计算 R data.table 中前 3 行的总和(按方格) [英] calculating sum of previous 3 rows in R data.table (by grid-square)

问题描述

我想计算过去三天每个方格的降雨量，并将其作为新列添加到我的 data.table 中.为了清楚起见，我想总结当前和之前两 (2) 天的降雨量，对于每个气象网格方格

I would like to calculate the rainfall that has fallen over the last three days for each grid square, and add this as a new column in my data.table. To be clear, I want to sum up the current and PREVIOUS two (2) days of rainfall, for each meterological grid square

library ( zoo )
library (data.table)


# making the data.table
rain           <- c(NA, NA, NA, 0, 0, 5, 1, 0, 3, 10)  # rainfall values to work with
square         <- c(1,1,1,1,1,1,1,1,1,2)               # the geographic grid square for the rainfall measurement
desired_result <- c(NA, NA, NA, NA, NA, 5, 6, 6, 4, NA )  # this is the result I'm looking for (the last NA as we are now on to the first day of the second grid square)
weather <- data.table(rain, square, desired_result)  # making the data.table

我的回答是:这条线曾经有效，但不再有效

My attempt to answer: this line used to work, but no longer does

weather[, rain_3 := filter(rain, rep(1, 2), sides = 1), by = list(square)]  

所以我在这里尝试另一种方法:

So here I am trying another method:

# this next line gets the numbers right, but sums the following values, not the preceeding ones. 
weather$rain_3 <- rollapply(zoo(weather$rain), list(seq(-2,0)), sum)

# here I add in the by weather$ square, but still no success
weather$rain_3 <- rollapply(zoo(weather$rain), list(seq(-2,0)), sum, by= list(weather$square))

如果您有任何见解或建议，我将不胜感激.

I would greatly appreciate any insights or suggestions you may have.

非常感谢！

推荐答案

weather[, rain_3 := filter(rain, rep(1, 3), sides = 1), by = list(square)]  
#Error in filter(rain, rep(1, 3), sides = 1) : 
#  'filter' is longer than time series
weather[, rain_3 := if(.N > 2) filter(rain, rep(1, 3), sides = 1) else NA_real_, 
        by = square] 
#    rain square desired_result rain_3
# 1:   NA      1             NA     NA
# 2:   NA      1             NA     NA
# 3:   NA      1             NA     NA
# 4:    0      1             NA     NA
# 5:    0      1             NA     NA
# 6:    5      1              5      5
# 7:    1      1              6      6
# 8:    0      1              6      6
# 9:    3      1              4      4
#10:   10      2             NA     NA

注意不要加载 dplyr，因为它掩盖了 filter.如果需要 dplyr，可以显式调用 stats::filter.

Take care that dplyr is not loaded because it masks filter. If you need dplyr, you can call stats::filter explicitly.

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