滚动总和 [英] R dplyr rolling sum
问题描述
#create data
dg = expand.grid（site = c（Boston 纽约），
年= 2000：2004）
dg $ animal =dog
dg $ animal [10] =cat; dg $ animal = as.factor dg $动物）
dg $ count = rpois（dim（dg）[1]，5）
如果我将运行下面的代码，因为我只有一行与猫，一个得到（错误：k <= n不是真的）错误
#running平均
dg2 = dg％>％
安排（网站，年，动物）％>％
group_by（site，动物）％>％
＃filter（animal ==dog）％>％
mutate（roll_sum = rollsum（x = count，2，align =right，fill = ）
我已经尝试通过使用以下代码来解决这个问题，该代码过滤掉猫值并做一个后续的合并，但我想知道是否可以直接在dplyr内部这样做，特别是在这个解决方案中，必须指定/知道n预先为每个变量提供唯一行的数量，并手动调整，如果更改滚动总和的范围等。
dg2 = dg％>％
安排（网站，年，动物）％>％
group_by（网站，动物）％>％
过滤器（动物==狗）％ >％
mutate（roll_sum = rollsum（x = count，2，align =right，fill = NA））
merge（dg，dg2，c（site year，animal，count），all.x = TRUE）
网站年动物数量roll_sum
1波士顿2000狗5 NA
2波士顿2001狗6 11
3波士顿2002狗6 12
4波士顿2003年狗5 11
5波士顿2004年狗3 8
6纽约2000狗8 NA
7纽约2001狗3 11
8纽约2002年狗12 15
9纽约2003年狗3 15
10纽约2004年猫3 NA
非常感谢 - W
n RcppRoll :: roll_sum 返回NA c>）小于窗口大小（ k ）。 set.seed（1）
dg $ count = rpois（dim（dg）[1]，5）
库（RcppRoll）
库（dplyr）
dg％>％
安排（站点，年，动物）％>％
group_by ）％>％
mutate（roll_sum = roll_sum（count，2，align =right，fill = NA））
＃site year animal count roll_sum
＃1波士顿2000狗4 NA
＃2波士顿2001年狗5 9
＃3波士顿2002年狗3 8
＃4波士顿2003年狗9 12
＃5波士顿2004年狗6 15
＃ 6纽约2000狗4 NA
＃7纽约2001年狗8 12
＃8纽约2002年狗8 16
＃9纽约2003年狗6 14
＃10新约克2004猫2 NA
i am implementing a rolling sum calculation through dplyr, but in my database i have a number of variables that have only one or only a few observations, causing an (k is smaller than n) error. i have tried to resolve this in thisj example with filter and merge, but wondering if there is a way to do this more elegantly and automatically within dplyr. please see the example below
#create data
dg = expand.grid(site = c("Boston","New York"),
year = 2000:2004)
dg$animal="dog"
dg$animal[10]="cat";dg$animal=as.factor(dg$animal)
dg$count = rpois(dim(dg)[1], 5)
If i would run the code below, because i only have one row with "cat", one gets the (Error: k <= n is not true) error
#running average
dg2 = dg %>%
arrange(site,year,animal) %>%
group_by(site,animal) %>%
# filter(animal=="dog") %>%
mutate(roll_sum = rollsum(x = count, 2, align = "right", fill = NA))
i have tried to solve this by using the following code, which filters out the "cat" value and does a subsequent merge, but I was wondering whether one can do this directly inside dplyr, especially as in this solution one would have to specify / know the number of unique rows for each variable in advance and adjust manually if one would change the range of the rolling sum, etc.
dg2 = dg %>%
arrange(site,year,animal) %>%
group_by(site,animal) %>%
filter(animal=="dog") %>%
mutate(roll_sum = rollsum(x = count, 2, align = "right", fill = NA))
merge(dg,dg2,c("site", "year","animal","count"),all.x=TRUE)
site year animal count roll_sum
1 Boston 2000 dog 5 NA
2 Boston 2001 dog 6 11
3 Boston 2002 dog 6 12
4 Boston 2003 dog 5 11
5 Boston 2004 dog 3 8
6 New York 2000 dog 8 NA
7 New York 2001 dog 3 11
8 New York 2002 dog 12 15
9 New York 2003 dog 3 15
10 New York 2004 cat 3 NA
Many thanks - W
You can instead use RcppRoll::roll_sum which returns NA if the sample size(n) is less than the window size(k).
set.seed(1)
dg$count = rpois(dim(dg)[1], 5)
library(RcppRoll)
library(dplyr)
dg %>%
arrange(site,year,animal) %>%
group_by(site, animal) %>%
mutate(roll_sum = roll_sum(count, 2, align = "right", fill = NA))
# site year animal count roll_sum
#1 Boston 2000 dog 4 NA
#2 Boston 2001 dog 5 9
#3 Boston 2002 dog 3 8
#4 Boston 2003 dog 9 12
#5 Boston 2004 dog 6 15
#6 New York 2000 dog 4 NA
#7 New York 2001 dog 8 12
#8 New York 2002 dog 8 16
#9 New York 2003 dog 6 14
#10 New York 2004 cat 2 NA
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