replace_join.R

## join x and y, replacing any columns in x with matching columns from y
## x    : the table with values to be replaced
## y    : the table containing replacement values
## cols : the key columns (i.e., cols to join on)
replace_join <- function(x, y, cols) {
  keep <- setdiff(names(x), names(y))
  dplyr::inner_join(dplyr::select_(x, .dots = c(cols, keep)), y, cols)
}

## like above, but:
## if an x row has no matching row in y, keep values from x
## NB: the common columns must have same data types
##     also, does not check for unique match in y
patch_join <- function(x, y, cols) {
  common <- intersect(names(x), names(y))
  keep_x <- setdiff(names(x), common)
  df1 <- dplyr::inner_join(dplyr::select_(x, .dots = c(cols, keep_x)),
                           dplyr::select_(y, .dots = c(cols, common)),
                           cols)
  dplyr::bind_rows(df1, dplyr::anti_join(x, df1, cols))
}

## example:
##
## x <- data.frame(A = 1:3, B = 4:6, C = 7:9, D = 1:3)
## y <- data.frame(A = 1:2, C = 11:10, D = 5:4, E = letters[5:6])

## replace_join(x, y, "A")
## patch_join(x, y, "A")