R中

Question

标签独特的价值观我的数据是这样的：

data <- matrix(c("1","install","2015-10-23 14:07:20.000000", 
       "2","install","2015-10-23 14:08:20.000000", 
       "3","install","2015-10-23 14:07:25.000000", 
       "3","sale","2015-10-23 14:08:20.000000", 
       "4","install","2015-10-23 14:07:20.000000", 
       "4","sale","2015-10-23 14:09:20.000000", 
       "4","sale","2015-10-23 14:11:20.000000"), 
       ncol=3, byrow=TRUE) 
colnames(data) <- c("id","event","time") 

我想补充的第四列，被称为标签，在标签我相应的每一行上的一些价值观。在这种情况下：

• “0”的标签，如果ID是唯一
• “1”的标签，如果ID不是唯一的，它有相关的1个销售
• “2”的标签，如果id不是唯一的，并且它具有相关联的2个销售

等等最多n个销售。

最后应当是这样的：

data1 <- matrix(c("1","install","2015-10-23 14:07:20.000000","0", 
        "2","install","2015-10-23 14:08:20.000000","0", 
        "3","install","2015-10-23 14:07:25.000000","1", 
        "3","sale","2015-10-23 14:08:20.000000","1", 
        "4","install","2015-10-23 14:07:20.000000","2", 
        "4","sale","2015-10-23 14:09:20.000000","2", 
        "4","sale","2015-10-23 14:11:20.000000","2"), 
       ncol=4, byrow=TRUE) 

这我不清楚什么是R中根据具体的情况来创建“标签”，最好的办法......也许dplyr::mutate？

Answer 1

更新为反映“等到n销售”。 - 要求。

一个dplyr选择是：

library(dplyr) 
data <- as.data.frame(data) 
data %>% 
    group_by(id) %>% 
    mutate(label = if(n() == 1) 0 else as.numeric(sum(event == "sale"))) 

#Source: local data frame [7 x 4] 
#Groups: id [4] 
# 
#  id event      time label 
# (fctr) (fctr)      (fctr) (dbl) 
#1  1 install 2015-10-23 14:07:20.000000  0 
#2  2 install 2015-10-23 14:08:20.000000  0 
#3  3 install 2015-10-23 14:07:25.000000  1 
#4  3 sale 2015-10-23 14:08:20.000000  1 
#5  4 install 2015-10-23 14:07:20.000000  2 
#6  4 sale 2015-10-23 14:09:20.000000  2 
#7  4 sale 2015-10-23 14:11:20.000000  2 

---

的data.table相当于是：

library(data.table) 
data <- as.data.table(data) # or setDT(data) if it's already a data.frame 
data[, label := if(.N == 1) 0 else as.numeric(sum(event == "sale")), by=id] 

Answer 2

随着base R：

我们可以使用sum通过id使用ave相符的"sale"的发生。然后检查ID是否与uniq一致。我们将"0"分配给任何唯一的行。 cbind将它们放在一起。我也转换为data.frame，因为没有任何理由在矩阵中存储混合信息。

indx <- ave(data[,2], data[,1], FUN=function(x) sum(x == "sale")) 
uniq <- table(data[,1]) == 1 
indx[data[,1] %in% which(uniq)] <- "0" 
cbind.data.frame(data, indx) 
# id event      time count 
# 1 1 sale 2015-10-23 14:07:20.000000  0 
# 2 2 install 2015-10-23 14:08:20.000000  0 
# 3 3 install 2015-10-23 14:07:25.000000  1 
# 4 3 sale 2015-10-23 14:08:20.000000  1 
# 5 4 install 2015-10-23 14:07:20.000000  2 
# 6 4 sale 2015-10-23 14:09:20.000000  2 
# 7 4 sale 2015-10-23 14:11:20.000000  2 

Answer 3

与汇总值添加列的另一种dplyr方法是创建汇总在另一个表中变量，然后将其加回到主数据帧中，如下所示：

library(dplyr) 
left_join(data, 
       data %>% 
       group_by(id) %>% 
       summarise(count = n(), sales = sum(event == "sale")) 
) %>% 
    mutate(label = ifelse(count == 1, 0, sales)) %>% 
    select(-count, -sales) 

> data 
    id event      time label 
1 1 install 2015-10-23 14:07:20.000000  0 
2 2 install 2015-10-23 14:08:20.000000  0 
3 3 install 2015-10-23 14:07:25.000000  1 
4 3 sale 2015-10-23 14:08:20.000000  1 
5 4 install 2015-10-23 14:07:20.000000  2 
6 4 sale 2015-10-23 14:09:20.000000  2 
7 4 sale 2015-10-23 14:11:20.000000  2