也许通过计算diff
并在两个方向上滞后:
dif <- diff(df1$process)
df1$Status <- factor(c(NA, dif) - 2 * c(dif, NA), levels = -3:3)
levels(df1$Status) <- c(rep(NA, 4), "Start", "End", "Start&End")
# date process Status
# 1 2007 0 <NA>
# 2 2008 1 Start
# 3 2009 1 <NA>
# 4 2010 1 <NA>
# 5 2011 1 <NA>
# 6 2012 1 End
# 7 2013 0 <NA>
Update
不带因素的版本:
dif <- diff(df1$process)
df1$Status <- c(NA, dif) - 2 * c(dif, NA)
df1$Status <- c(rep(NA,4), "Start", "End", "Start&End")[df1$Status + 4]
请注意,如果是单年流程,则有“开始和结束”情况。
Update 2
如果系列以 process = 1 开始(或结束),则预期输出可能不是 NA,而是 Start(或 End):
dif <- diff(df1$process)
df1$Status <- c(df1$process[1], dif) - 2 * c(dif, -tail(df1$process,1))
df1$Status <- c(rep(NA,4), "Start", "End", "Start&End")[df1$Status + 4]
更复杂的例子:
set.seed(4)
df1 <- data.frame(date = 2007:(2007+24), process = sample(c(0,1, 1), 25, TRUE))
最后一个版本产生:
# date process Status
# 1 2007 1 Start&End
# 2 2008 0 <NA>
# 3 2009 0 <NA>
# 4 2010 0 <NA>
# 5 2011 1 Start&End
# 6 2012 0 <NA>
# 7 2013 1 Start
# 8 2014 1 <NA>
# 9 2015 1 End
# 10 2016 0 <NA>
# 11 2017 1 Start&End
# 12 2018 0 <NA>
# 13 2019 0 <NA>
# 14 2020 1 Start
# 15 2021 1 <NA>
# 16 2022 1 <NA>
# 17 2023 1 <NA>
# 18 2024 1 <NA>
# 19 2025 1 <NA>
# 20 2026 1 <NA>
# 21 2027 1 <NA>
# 22 2028 1 <NA>
# 23 2029 1 <NA>
# 24 2030 1 <NA>
# 25 2031 1 End