按列分组并查找另一列的前导值

Question

我有一个很长的销售数据，下面是一个示例摘录：

|    Date    | CountryA | CountryB | PriceA | PriceB |  |
+------------+----------+----------+--------+--------+--+
| 05/09/2019 | US       | Japan    |     20 |     55 |  |
| 28/09/2019 | Japan    | Germany  |     30 |     28 |  |
| 16/10/2019 | Canada   | US       |     25 |     78 |  |
| 28/10/2019 | Germany  | Japan    |     60 |     17 |  |
+------------+----------+----------+--------+--------+--+

我想在“CountryB”列上分组，然后生成一个新列，显示相应国家/地区的 PriceA 的先前值，即该特定国家/地区上次出现在“CountryA”列中时基于日期顺序。在这个示例 table 中，我想得到以下结果：

|    Date    | CountryA | CountryB | PriceA | PriceB | PriceA_lag1 |  |
+------------+----------+----------+--------+--------+-------------+--+
| 05/09/2019 | US       | Japan    |     20 |     55 |             |  |
| 28/09/2019 | Japan    | Germany  |     30 |     28 |             |  |
| 16/10/2019 | Canada   | US       |     25 |     78 |          20 |  |
| 28/10/2019 | Germany  | Japan    |     60 |     17 |          30 |  |
+------------+----------+----------+--------+--------+-------------+--+

我用 dplyr 尝试了以下操作：

data=data%>%group_by(CountryB)%>%mutate_at(list(lag1=~dplyr::lag(.,1,order_by=Date)),.vars=vars(PriceA))

然而，当相应的国家位于“CountryA”列时，这并没有给我前面的值，而是当相应的国家位于“CountryB”时。

有人可以帮我解决这个问题吗？谢谢

Answer 1

很可能是我写过的最丑陋的代码，但是...

# install.packages('dplyr', 'magrittr')
library(dplyr)
library(magrittr)

d <- data.frame(
  stringsAsFactors = FALSE,
              Date = c("05/09/2019", "28/09/2019", "16/10/2019", "28/10/2019"),
          CountryA = c("US", "Japan", "Canada", "Germany"),
          CountryB = c("Japan", "Germany", "US", "Japan"),
            PriceA = c(20L, 30L, 25L, 60L),
            PriceB = c(55L, 28L, 78L, 17L)
) %>%
  mutate(Date = as.Date(Date, format = '%d/%m/%Y'))

priceA_lag <- c()
for(row in 1:nrow(d)){
  
  country <- slice(d, row) %$% CountryB
  date <- slice(d, row) %$% Date
  
  thePrice <- d %>% 
    filter(CountryA == country,
           date > Date) %>%
    filter(Date == max(Date)) %$%
    PriceA
  
  thePrice <- ifelse(length(thePrice) > 0, thePrice, NA)
  
  priceA_lag <- priceA_lag %>%
    append(thePrice)
  
}

d$priceA_lag <- priceA_lag

> d
  Date       CountryA CountryB PriceA PriceB priceA_lag
1 2019-09-05       US    Japan     20     55         NA
2 2019-09-28    Japan  Germany     30     28         NA
3 2019-10-16   Canada       US     25     78         20
4 2019-10-28  Germany    Japan     60     17         30

按列分组并查找另一列的前导值

Grouping by column and finding preceeding value of another column

r

dplyr

group-by

lag