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Normalise string

Source: R/normalise_strings_class.R
normalise_strings.Rd

Replace matching (sub)strings based on a provided dictionary of search terms and their replacements.

Usage

normalise_strings(
  search_column,
  output_column = NULL,
  dictionary = list(),
  ...
)

Arguments

search_column

(character) The column name of the input annotation_source that will be searched for matching (sub)strings.

output_column

(character, NULL) The name of a new column that the modified strings will be stored in. If NULL the search_column will be replaced. The default is NULL.

dictionary

(list, annotation_database) A list of patterns and functions that take the input pattern and return a replacement string. A annotation_database object containing a suitable list can also be used here. The default is list().

...

Additional slots and values passed to struct_class.

Value

A normalise_strings object with the following output slots:

updated(annotation_source) The updated annotations as an annotation_source object.

Details

This object makes use of functionality from the following packages:

  • dplyr

Each item of the dictionary list should #' have at least two fields: "pattern" and "replace". "pattern" is used as inputs to the [grepl()] function to detect matches to the input pattern. Parameters such as perl = TRUE can also be included in the list and these will be passed to [grepl()], otherwise the defaults are used. When a match is detected the function in "replace" is called with the same inputs as [grepl()]. The "replace" function should return a new string. Alternatively replace = NA can be used to return NA for a matching pattern. If a character string is provided then [gsub()] will be used by default.

Inheritance

A normalise_strings object inherits the following struct classes:

[normalise_strings] -> [model] -> [struct_class]

References

Wickham H, François R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data Manipulation. R package version 1.1.4, https://CRAN.R-project.org/package=dplyr.

See also

grepl(), gsub()

Examples

M <- normalise_strings(
        search_column = character(0),
        output_column = NULL,
        dictionary = list())