First, let\'s start with DataFrame 1 (DF1) :
DF1 <- data.frame(c(\"06/19/2016\", \"06/20/2016\", \"06/21/2016\", \"06/22/2016\",
\"06
df <- merge(DF1, DF2, by = c("date", "id"))
df$newcolumn <- ifelse(is.na(df$column.y), df$column.x, df$column.y, all.x = TRUE)
Replace column
with your variable.
You could use the join functionality of the data.table-package for this:
library(data.table)
setDT(DF1)
setDT(DF2)
DF1[DF2, on = .(date, id), `:=` (city = i.city, sales = i.sales)]
which gives:
> DF1 date id sales cost city 1: 06/19/2016 1 9999 101 LON 2: 06/20/2016 1 150 102 MTL 3: 06/21/2016 1 151 104 MTL 4: 06/22/2016 1 152 107 MTL 5: 06/23/2016 1 155 99 MTL 6: 06/19/2016 2 84 55 NY 7: 06/20/2016 2 83 55 NY 8: 06/21/2016 2 80 56 NY 9: 06/22/2016 2 777 57 QC 10: 06/23/2016 2 555 58 QC
When you have many columns in both datasets, it is easier to use mget
instead off typing all the column names. For the used data in the question it would look like:
DF1[DF2, on = .(date, id), names(DF2)[3:4] := mget(paste0("i.", names(DF2)[3:4]))]
When you want to construct a vector of columnnames that need to be added beforehand, you could do this as follows:
cols <- names(DF2)[3:4]
DF1[DF2, on = .(date, id), (cols) := mget(paste0("i.", cols))]
df <- merge(DF1, DF2, by = c("date", "id"), all.x=TRUE)
tmp1 <- df[is.na(df$sales.y) & is.na(df$city.y),]
tmp1$sales.y <- NULL
tmp1$city.y <- NULL
names(tmp1)[names(tmp1) == "sales.x"] <- "sales"
names(tmp1)[names(tmp1) == "city.x"] <- "city"
tmp2 <- df[!is.na(df$sales.y) & !is.na(df$city.y),]
tmp2$sales.x <- NULL
tmp2$city.x <- NULL
names(tmp2)[names(tmp2) == "sales.y"] <- "sales"
names(tmp2)[names(tmp2) == "city.y"] <- "city"
results <- rbindlist(list(tmp1,tmp2), use.names= TRUE, fill = TRUE)