计算n天滚动平均值

时间:2020-05-12 21:12:45

标签: r mean finance

我有以下数据集:

date <- StockData[1:10,2]
x <- c(2,4,2,3,5,1,6,2,3,4)
df <- as.data.frame(cbind(x,date))
df

   x       date
1  2 2019-06-28
2  4 2019-07-01
3  2 2019-07-02
4  3 2019-07-03
5  5 2019-07-04
6  1 2019-07-05
7  6 2019-07-08
8  2 2019-07-09
9  3 2019-07-10
10 4 2019-07-11

现在,我想创建一个新列,其滚动平均值要提前5(n)天,因此数据集如下所示:

   x       date five.day.average
1  2 2019-06-28              3.2
2  4 2019-07-01              3
3  2 2019-07-02              3.4
4  3 2019-07-03              3.4
5  5 2019-07-04              3.4
6  1 2019-07-05              3.2
7  6 2019-07-08              NA
8  2 2019-07-09              NA
9  3 2019-07-10              NA
10 4 2019-07-11              NA

换句话说,我想要一个公式/函数,其功能与程序包rollmean中的zoo相同,但是要使时间倒退,而不要倒退(因为k rollmean不能为负。

提前谢谢!

2 个答案:

答案 0 :(得分:3)

一个选项是frollmean中的data.table

library(data.table)
setDT(df)[, five.day.average := frollmean(x, 5, align = 'left')]
df
#    x       date five.day.average
# 1: 2 2019-06-28              3.2
# 2: 4 2019-07-01              3.0
# 3: 2 2019-07-02              3.4
# 4: 3 2019-07-03              3.4
# 5: 5 2019-07-04              3.4
# 6: 1 2019-07-05              3.2
# 7: 6 2019-07-08               NA
# 8: 2 2019-07-09               NA
# 9: 3 2019-07-10               NA
#10: 4 2019-07-11               NA

或者使用rollmean中的zoo

rollmean(df$x, 5, align = 'left', fill = NA)
#[1] 3.2 3.0 3.4 3.4 3.4 3.2  NA  NA  NA  NA

数据

df <- structure(list(x = c(2L, 4L, 2L, 3L, 5L, 1L, 6L, 2L, 3L, 4L), 
    date = c("2019-06-28", "2019-07-01", "2019-07-02", "2019-07-03", 
    "2019-07-04", "2019-07-05", "2019-07-08", "2019-07-09", "2019-07-10", 
    "2019-07-11")), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10"))

答案 1 :(得分:3)

base 中,您可以使用filter来获得滚动平均值。要使其向前看 rev

rev(filter(rev(df$x), rep(1/5, 5), sides=1))
# [1] 3.2 3.0 3.4 3.4 3.4 3.2  NA  NA  NA  NA