Select or remove tokens from a tokens object

These function select or discard tokens from a tokens object. For convenience, the functions tokens_remove and tokens_keep are defined as shortcuts for tokens_select(x, pattern, selection = "remove") and tokens_select(x, pattern, selection = "keep"), respectively. The most common usage for tokens_remove will be to eliminate stop words from a text or text-based object, while the most common use of tokens_select will be to select tokens with only positive pattern matches from a list of regular expressions, including a dictionary. startpos and endpos determine the positions of tokens searched for pattern and areas affected are expanded by window.

tokens_select(
  x,
  pattern,
  selection = c("keep", "remove"),
  valuetype = c("glob", "regex", "fixed"),
  case_insensitive = TRUE,
  padding = FALSE,
  window = 0,
  min_nchar = NULL,
  max_nchar = NULL,
  startpos = 1L,
  endpos = -1L,
  verbose = quanteda_options("verbose")
)

tokens_remove(x, ...)

tokens_keep(x, ...)

Arguments

x	tokens object whose token elements will be removed or kept
pattern	a character vector, list of character vectors, dictionary, or collocations object. See pattern for details.
selection	whether to "keep" or "remove" the tokens matching pattern
valuetype	the type of pattern matching: "glob" for "glob"-style wildcard expressions; "regex" for regular expressions; or "fixed" for exact matching. See valuetype for details.
case_insensitive	logical; if TRUE, ignore case when matching a pattern or dictionary values
padding	if TRUE, leave an empty string where the removed tokens previously existed. This is useful if a positional match is needed between the pre- and post-selected tokens, for instance if a window of adjacency needs to be computed.
window	integer of length 1 or 2; the size of the window of tokens adjacent to pattern that will be selected. The window is symmetric unless a vector of two elements is supplied, in which case the first element will be the token length of the window before pattern, and the second will be the token length of the window after pattern. The default is 0, meaning that only the pattern matched token(s) are selected, with no adjacent terms. Terms from overlapping windows are never double-counted, but simply returned in the pattern match. This is because tokens_select never redefines the document units; for this, see kwic().
min_nchar, max_nchar	optional numerics specifying the minimum and maximum length in characters for tokens to be removed or kept; defaults are NULL for no limits. These are applied after (and hence, in addition to) any selection based on pattern matches.
startpos, endpos	integer; position of tokens in documents where pattern matching starts and ends, where 1 is the first token in a document. For negative indexes, counting starts at the ending token of the document, so that -1 denotes the last token in the document, -2 the second to last, etc. When the length of the vector is equal to ndoc, tokens in corresponding positions will be selected. Otherwise, only the first element in the vector is used.
verbose	if TRUE print messages about how many tokens were selected or removed
...	additional arguments passed by tokens_remove and tokens_keep to tokens_select. Cannot include selection.

Value

a tokens object with tokens selected or removed based on their match to pattern

Examples

## tokens_select with simple examples
toks <- as.tokens(list(letters, LETTERS))
tokens_select(toks, c("b", "e", "f"), selection = "keep", padding = FALSE)
#> Tokens consisting of 2 documents.
#> text1 :
#> [1] "b" "e" "f"
#> 
#> text2 :
#> [1] "B" "E" "F"
#> 
tokens_select(toks, c("b", "e", "f"), selection = "keep", padding = TRUE)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] ""  "b" ""  ""  "e" "f" ""  ""  ""  ""  ""  "" 
#> [ ... and 14 more ]
#> 
#> text2 :
#>  [1] ""  "B" ""  ""  "E" "F" ""  ""  ""  ""  ""  "" 
#> [ ... and 14 more ]
#> 
tokens_select(toks, c("b", "e", "f"), selection = "remove", padding = FALSE)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "a" "c" "d" "g" "h" "i" "j" "k" "l" "m" "n" "o"
#> [ ... and 11 more ]
#> 
#> text2 :
#>  [1] "A" "C" "D" "G" "H" "I" "J" "K" "L" "M" "N" "O"
#> [ ... and 11 more ]
#> 
tokens_select(toks, c("b", "e", "f"), selection = "remove", padding = TRUE)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "a" ""  "c" "d" ""  ""  "g" "h" "i" "j" "k" "l"
#> [ ... and 14 more ]
#> 
#> text2 :
#>  [1] "A" ""  "C" "D" ""  ""  "G" "H" "I" "J" "K" "L"
#> [ ... and 14 more ]
#> 

# how case_insensitive works
tokens_select(toks, c("b", "e", "f"), selection = "remove", case_insensitive = TRUE)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "a" "c" "d" "g" "h" "i" "j" "k" "l" "m" "n" "o"
#> [ ... and 11 more ]
#> 
#> text2 :
#>  [1] "A" "C" "D" "G" "H" "I" "J" "K" "L" "M" "N" "O"
#> [ ... and 11 more ]
#> 
tokens_select(toks, c("b", "e", "f"), selection = "remove", case_insensitive = FALSE)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "a" "c" "d" "g" "h" "i" "j" "k" "l" "m" "n" "o"
#> [ ... and 11 more ]
#> 
#> text2 :
#>  [1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L"
#> [ ... and 14 more ]
#> 

# use window
tokens_select(toks, c("b", "f"), selection = "keep", window = 1)
#> Tokens consisting of 2 documents.
#> text1 :
#> [1] "a" "b" "c" "e" "f" "g"
#> 
#> text2 :
#> [1] "A" "B" "C" "E" "F" "G"
#> 
tokens_select(toks, c("b", "f"), selection = "remove", window = 1)
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "d" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r"
#> [ ... and 8 more ]
#> 
#> text2 :
#>  [1] "D" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R"
#> [ ... and 8 more ]
#> 
tokens_remove(toks, c("b", "f"), window = c(0, 1))
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "a" "d" "e" "h" "i" "j" "k" "l" "m" "n" "o" "p"
#> [ ... and 10 more ]
#> 
#> text2 :
#>  [1] "A" "D" "E" "H" "I" "J" "K" "L" "M" "N" "O" "P"
#> [ ... and 10 more ]
#> 
tokens_select(toks, pattern = c("e", "g"), window = c(1, 2))
#> Tokens consisting of 2 documents.
#> text1 :
#> [1] "d" "e" "f" "g" "h" "i"
#> 
#> text2 :
#> [1] "D" "E" "F" "G" "H" "I"
#> 

# tokens_remove example: remove stopwords
txt <- c(wash1 <- "Fellow citizens, I am again called upon by the voice of my
                   country to execute the functions of its Chief Magistrate.",
         wash2 <- "When the occasion proper for it shall arrive, I shall
                   endeavor to express the high sense I entertain of this
                   distinguished honor.")
tokens_remove(tokens(txt, remove_punct = TRUE), stopwords("english"))
#> Tokens consisting of 2 documents.
#> text1 :
#>  [1] "Fellow"     "citizens"   "called"     "upon"       "voice"     
#>  [6] "country"    "execute"    "functions"  "Chief"      "Magistrate"
#> 
#> text2 :
#>  [1] "occasion"      "proper"        "shall"         "arrive"       
#>  [5] "shall"         "endeavor"      "express"       "high"         
#>  [9] "sense"         "entertain"     "distinguished" "honor"        
#> 

# token_keep example: keep two-letter words
tokens_keep(tokens(txt, remove_punct = TRUE), "??")
#> Tokens consisting of 2 documents.
#> text1 :
#> [1] "am" "by" "of" "my" "to" "of"
#> 
#> text2 :
#> [1] "it" "to" "of"
#>