Kas*_*lma 4 aggregate r date dplyr
我的简化数据如下所示:
set.seed(1453); x = sample(0:1, 10, TRUE)
date = c('2016-01-01', '2016-01-05', '2016-01-07', '2016-01-12', '2016-01-16', '2016-01-20',
'2016-01-20', '2016-01-25', '2016-01-26', '2016-01-31')
df = data.frame(x, date = as.Date(date))
df
x date
1 2016-01-01
0 2016-01-05
1 2016-01-07
0 2016-01-12
0 2016-01-16
1 2016-01-20
1 2016-01-20
0 2016-01-25
0 2016-01-26
1 2016-01-31
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我想计算x == 1在指定时间段内出现的次数,例如距离当前日期的14天和30天(但不包括当前条目,如果是的话x == 1.所需的输出如下所示:
solution
x date x_plus14 x_plus30
1 2016-01-01 1 3
0 2016-01-05 1 4
1 2016-01-07 2 3
0 2016-01-12 2 3
0 2016-01-16 2 3
1 2016-01-20 2 2
1 2016-01-20 1 1
0 2016-01-25 1 1
0 2016-01-26 1 1
1 2016-01-31 0 0
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理想情况下,我希望这样dplyr,但这不是必须的.任何想法如何实现这一目标?非常感谢你的帮助!
添加另一种方法基于findInterval:
cs = cumsum(df$x) # cumulative number of occurences
data.frame(df,
plus14 = cs[findInterval(df$date + 14, df$date, left.open = TRUE)] - cs,
plus30 = cs[findInterval(df$date + 30, df$date, left.open = TRUE)] - cs)
# x date plus14 plus30
#1 1 2016-01-01 1 3
#2 0 2016-01-05 1 4
#3 1 2016-01-07 2 3
#4 0 2016-01-12 2 3
#5 0 2016-01-16 2 3
#6 1 2016-01-20 2 2
#7 1 2016-01-20 1 1
#8 0 2016-01-25 1 1
#9 0 2016-01-26 1 1
#10 1 2016-01-31 0 0
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