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
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
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