Remove/replace/extract title (honorific) + person name(s) from a string.
rm_title_name(
text.var,
trim = !extract,
clean = TRUE,
pattern = "@rm_title_name",
replacement = "",
extract = FALSE,
dictionary = getOption("regex.library"),
...
)ex_title_name(
text.var,
trim = !extract,
clean = TRUE,
pattern = "@rm_title_name",
replacement = "",
extract = TRUE,
dictionary = getOption("regex.library"),
...
)
Returns a character string with person tags removed.
The text variable.
logical. If TRUE removes leading and trailing white
spaces.
trim logical. If TRUE extra white spaces and escaped
character will be removed.
A character string containing a regular expression (or
character string for fixed = TRUE) to be matched in the given
character vector. Default, @rm_title_name uses the
rm_title_name regex from the regular expression dictionary from
the dictionary argument.
Replacement for matched pattern.
logical. If TRUE the person tags are extracted into a
list of vectors.
A dictionary of canned regular expressions to search within
if pattern begins with "@rm_".
Other arguments passed to gsub.
Other rm_ functions:
rm_abbreviation(),
rm_between(),
rm_bracket(),
rm_caps_phrase(),
rm_caps(),
rm_citation_tex(),
rm_citation(),
rm_city_state_zip(),
rm_city_state(),
rm_date(),
rm_default(),
rm_dollar(),
rm_email(),
rm_emoticon(),
rm_endmark(),
rm_hash(),
rm_nchar_words(),
rm_non_ascii(),
rm_non_words(),
rm_number(),
rm_percent(),
rm_phone(),
rm_postal_code(),
rm_repeated_characters(),
rm_repeated_phrases(),
rm_repeated_words(),
rm_tag(),
rm_time(),
rm_url(),
rm_white(),
rm_zip()
x <- c("Dr. Brend is mizz hart's in mrs. Holtz's.",
"Where is mr. Bob Jr. and Ms. John Kennedy?")
rm_title_name(x)
ex_title_name(x)
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