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Create a Detailed Record Table

Source: R/new_count_and_table.R
create_detailed_record_table.Rd

This function generates a formatted summary table using the gt package, which displays detailed counts for each citation source. The table includes columns for the number of records imported, distinct records, unique records, non-unique records, and various contribution percentages. Data from the function calculate_detailed_records is pre-formatted for this table.

Usage

create_detailed_record_table(data)

Arguments

data

A data frame containing the detailed counts for each citation source. The data frame must include the following columns:

  • Source: The name of the citation source.

  • Records Imported: The total number of records imported from the source.

  • Distinct Records: The number of distinct records after deduplication within the source.

  • Unique Records: The number of records unique to that source.

  • Non-unique Records: The number of records found in at least one other source.

  • Source Contribution %: The percentage contribution of each source to the total distinct records.

  • Source Unique Contribution %: The percentage contribution of each source to the total unique records.

  • Source Unique %: The percentage of records from each source that were unique.

Value

A gt table object summarizing the detailed record counts for each citation source.

Details

The function checks for the presence of all required columns in the input data frame. If any required columns are missing, the function stops and returns an error message specifying the missing columns. This ensures that the input data is correctly formatted before attempting to generate the table.

The generated table includes a header and footnotes that provide additional context for each column, explaining the meaning of the data presented.

Examples

# Example usage with a sample dataset
sample_data <- data.frame(
  Source = c("Source1", "Source2", "Source3", "Total"),
  `Records Imported` = c(100, 150, 250, 500),
  `Distinct Records` = c(90, 140, 230, 460),
  `Unique Records` = c(50, 70, 120, 240),
  `Non-unique Records` = c(40, 70, 110, 220),
  `Source Contribution %` = c("39.1%", "60.9%", "100%", "100%"),
  `Source Unique Contribution %` = c("41.7%", "58.3%", "100%", "100%"),
  `Source Unique %` = c("55.6%", "50%", "52.2%", "52.2%"),
  check.names = FALSE
)

# Create the detailed record table
create_detailed_record_table(sample_data)



  
Record Summary
    

      Records Imported1
      Distinct Records2
      Unique Records3
      Non-unique Records4
      Source Contribution %5
      Source Unique Contribution %6
      Source Unique %7
    
Source1
100
90
50
40
39.1%
41.7%
55.6%
Source2
150
140
70
70
60.9%
58.3%
50%
Source3
250
230
120
110
100%
100%
52.2%
Total
500
8 460
240
220
100%
100%
52.2%
1 Number of raw records imported from each database.
    
2 Number of records after internal source deduplication.
    
3 Number of records not found in another source.
    
4 Number of records found in at least one other source.
    
5 Percent distinct records contributed to the total number of distinct records.
    
6 Percent of unique records contributed to the total unique records.
    
7 Percentage of records that were unique from each source.
    
8 Total citations discovered (after internal and cross-source deduplication).