qdap (version 2.2.1)

trans_context: Print Context Around Indices

Description

Print (or save to an external file) n text elements before and after indices.

Usage

trans_context(text.var, grouping.var, inds, n.before = 3, tot = TRUE,
  n.after = n.before, ord.inds = TRUE)

Arguments

text.var

The text variable.

grouping.var

The grouping variables. Also takes a single grouping variable or a list of 1 or more grouping variables.

inds

A list of integer indices to print context for.

n.before

The number of rows before the indexed occurrence.

tot

logical. If TRUE condenses sub-units (e.g., sentences) into turns of talk for that grouping.var.

n.after

The number of rows after the indexed occurrence.

ord.inds

logical. If TRUE inds is ordered least to greatest.

Value

• Returns a dataframe of the class "qdap_context" that can be printed (i.e., saved) in flexible outputs. The dataframe can be printed as a dataframe style or pretty text output. The resulting file contains n rows before and after each index of a vector of indices.

See Also

boolean_search, question_type, end_mark

Examples

(x <- with(DATA, trans_context(state, person, inds=c(1, 4, 7, 11))))
print(x, pretty=FALSE)
print(x, double_space = FALSE)
print(x, file="foo.xlsx")
print(x, file="foo.csv")
print(x, file="foo.txt")
print(x, file="foo.txt", pretty = FALSE)
print(x, file="foo.doc")

## With `end_mark`
inds1 <- which(end_mark(DATA.SPLIT[, "state"]) == "?")
with(DATA.SPLIT, trans_context(state, person, inds=inds1))
with(DATA.SPLIT, trans_context(state, person, n.before = 0, inds=inds1))

## With `boolean_search`
inds2 <- boolean_search(DATA.SPLIT$state, " I &&.")
with(DATA.SPLIT, trans_context(state, person, inds=inds2))

inds3 <- boolean_search(DATA$state, " I ||.")
with(DATA.SPLIT, trans_context(state, person, inds=inds3))
with(DATA.SPLIT, trans_context(state, list(person, sex), inds=inds3))
with(DATA.SPLIT, trans_context(state, list(sex, adult), inds=inds3))

inds4 <- boolean_search(raj$dialogue, spaste(paste(negation.words, collapse = " || ")))
trans_context(raj$dialogue, raj$person, inds4)

### With `question_type`
(x <- question_type(DATA.SPLIT$state, DATA.SPLIT$person))

## All questions
with(DATA.SPLIT, trans_context(state, person, inds=x$inds))

## Specific question types
y <- x[["raw"]]
inds5 <- y[y[, "q.type"] %in% qcv(what, how), "n.row"]
with(DATA.SPLIT, trans_context(state, person, inds=inds5))
with(DATA.SPLIT, trans_context(state, person, inds=inds5, tot=F))