quanteda (version 1.5.2)

dfm_select: Select features from a dfm or fcm

Description

This function selects or removes features from a dfm or fcm, based on feature name matches with pattern. The most common usages are to eliminate features from a dfm already constructed, such as stopwords, or to select only terms of interest from a dictionary.

Usage

dfm_select(
  x,
  pattern = NULL,
  selection = c("keep", "remove"),
  valuetype = c("glob", "regex", "fixed"),
  case_insensitive = TRUE,
  min_nchar = NULL,
  max_nchar = NULL,
  verbose = quanteda_options("verbose")
)
dfm_remove(x, ...)
dfm_keep(x, ...)
fcm_select(
  x,
  pattern = NULL,
  selection = c("keep", "remove"),
  valuetype = c("glob", "regex", "fixed"),
  case_insensitive = TRUE,
  verbose = quanteda_options("verbose"),
  ...
)
fcm_remove(x, pattern = NULL, ...)
fcm_keep(x, pattern = NULL, ...)

Arguments

x

the dfm or fcm object whose features will be selected

pattern

a character vector, list of character vectors, dictionary, or collocations object. See pattern for details.

selection

whether to keep or remove the features

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.

For dfm_select, pattern may also be a dfm; see Value below.

case_insensitive

ignore the case of dictionary values if TRUE

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.

verbose

if TRUE print message about how many pattern were removed

...

used only for passing arguments from dfm_remove or dfm_keep to dfm_select. Cannot include selection.

Value

A dfm or fcm object, after the feature selection has been applied.

For compatibility with earlier versions, when pattern is a dfm object and selection = "keep", then this will be equivalent to calling dfm_match. In this case, the following settings are always used: case_insensitive = FALSE, and valuetype = "fixed". This functionality is deprecated, however, and you should use dfm_match instead.

Details

dfm_remove and fcm_remove are simply a convenience wrappers to calling dfm_select and fcm_select with selection = "remove".

dfm_keep and fcm_keep are simply a convenience wrappers to calling dfm_select and fcm_select with selection = "keep".

See Also

dfm_match

Examples

# NOT RUN {
dfmat <- dfm(c("My Christmas was ruined by your opposition tax plan.",
               "Does the United_States or Sweden have more progressive taxation?"),
             tolower = FALSE)
dict <- dictionary(list(countries = c("United_States", "Sweden", "France"),
                          wordsEndingInY = c("by", "my"),
                          notintext = "blahblah"))
dfm_select(dfmat, pattern = dict)
dfm_select(dfmat, pattern = dict, case_insensitive = FALSE)
dfm_select(dfmat, pattern = c("s$", ".y"), selection = "keep", valuetype = "regex")
dfm_select(dfmat, pattern = c("s$", ".y"), selection = "remove", valuetype = "regex")
dfm_select(dfmat, pattern = stopwords("english"), selection = "keep", valuetype = "fixed")
dfm_select(dfmat, pattern = stopwords("english"), selection = "remove", valuetype = "fixed")

# select based on character length
dfm_select(dfmat, min_nchar = 5)

dfmat <- dfm(c("This is a document with lots of stopwords.",
               "No if, and, or but about it: lots of stopwords."))
dfmat
dfm_remove(dfmat, stopwords("english"))
toks <- tokens(c("this contains lots of stopwords",
                 "no if, and, or but about it: lots"),
               remove_punct = TRUE)
fcmat <- fcm(toks)
fcmat
fcm_remove(fcmat, stopwords("english"))
# }