rm_zip {qdapRegex}

Remove/Replace/Extract Zip Codes

Description

Remove/replace/extract zip codes from a string.

Usage

rm_zip(
  text.var,
  trim = !extract,
  clean = TRUE,
  pattern = "@rm_zip",
  replacement = "",
  extract = FALSE,
  dictionary = getOption("regex.library"),
  ...
)

ex_zip(
  text.var,
  trim = !extract,
  clean = TRUE,
  pattern = "@rm_zip",
  replacement = "",
  extract = TRUE,
  dictionary = getOption("regex.library"),
  ...
)

Arguments

text.var

The text variable.

trim

logical. If TRUE removes leading and trailing white spaces.

clean

trim logical. If TRUE extra white spaces and escaped character will be removed.

pattern

A character string containing a regular expression (or character string for fixed = TRUE) to be matched in the given character vector. Default, @rm_zip uses the rm_zip regex from the regular expression dictionary from the dictionary argument.

replacement

Replacement for matched pattern.

extract

logical. If TRUE the zip codes are extracted into a list of vectors.

dictionary

A dictionary of canned regular expressions to search within if pattern begins with "@rm_".

...

Other arguments passed to gsub.

Value

Returns a character string with U.S. 5 and 5+4 zip codes removed.

Author(s)

stackoverflow's hwnd and Tyler Rinker <[e-mail]>.

References

The time regular expression was taken from: https://stackoverflow.com/a/25223890/1000343

See Also

gsub, stri_extract_all_regex

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_title_name(), rm_url(), rm_white()

Examples

x <- c("Mr. Bean bought 2 tickets 2-613-213-4567",
  "43 Butter Rd, Brossard QC K0A 3P0 - 613 213 4567", 
  "Rat Race, XX, 12345",
  "Ignore phone numbers(613)2134567",
  "Grab zips with dashes 12345-6789 or no space before12345-6789",  
  "Grab zips with spaces 12345 6789 or no space before12345 6789",
  "I like 1234567 dogs"
)

rm_zip(x)
ex_zip(x)

## ======================= ##
## BUILD YOUR OWN FUNCTION ##
## ======================= ##

## example from: https://stackoverflow.com/a/26092576/1000343
zips <- data.frame(id = seq(1, 6), 
    address = c("Company, 18540 Main Ave., City, ST 12345", 
    "Company 18540 Main Ave. City ST 12345-0000", 
    "Company 18540 Main Ave. City State 12345", 
    "Company, 18540 Main Ave., City, ST 12345 USA", 
    "Company, One Main Ave Suite 18540m, City, ST 12345",
    "company 12345678")
)

## Function to grab even if a character follows the zip

# paste together a more flexible regular expression    
pat <- pastex(
    "@rm_zip", 
    "(?<!\\d)\\d{5}(?!\\d)",
    "(?<!\\d)\\d{5}-\\d{4}(?!\\d)"
)
# Create your own function that extract is set to TRUE
ex_zip2 <- rm_(pattern=pat, extract=TRUE)
ex_zip2(zips$address)

## Function to extract just 5 digit zips

ex_zip3 <- rm_(pattern="(?<!\\d)\\d{5}(?!\\d)", extract=TRUE)
ex_zip3(zips$address)