rm_dollar(text.var, trim = !extract, clean = TRUE, pattern = "@rm_dollar",
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_dollar uses the
rm_dollar regex from the regular expression dictpattern.TRUE the dollar strings are extracted into a
list of vectors.pattern begins with "@rm_".gsub.gsub,
stri_extract_all_regex
Other rm_.functions: 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_email;
rm_emoticon; rm_endmark;
rm_hash; rm_nchar_words;
rm_non_ascii; rm_number;
rm_percent; rm_phone;
rm_postal_code;
rm_repeated_characters;
rm_repeated_phrases;
rm_repeated_words; rm_tag;
rm_time; 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_zipx <- c("There is $5.50 for me.", "that's 45.6% of the pizza",
"14% is $26 or $25.99")
rm_dollar(x)
rm_dollar(x, extract=TRUE)Run the code above in your browser using DataLab