rm_postal_code(text.var, trim = !extract, clean = TRUE, pattern = "@rm_postal_code", replacement = "", extract = FALSE, dictionary = getOption("regex.library"), ...)
TRUE removes leading and trailing white
spaces.TRUE extra white spaces and escaped
character will be removed.fixed = TRUE) to be matched in the given
character vector.  Default, @rm_postal_code uses the
rm_postal_code regex from the regular expression dictionary from
the dictionary argument.pattern.TRUE the city & state are extracted into a
list of vectors.pattern begins with "@rm_".gsub.Remove/replace/extract postal codes.
x <- c("Anchorage, AK", "New York City, NY", "Some Place, Another Place, LA") rm_postal_code(x)[1] "Anchorage," "New York City," "Some Place, Another Place,"rm_postal_code(x, extract=TRUE)[[1]] [1] "AK" [[2]] [1] "NY" [[3]] [1] "LA"
gsub,
stri_extract_all_regex
Other rm_.functions: as_numeric,
  as_numeric2, rm_number;
  as_time, as_time2,
  rm_time, rm_transcript_time;
  rm_abbreviation; rm_angle,
  rm_bracket,
  rm_bracket_multiple,
  rm_curly, rm_round,
  rm_square; rm_between,
  rm_between_multiple;
  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_percent;
  rm_phone;
  rm_repeated_characters;
  rm_repeated_phrases;
  rm_repeated_words; rm_tag;
  rm_title_name;
  rm_twitter_url, rm_url;
  rm_white, rm_white_bracket,
  rm_white_colon,
  rm_white_comma,
  rm_white_endmark,
  rm_white_lead,
  rm_white_lead_trail,
  rm_white_multiple,
  rm_white_punctuation,
  rm_white_trail; rm_zip