r - Lag doesn't see the effects of mutate on previous rows -

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i seem have stumbled upon mutate/lag/ifelse behaviour cannot explain. have following (simplified) dataframe:

test <- data.frame(type = c("start", "end", "start", "start", "start", "start", "end"),                    stringsasfactors = false)  > test    type 1 start 2   end 3 start 4 start 5 start 6 start 7 start 8   end

i modify column type in order have sequence of alternating start , end pairs (note in test dataframe sequences of start possible, end never repeated):

> desired    type 1 start 2   end 3 start 4   end 5 start 6   end 7 start 8   end

i thought achieve goal following code:

test %>%  mutate(type = ifelse( type == "start" &                        dplyr::lag(type, n=1, default="end") == "start" &                        dplyr::lead(type, n=1, default="end") == "start", "end" , type))

the code should detect rows in start preceded start , followed start, in case type value changed end. after change, following start (row number 5 of test) should not matched, since previous type value end. unfortunately, output of command following:

   type 1 start 2   end 3 start 4   end 5   end 6   end 7 start 8   end

it's value seen lag not affected mutate. how supposed work? there way code in way lag sees effects of mutate on previous row?

versions: r version 3.2.3 (2015-12-10), dplyr_0.4.3

update: reason why above code doesn't work explained paul rougieux below: lead , lag fixed , not take account further modification. guess correct answer "it cannot done straightforwardly using dplyr".

defining lag , lead variables separately in mutate() show call ifelse(type == "start" & lag == "start" & lead == "start", "end" , type) not going work:

test <- data.frame(type = c("start", "end", "start", "start", "start", "start", "end"), stringsasfactors = false) test %>%     mutate(lag = dplyr::lag(type, n=1, default="end"),            lead = dplyr::lead(type, n=1, default="end"),            type2 = ifelse(type == "start" & lag == "start" & lead == "start",                           "end" , type))  #   type   lag  lead type2 #1 start   end   end start #2   end start start   end #3 start   end start start #4 start start start   end #5 start start start   end #6 start start   end start #7   end start   end   end

dplyr::mutate() modifies vector whole. lead , lag fixed , not take account further modification type vector. want `reduce()̀ function in case. check help(reduce).


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