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I have a data set with the following variables: 1. Group 2. Status (Takes on variables 1-7)

I need to create a flag where the following conditions are met: -Flag 1=0 when Status <6, else Flag 1= 1 when Status >=6 -Within each group: If Status has reached 6 or higher and goes back down to below 6, the flag 1 must remain as 1.

The desired table would look as follows:

enter image description here

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3 Answers 3

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Using ave to apply a custom function within each group.

df <- data.frame(Group = c(1,2,2,3,3,3,3,4,4), Status = c(1,2,3,7,6,5,4,5,6)) df$Flag = ave(df$Status, df$Group, FUN = function(x) {cumsum(x >= 6) > 0})
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data.table and cummax do the job:

library(data.table) dt <- data.table(Group = c(1,2,2,3,3,3,3,4,4), Status = c(1,2,3,7,6,5,4,5,6)) dt[, flag := cummax(Status >= 6), by = Group] dt Group Status flag 1: 1 1 0 2: 2 2 0 3: 2 3 0 4: 3 7 1 5: 3 6 1 6: 3 5 1 7: 3 4 1 8: 4 5 0 9: 4 6 1
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df$flag <- ifelse(df$status >6,0,1)

df$status <- ifelse(df$status =>6,5,df$status)

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Thanks for this. This solves the first condition but does not address the second condition.
Add another ifelse and give reference of status variable

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