R数据表创建前五年的平均值

Question

我有一个变量的数据，我想得到当前水平与前 5 年同月同一变量的平均值之间的差异。

library(tidyverse)
library(data.table)
library(lubridate)
MWE <- as.data.table(ggplot2::economics) %>%
  .[,c("pce","psavert","uempmed","unemploy"):=NULL]

> MWE
           date      pop
  1: 1967-07-01 198712.0
  2: 1967-08-01 198911.0
  3: 1967-09-01 199113.0
  4: 1967-10-01 199311.0
  5: 1967-11-01 199498.0
 ---                    
570: 2014-12-01 319746.2
571: 2015-01-01 319928.6
572: 2015-02-01 320074.5
573: 2015-03-01 320230.8
574: 2015-04-01 320402.3

我可以按月完成，但我无法合并对当前行的引用来执行类似 year(date) < year(currentline) & year(date) >= year(currentline)-6

的操作

MWE_2 <- MWE[,MeanPastYears:=mean(pop),by=month(date)]

我想要的输出是

       date      pop      avg_5yrs
  1: 1967-07-01 198712.0     NA
  2: 1967-08-01 198911.0     NA
  3: 1967-09-01 199113.0     NA
  4: 1967-10-01 199311.0     NA
  5: 1967-11-01 199498.0     NA
 ---                    
570: 2014-12-01 319746.2   313013.8
571: 2015-01-01 319928.6   313192.1
572: 2015-02-01 320074.5   313350.7
573: 2015-03-01 320230.8   313511.2
574: 2015-04-01 320402.3   313640.3

Answer 1

[ 中的列可以作为向量进行索引，因此我们首先为每一行创建一个向量 year(date) < year(date[..I]) & year(date) >= year(date[..I]) - 6 当日期在区间内时为真，然后得到 pop 按月：

df[,
    year:=year(date)
][, 
    avg_5yrs := sapply(1:.N, function(..I) mean(pop[year < year[..I] & year >= year[..I] -6])), by=month(date)
][, year:=NULL][]
            date      pop avg_5yrs
  1: 1967-07-01 198712.0      NaN
  2: 1967-08-01 198911.0      NaN
  3: 1967-09-01 199113.0      NaN
  4: 1967-10-01 199311.0      NaN
  5: 1967-11-01 199498.0      NaN
 ---                             
570: 2014-12-01 319746.2 311845.5
571: 2015-01-01 319928.6 312028.1
572: 2015-02-01 320074.5 312192.6
573: 2015-03-01 320230.8 312357.4
574: 2015-04-01 320402.3 312498.1

R数据表创建前五年的平均值

R datatable create the average value over the five previous years

r

date

data-manipulation

lubridate

data.table