This is a 'data.table' implementation that mimics the output of
pairwise_count() from 'widyr' to reduce package dependency. This is used
internally within tm_cooc().
Arguments
- data
Data frame output from
tm_clean().- id
String to represent the id variable. Defaults to
"line".- word
String to represent the word variable. Defaults to
"word".
See also
Other Support:
any_idate(),
camel_clean(),
check_inputs(),
cut_hour(),
extract_date_range(),
extract_hr(),
heat_colours(),
is_date_format(),
maxmin(),
read_preamble(),
rgb2hex(),
totals_bind(),
totals_col(),
tstamp(),
us_to_space(),
wrap()
Other Text-mining:
meeting_tm_report(),
tm_clean(),
tm_cooc(),
tm_freq(),
tm_wordcloud()
Examples
td <- data.frame(line = c(1, 1, 2, 2),
word = c("work", "meeting", "catch", "up"))
pairwise_count(td, id = "line", word = "word")
#> # A tibble: 2 × 3
#> item1 item2 n
#> <chr> <chr> <int>
#> 1 work meeting 1
#> 2 catch up 1
