I would like to create a new column which reports the reported col1 value larger than zero until a new col1 value larger than zero is encountered (see col2 in df2). I.e. the value of zero in col1 is replaced by the observed value larger than zero.
ID = c(1,1,1,1,1,1,1,1,2,2,2,2)
col1 = c(500,0,0,0,600,0,0,0,450,0,0,0)
df1 = data.frame(ID,col1)
ID = c(1,1,1,1,1,1,1,1,2,2,2,2)
col1 = c(500,0,0,0,600,0,0,0,450,0,0,0)
col2 = c(500,500,500,500,600,600,600,600,450,450,450,450)
df2 = data.frame(ID,col1,col2)
Any way of doing this?
We can use data.table with zoo. Convert the 'data.frame' to 'data.table' (setDT(df1)), assign a new column 'col2' with the values of 'col1', change the elements which are '0' to NA and then use na.locf to replace the NA elements with the previous non-NA element grouped by "ID".
library(zoo)
library(data.table)
setDT(df1)[, col2:=col1][col2==0, col2:= NA]
df1[,col2:= na.locf(col2) ,ID]
df1
# ID col1 col2
# 1: 1 500 500
# 2: 1 0 500
# 3: 1 0 500
# 4: 1 0 500
# 5: 1 600 600
# 6: 1 0 600
# 7: 1 0 600
# 8: 1 0 600
# 9: 2 450 450
#10: 2 0 450
#11: 2 0 450
#12: 2 0 450
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