r - How to Detect and Mark Change within a Column in Another Column -


i'm trying mark when process starts , ends. code needs detect when change begins , when ends, marking in column.

example data:

date  process  2007     0             2008     1 2009     1 2010     1 2011     1 2012     1 2013     0

goal:

date  process        status 2007     0             na 2008     1        process_start 2009     1             na 2010     1             na 2011     1             na 2012     1        process_end 2013     0             na

maybe calculating diff , lagging in both directions:

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

version without factors:

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]

note in case of single year process have "start & end" situation.

update 2

if series starts (or ends) process = 1 expected output might not na start (or 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]

more complicated example:

set.seed(4) df1 <- data.frame(date = 2007:(2007+24), process = sample(c(0,1, 1), 25, true))

the last version produces:

#    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

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