我有一个简单的时间序列数据集,其中包含10个变量-我想创建一个for循环(或函数),为其中的每个变量创建一个'前一个月变化的变量'和'前一个月变量的变化百分比'时间序列(日期除外)。我知道我可以为每个特定的列简单地编写代码,但是由于有很多列,所以我想对其进行优化。
这是我的数据,“日期”,“销售”,“价格”是一些列名称:
+----+---+---+---+---+---+---+---+--
| Date | Sales | Price |
+----+---+---+---+---+---+---+---+--
| 01Aug2019 | 4 | 15 |
| 01Sept2019 | 6 | 30 |
| 01Oct2019 | 10 | 44 |
+----+---+---+---+---+---+---+---+--
这是我希望通过for循环(或任何函数)使用的样子
+----+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+
| Date | Sales | chg_Sales | pct_chg_Sales | Price | chg_Price | pct_chg_Price|
+----+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+
| 01Aug2019 | 4 | NA |NA | 15 | NA |NA |
| 01Sept2019 | 6 | 2 |50% | 30 | 15 |100% |
| 01Oct2019 | 10 | 4 |66% | 44 | 14 |46% |
+----+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+
我尝试了下面的代码,但是没有用
add_column <- function (x, y){
setDT (x)[,pct_chg_y:= (y - shift (y,1, type="lag")/shift (,1, type="lag")*100]
}
[这是data.table
的选项
nm1 <- c("Sales", "Price")
setDT(df1)[, paste0("chg_", nm1) := .SD - shift(.SD), .SDcols = nm1]
df1[, paste0("pct_chg_", nm1) :=
Map(function(x, y) 100 * (y/shift(x)), .SD, mget(paste0("chg_", nm1)),
.SDcols = nm1]
df1 <- structure(list(Date = c("01Aug2019", "01Sept2019", "01Oct2019"
), Sales = c(4, 6, 10), Price = c(15, 30, 44)),
class = "data.frame", row.names = c(NA,
-3L))