我有一个包含5列的数据框：“ Date_Time”，“ Categ_1”，“ Categ_2”，“ Price”和“ Volume”。数据帧由Date_Time排序。对于此有序数据帧，我想计算Categ_1和Categ_2每组中的价格百分比变化。 我正在使用代码：
A <- dataset %>%
group_by(Categ_1, Categ_2) %>%
mutate(price_prc_change = (Price/lag(Price)-1)*100)
，但按组结果不起作用。百分比变化仅基于“价格”列计算，未考虑Categ_1或Categ_2。
> dput(droplevels(df[1:50, ]))
structure(list(Date_Time = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 5L, 6L,
6L, 6L, 6L, 7L, 7L, 8L, 8L, 9L, 9L, 10L, 11L, 11L), .Label = c("2020-04-30 15:26:03.8430000",
"2020-04-30 15:26:14.5870000", "2020-04-30 15:45:11.4690000",
"2020-04-30 16:00:37.8760000", "2020-04-30 16:00:39.4960000",
"2020-04-30 16:01:18.9490000", "2020-04-30 16:02:02.6070000",
"2020-04-30 16:02:23.2270000", "2020-04-30 16:02:25.3250000",
"2020-04-30 16:07:34.7980000", "2020-04-30 16:08:33.1210000"), class = "factor"),
Categ_1 = structure(c(3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 2L, 2L, 4L, 1L, 1L, 3L, 1L, 3L, 5L), .Label = c("ED1",
"ED2", "ED3", "ED4", "XHE"), class = "factor"), Categ_2 = structure(c(5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 3L, 2L, 3L, 2L, 4L, 4L,
9L, 9L, 7L, 7L, 1L), .Label = c("H01", "H06Q1", "H07Q1",
"H09Q2", "H11", "H12", "H12Q3", "H13", "H15Q4", "H18Q1"), class = "factor"),
Price = c(-14.88, -14.88, -14.88, -14.88, -14.89, -14.88,
-14.88, -14.88, -14.88, -14.89, -14.48, -14.48, -14.48, -14.48,
-14.49, -14.5, -14.48, -14.48, -14.48, -14.48, -14.49, -11.38,
-11.38, -11.38, -11.38, -11.38, -11.38, -11.38, -11.39, -11.39,
-11.38, -11.38, -11.38, -11.38, -11.38, -11.38, -11.38, -11.39,
-11.39, -42, -52.2, 9.6, 9.96, 9.6, 9.96, 9.46, 9.46, 17.86,
17.86, 9.56), Volume = c(5.8, 5.8, 5.8, 2.6, 5, 5.8, 5.8,
5.8, 2.6, 5, 5.5, 5.5, 5.5, 3.5, 5, 25, 5.5, 5.5, 5.5, 3.5,
5, 5.4, 0.6, 4.8, 1.2, 4.2, 1.8, 2, 4, 1, 5.4, 0.6, 4.8,
1.2, 4.2, 1.8, 2, 4, 1, 1, 1, 1, 1, 1, 1, 0.1, 0.1, 0.1,
0.1, 0.1)), row.names = c(NA, 50L), class = "data.frame")