This function merges two literature matrices based on specified key columns, with options for full or inner joins and duplicate column removal.
Usage
merge_matrix(
.data,
.data2,
by = NULL,
all = FALSE,
remove_dups = TRUE,
suffixes = c(".x", ".y"),
silent = FALSE
)Arguments
- .data
A data frame to be merged.
- .data2
A second data frame to be merged with `.data`.
- by
A character vector specifying the column(s) to merge by. Must exist in both data frames.
- all
A logical value indicating whether to perform a full join (`TRUE`) or an inner join (`FALSE`, default).
- remove_dups
A logical value indicating whether to remove duplicate columns before merging. Default is `TRUE`.
- suffixes
A character vector of length 2 specifying suffixes to apply to overlapping column names from `.data` and `.data2`, respectively. Default is `c(".x", ".y")`.
- silent
A logical value indicating whether to suppress messages about duplicate column removal. Default is `FALSE`.
Details
The function first ensures that `.data` and `.data2` are valid data frames and checks that the `by` columns exist in both. If `remove_dups = TRUE`, duplicate columns are removed before merging. The function then performs either a full or inner join using `dplyr::full_join()` or `dplyr::inner_join()`, respectively.
Examples
df1 <- data.frame(id = c(1, 2, 3), value1 = c("A", "B", "C"))
df2 <- data.frame(id = c(2, 3, 4), value2 = c("X", "Y", "Z"))
# Inner join (default)
merge_matrix(df1, df2, by = "id")
#> Removing duplicate columns...
#> id value1 value2
#> 1 2 B X
#> 2 3 C Y
# Full join
merge_matrix(df1, df2, by = "id", all = TRUE)
#> Removing duplicate columns...
#> id value1 value2
#> 1 1 A <NA>
#> 2 2 B X
#> 3 3 C Y
#> 4 4 <NA> Z
# Remove duplicate columns before merging
df3 <- data.frame(id = c(1, 2, 3), value1 = c("A", "B", "C"), extra = c(1, 2, 3))
df4 <- data.frame(id = c(2, 3, 4), value2 = c("X", "Y", "Z"), extra = c(4, 5, 6))
merge_matrix(df3, df4, by = "id", remove_dups = TRUE)
#> Removing duplicate columns...
#> id value1 extra.x value2 extra.y
#> 1 2 B 2 X 4
#> 2 3 C 3 Y 5