我有一组个人的数据集,从每个人在不同的时间开始收集。
我需要从第一次输入数据开始的一年中对数据进行子集,如:myData[myDate >= "first entry" & myDate += "1 year"]
示例数据:
df_date <- data.frame( Name = c("Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim",
"Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue"),
Dates = c("2010-1-1", "2010-2-2", "2010-3-5","2010-4-17","2010-5-20",
"2010-6-29","2010-7-6","2010-8-9","2010-9-16","2010-10-28","2010-11-16","2010-12-28","2011-1-16","2011-2-28",
"2010-4-1", "2010-5-2", "2010-6-5","2010-7-17","2010-8-20",
"2010-9-29","2010-10-6","2010-11-9","2012-12-16","2011-1-28","2011-2-28","2011-3-28","2011-2-28","2011-3-28"),
Event = c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1) )
所需的输出将是Jim将拥有来自1/1/2010 - 12/28/2010
的数据和来自4/4/2010 - 3/28/2011
的Sue等。实际的数据集有>20个样本,都是从不同的时间开始的。
发布于 2022-09-13 14:47:00
使用tidyverse
和lubridate
函数的组合:
library(tidyverse)
library(lubridate)
df_date %>%
mutate(Dates = as_datetime(Dates)) %>%
group_by(Name) %>%
arrange(Dates, .by_group = T) %>%
filter(Dates <= first(Dates) + duration(1, units = "year"))
发布于 2022-09-13 14:51:28
与马丁·C·阿诺德(MartinC.Arnold)的答案类似,我得到了另一个基于dplyr
和lubridate
的答案。min(Dates) + years(1)
意味着在最小日期的基础上再加上一年。
library(dplyr)
library(lubridate)
df_date2 <- df_date %>%
mutate(Dates = ymd(Dates)) %>%
group_by(Name) %>%
filter(Dates <= min(Dates) + years(1)) %>%
ungroup()
https://stackoverflow.com/questions/73704912
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