Creates a per-record table that shows which sources (and/or labels/strings) each item was found in.
record_level_table( citations, include = "sources", include_empty = TRUE, return = c("tibble", "DT"), indicator_presence = NULL, indicator_absence = NULL )
A deduplicated tibble as returned by
Which metadata should be included in the table? Defaults to 'sources', can be replaced or expanded with 'labels' and/or 'strings'
Should records with empty metadata (e.g., no information on 'sources') be included in the table? Defaults to FALSE.
tibblethat can be exported, e.g. as a csv, or a DataTable (
DT) that allows for interactive exploration. Note that the DataTable allows users to download a .csv file; in that file, presence and absence is always indicated as TRUE and FALSE to prevent issues with character encodings.
How should it be indicated that a value is present in a source/label/string? Defaults to TRUE in tibbles and a tickmark in DT tables
How should it be indicated that a value is not present in a source/label/string? Defaults to FALSE in tibbles and a cross in DT tables
A tibble or DataTable containing the per-record table that shows which sources (and/or labels/strings) each item was found in.
# Load example data from the package examplecitations_path <- system.file("extdata", "examplecitations.rds", package = "CiteSource") examplecitations <- readRDS(examplecitations_path) # Deduplicate citations and compare sources unique_citations <- dedup_citations(examplecitations) #> formatting data... #> Warning: Search contains missing values for the record_id column. A record_id will be created using row numbers #> identifying potential duplicates... #> identified duplicates! #> Joining with `by = join_by(record_id)` #> flagging potential pairs for manual dedup... #> Warning: There were 2 warnings in `mutate()`. #> The first warning was: #> ℹ In argument: `min_id = min(duplicate_id.x, duplicate_id.y)`. #> Caused by warning in `min()`: #> ! no non-missing arguments, returning NA #> ℹ Run `dplyr::last_dplyr_warnings()` to see the 1 remaining warning. #> Joining with `by = join_by(duplicate_id.x, duplicate_id.y)` #> 165 citations loaded... #> 67 duplicate citations removed... #> 98 unique citations remaining! unique_citations |> dplyr::filter(stringr::str_detect(cite_label, "final")) |> record_level_table(return = "DT")