，B，B，B，A，C））
 DT2 < -  data.table（group = c（A，B，C，D））
  

所需输出为

  group popular 
 1：A TRUE 
 2：B TRUE 
 3：C FALSE 
 4：D FALSE 
  

解决方案

我只是这样做：

  ## 1.9.4+ 
 setkey（DT1，group）
 DT1 [J（DT2 $ group），list（popular = .N> = 2L），by = .EACHI] 
＃group popular 
＃1：A 
＃2：B TRUE 
＃3：C FALSE 
＃4：D FALSE ##更新示例中的
  

data.table 的连接语法非常强大，还会聚合/选择/更新 j 中的列。这里我们执行一个join。对于 DT2 $ group 中的每一行，在 DT1 中的相应匹配行上，我们计算j-表达式 .N> = 2L ;指定 by = .EACHI （请检查 1.9.4 NEWS ），我们每次计算j表达式。

---

在 1.9.4 ，。（）已在所有i，j和by中引入为别名。所以你也可以做：

  DT1 [。（DT2 $ group），。（popular = .N> = 2L） ，by = .EACHI] 
  

当您通过单个字符列加入时， 。（） / J（）语法。因此，这也可以写成：

  DT1 [DT2 $ group，。（popular = .N> = 2L） by = .EACHI] 
  

 library(data.table)
 DT1 <- data.table(num = 1:6, group = c("A", "B", "B", "B", "A", "C"))
 DT2 <- data.table(group = c("A", "B", "C"))

I want to add a column popular to DT2 with value TRUE whenever DT2$group is contained in DT1$group at least twice. So, in the example above, DT2 should be

    group popular
 1:     A    TRUE
 2:     B    TRUE
 3:     C   FALSE

What would be an efficient way to get to this?

Updated example: DT2 may actually contain more groups than DT1, so here's an updated example:

 DT1 <- data.table(num = 1:6, group = c("A", "B", "B", "B", "A", "C"))
 DT2 <- data.table(group = c("A", "B", "C", "D"))

And the desired output would be

    group popular
 1:     A    TRUE
 2:     B    TRUE
 3:     C   FALSE
 4:     D   FALSE

解决方案

I'd just do it this way:

## 1.9.4+
setkey(DT1, group)
DT1[J(DT2$group), list(popular = .N >= 2L), by=.EACHI]
#    group popular
# 1:     A    TRUE
# 2:     B    TRUE
# 3:     C   FALSE
# 4:     D   FALSE ## on the updated example

data.table's join syntax is quite powerful, in that, while joining, you can also aggregate / select / update columns in j. Here we perform a join. For each row in DT2$group, on the corresponding matching rows in DT1, we compute the j-expression .N >= 2L; by specifying by=.EACHI (please check 1.9.4 NEWS), we compute the j-expression each time.

---

In 1.9.4, .() has been introduced as an alias in all i, j and by. So you could also do:

DT1[.(DT2$group), .(popular = .N >= 2L), by=.EACHI]

When you're joining by a single character column, you can drop the .() / J() syntax altogether (for convenience). So this can be also written as:

DT1[DT2$group, .(popular = .N >= 2L), by=.EACHI]

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