Replace specific values based on another dataframe

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

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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)