Search: Search Columns of a Data Frame

Description

Search - Find terms located in columns of a data frame.

boolean_search - Conducts a Boolean search for terms/strings within a character vector.

%bs% - Binary operator version of boolean_search .

Usage

Search(dataframe, term, column.name = NULL, max.distance = 0.02, ...)
boolean_search(
  text.var,
  terms,
  ignore.case = TRUE,
  values = FALSE,
  exclude = NULL,
  apostrophe.remove = FALSE,
  char.keep = NULL,
  digit.remove = FALSE
)
text.var %bs% terms

Value

Search - Returns the rows of the data frame that match the search term.

boolean_search - Returns the values (or indices) of a vector of strings that match given terms.

Arguments

dataframe: A dataframe object to search.
term: A character string to search for.
column.name: Optional column of the data frame to search (character name or integer index).
max.distance: Maximum distance allowed for a match. Expressed either as integer, or as a fraction of the pattern length times the maximal transformation cost (will be replaced by the smallest integer not less than the corresponding fraction).
text.var: The text variable.
terms: A character string(s) to search for. The terms are arranged in a single string with AND (use AND or && to connect terms together) and OR (use OR or || to allow for searches of either set of terms. Spaces may be used to control what is searched for. For example using " I " on c("I'm", "I want", "in") will result in FALSE TRUE FALSE whereas "I" will match all three (if case is ignored).
ignore.case: logical. If TRUE case is ignored.
values: logical. Should the values be returned or the index of the values.
exclude: Terms to exclude from the search. If one of these terms is found in the sentence it cannot be returned.
apostrophe.remove: logical. If TRUE removes apostrophes from the text before examining.
char.keep: A character vector of symbol character (i.e., punctuation) that strip should keep. The default is to strip everything except apostrophes. termco attempts to auto detect characters to keep based on the elements in match.list.
digit.remove: logical. If TRUE strips digits from the text before counting. termco attempts to auto detect if digits should be retained based on the elements in match.list.
...: Other arguments passed to agrep.

Details

The terms string is first split by the OR separators into a list. Next the list of vectors is split on the AND separator to produce a list of vectors of search terms. Each sentence is matched against the terms. For a sentence to be counted it must fit all of the terms in an AND Boolean or one of the conditions in an OR Boolean.

Examples

Run this code

if (FALSE) {
## Dataframe search:
(SampDF <- data.frame("islands"=names(islands)[1:32],mtcars, row.names=NULL))

Search(SampDF, "Cuba", "islands")
Search(SampDF, "New", "islands")
Search(SampDF, "Ho")
Search(SampDF, "Ho", max.distance = 0)
Search(SampDF, "Axel Heiberg")
Search(SampDF, 19) #too much tolerance in max.distance
Search(SampDF, 19, max.distance = 0)
Search(SampDF, 19, "qsec", max.distance = 0)

##Boolean search:
boolean_search(DATA$state, " I ORliar&&stinks")
boolean_search(DATA$state, " I &&.", values=TRUE)
boolean_search(DATA$state, " I OR.", values=TRUE)
boolean_search(DATA$state, " I &&.")

## Exclusion:
boolean_search(DATA$state, " I ||.", values=TRUE)
boolean_search(DATA$state, " I ||.", exclude = c("way", "truth"), values=TRUE)

## From stackoverflow: http://stackoverflow.com/q/19640562/1000343
dat <- data.frame(x = c("Doggy", "Hello", "Hi Dog", "Zebra"), y = 1:4)
z <- data.frame(z =c("Hello", "Dog"))

dat[boolean_search(dat$x, paste(z$z, collapse = "OR")), ]

## Binary operator version
dat[dat$x %bs% paste(z$z, collapse = "OR"), ]

## Passing to `trans_context`
inds <- boolean_search(DATA.SPLIT$state, " I&&.|| I&&!", ignore.case = FALSE)
with(DATA.SPLIT, trans_context(state, person, inds=inds))

(inds2 <- boolean_search(raj$dialogue, spaste(paste(negation.words, 
    collapse = " || "))))
trans_context(raj$dialogue, raj$person, inds2)
}