subset.sento_measures {sentometrics}

Subset sentiment measures

Description

Subsets rows of the sentiment measures based on its columns.

Usage

## S3 method for class 'sento_measures'
subset(x, subset = NULL, select = NULL, delete = NULL, ...)

Arguments

x

a sento_measures object created using sento_measures.

subset

a logical (non-character) expression indicating the rows to keep. If a numeric input is given, it is used for row index subsetting.

select

a character vector of the lexicon, feature and time weighting scheme names, to indicate which measures need to be selected, or as a list of character vectors, possibly with separately specified combinations (consisting of one unique lexicon, one unique feature, and one unique time weighting scheme at maximum).

delete

see the select argument, but to delete measures.

...

not used.

Value

A modified sento_measures object, with only the remaining rows and sentiment measures, including updated information and statistics, but the original sentiment scores data.table untouched.

Author(s)

Samuel Borms

Examples

data("usnews", package = "sentometrics")
data("list_lexicons", package = "sentometrics")
data("list_valence_shifters", package = "sentometrics")

# construct a sento_measures object to start with
corpus <- sento_corpus(corpusdf = usnews)
corpusSample <- quanteda::corpus_sample(corpus, size = 500)
l <- sento_lexicons(list_lexicons[c("LM_en", "HENRY_en")])
ctr <- ctr_agg(howTime = c("equal_weight", "linear"), by = "year", lag = 3)
sm <- sento_measures(corpusSample, l, ctr)

# three specified indices in required list format
three <- as.list(
  stringi::stri_split(c("LM_en--economy--linear",
                        "HENRY_en--wsj--equal_weight",
                        "HENRY_en--wapo--equal_weight"),
                      regex = "--")
)

# different subsets
sub1 <- subset(sm, HENRY_en--economy--equal_weight >= 0.01)
sub2 <- subset(sm, date %in% get_dates(sm)[3:12])
sub3 <- subset(sm, 3:12)
sub4 <- subset(sm, 1:100) # warning

# different selections
sel1 <- subset(sm, select = "equal_weight")
sel2 <- subset(sm, select = c("equal_weight", "linear"))
sel3 <- subset(sm, select = c("linear", "LM_en"))
sel4 <- subset(sm, select = list(c("linear", "wsj"), c("linear", "economy")))
sel5 <- subset(sm, select = three)

# different deletions
del1 <- subset(sm, delete = "equal_weight")
del2 <- subset(sm, delete = c("linear", "LM_en"))
del3 <- subset(sm, delete = list(c("linear", "wsj"), c("linear", "economy")))
del4 <- subset(sm, delete = c("equal_weight", "linear")) # warning
del5 <- subset(sm, delete = three)