| count {polmineR} | R Documentation |
Get counts.
Description
Count all tokens, or number of occurrences of a query (CQP syntax may be used), or matches for the query.
Usage
count(.Object, ...)
## S4 method for signature 'partition'
count(
.Object,
query = NULL,
cqp = is.cqp,
check = TRUE,
breakdown = FALSE,
decode = TRUE,
p_attribute = getOption("polmineR.p_attribute"),
mc = getOption("polmineR.cores"),
verbose = TRUE,
progress = FALSE,
phrases = NULL,
...
)
## S4 method for signature 'subcorpus'
count(
.Object,
query = NULL,
cqp = is.cqp,
check = TRUE,
breakdown = FALSE,
decode = TRUE,
p_attribute = getOption("polmineR.p_attribute"),
mc = getOption("polmineR.cores"),
verbose = TRUE,
progress = FALSE,
phrases = NULL,
...
)
## S4 method for signature 'partition_bundle'
count(
.Object,
query = NULL,
cqp = FALSE,
p_attribute = getOption("polmineR.p_attribute"),
phrases = NULL,
freq = FALSE,
total = TRUE,
mc = FALSE,
progress = FALSE,
verbose = FALSE,
...
)
## S4 method for signature 'subcorpus_bundle'
count(
.Object,
query = NULL,
cqp = FALSE,
p_attribute = NULL,
phrases = NULL,
freq = FALSE,
total = TRUE,
mc = FALSE,
progress = TRUE,
verbose = FALSE,
...
)
## S4 method for signature 'corpus'
count(
.Object,
query = NULL,
cqp = is.cqp,
check = TRUE,
p_attribute = getOption("polmineR.p_attribute"),
breakdown = FALSE,
sort = FALSE,
decode = TRUE,
verbose = TRUE,
...
)
## S4 method for signature 'character'
count(
.Object,
query = NULL,
cqp = is.cqp,
check = TRUE,
p_attribute = getOption("polmineR.p_attribute"),
breakdown = FALSE,
sort = FALSE,
decode = TRUE,
verbose = TRUE,
...
)
## S4 method for signature 'vector'
count(.Object, corpus, p_attribute, ...)
## S4 method for signature 'remote_corpus'
count(.Object, ...)
## S4 method for signature 'remote_subcorpus'
count(.Object, ...)
Arguments
.Object |
A |
... |
Further arguments. If |
query |
A character vector (one or multiple terms), CQP syntax can be used. |
cqp |
Either logical ( |
check |
A |
breakdown |
Logical, whether to report number of occurrences for different matches for a query. |
decode |
Logical, whether to turn token ids into decoded strings (only if query is NULL). |
p_attribute |
The p-attribute(s) to use. |
mc |
Logical, whether to use multicore (defaults to |
verbose |
Logical, whether to be verbose. |
progress |
Logical, whether to show progress bar. |
phrases |
A |
freq |
Logical, if |
total |
Defaults to |
sort |
Logical, whether to sort table with counts (in stat slot). |
corpus |
The name of a CWB corpus. |
Details
If .Object is a partiton_bundle, the data.table returned will
have the queries in the columns, and as many rows as there are in the
partition_bundle.
If .Object is a length-one character vector and query is
NULL, the count is performed for the whole partition.
If breakdown is TRUE and one query is supplied, the function
returns a frequency breakdown of the results of the query. If several queries
are supplied, frequencies for the individual queries are retrieved.
Multiple queries can be used for argument query. Some care may be
necessary when summing up the counts for the individual queries. When the
CQP syntax is used, different queries may yield the same match result, so that
the sum of all individual query matches may overestimate the true number of
unique matches. In the case of overlapping matches, a warning message is
issued. Collapsing multiple CQP queries into a single query (separating the
individual queries by "|" and wrapping everything in round brackets) solves
this problem.
Value
A data.table if argument query is used, a count-object,
if query is NULL and .Object is a character vector (referring
to a corpus) or a partition, a count_bundle-object, if .Object
is a partition_bundle.
References
Baker, Paul (2006): Using Corpora in Discourse Analysis. London: continuum, p. 47-69 (ch. 3).
See Also
For a metadata-based breakdown of counts (i.e. tabulation by
s-attributes), see dispersion. The hits is the
worker behind the dispersion method and offers a similar, yet more
low-level functionality as compared to the count method. Using the
hits method may be useful to obtain the data required for
flexible cross-tabulations.
Examples
use("polmineR")
use(pkg = "RcppCWB", corpus = "REUTERS")
debates <- partition("GERMAPARLMINI", date = ".*", regex=TRUE)
count(debates, query = "Arbeit") # get frequencies for one token
count(debates, c("Arbeit", "Freizeit", "Zukunft")) # get frequencies for multiple tokens
count("GERMAPARLMINI", query = c("Migration", "Integration"), p_attribute = "word")
debates <- partition_bundle(
"GERMAPARLMINI", s_attribute = "date", values = NULL,
mc = FALSE, verbose = FALSE
)
y <- count(debates, query = "Arbeit", p_attribute = "word")
y <- count(debates, query = c("Arbeit", "Migration", "Zukunft"), p_attribute = "word")
count("GERMAPARLMINI", '"Integration.*"', breakdown = TRUE)
P <- partition("GERMAPARLMINI", date = "2009-11-11")
count(P, '"Integration.*"', breakdown = TRUE)
sc <- corpus("GERMAPARLMINI") %>% subset(party == "SPD")
phr <- cpos(sc, query = '"Deutsche.*" "Bundestag.*"', cqp = TRUE) %>%
as.phrases(corpus = "GERMAPARLMINI", enc = "latin1")
cnt <- count(sc, phrases = phr, p_attribute = "word")
# Multiple queries and overlapping query matches. The first count
# operation will issue a warning that matches overlap, see the second
# example for a solution.
corpus("REUTERS") %>%
count(query = c('".*oil"', '"turmoil"'), cqp = TRUE)
corpus("REUTERS") %>%
count(query = '"(.*oil|turmoil)"', cqp =TRUE)