You can use data.table
from R
. Assuming that ‘time’ column is of ‘Date’ class,
library(data.table)#v1.9.5+
DT1 <- setDT(df1)[, list(time=seq(min(time), max(time), by ='day')),
by =.(shop_id, item_id)]
setkeyv(df1, names(df1)[1:3])[DT1][is.na(value), value:=0]
# shop_id item_id time value
#1: 150 1 2015-07-10 3
#2: 150 1 2015-07-11 5
#3: 150 1 2015-07-12 0
#4: 150 1 2015-07-13 2
#5: 150 2 2015-07-10 15
#6: 150 2 2015-07-11 0
#7: 150 2 2015-07-12 12
In the devel version, you can also do this without setting the ‘key’. Instructions to install the devel version are here
df1[DT1, on =c('shop_id', 'item_id', 'time')][is.na(value), value:=0]
# shop_id item_id time value
#1: 150 1 2015-07-10 3
#2: 150 1 2015-07-11 5
#3: 150 1 2015-07-12 0
#4: 150 1 2015-07-13 2
#5: 150 2 2015-07-10 15
#6: 150 2 2015-07-11 0
#7: 150 2 2015-07-12 12
Or as @Arun suggested, a more efficient option would be
DT1[, value := 0L][df1, value := i.value, on = c('shop_id', 'item_id', 'time')]
DT1