tif_is_tokens_df: Validate Tokens Data Frame Object

In ropensci/tif: Text Interchange Format

Validate Tokens Data Frame Object

Description

A valid tokens data frame object is a data frame or an object that inherits a data frame. It has no row names and has at least two columns. It must a contain column called doc_id that is a character vector with UTF-8 encoding. Document ids must be unique. It must also contain a column called token that must also be a character vector in UTF-8 encoding. Each individual token is represented by a single row in the data frame. Addition token-level metadata columns are allowed but not required.

Usage

tif_is_tokens_df(tokens, warn = FALSE)

Arguments

tokens	a tokens object to test for validity
warn	logical. Should the function produce a verbose warning for the condition for which the validation fails. Useful for testing.

Details

The tests are run sequentially and the function returns, with a warning if the warn flag is set, on the first test that fails. We use this implementation because some tests may fail entirely or be meaningless if the prior ones are note passed. For example, if the tokens object does not have a variable named "doc_id" it does not make sense to check whether this column is a character vector.

Value

a logical vector of length one indicating whether the input is a valid tokens object

Examples

tokens <- data.frame(doc_id = c("doc1", "doc1", "doc1", "doc1",
                                "doc2",  "doc2", "doc2", "doc2",
                                "doc2", "doc2", "doc3", "doc3",
                                "doc3", "doc3", "doc3", "doc3"),
                     token = c("aujourd'hui", "maman", "est",
                               "morte", "it", "was", "a", "pleasure",
                               "to", "burn", "all", "this", "happened",
                               "more", "or", "less"),
                     stringsAsFactors = FALSE)

tif_is_tokens_df(tokens)

tokens$pos <- "NOUN"
tokens$NER <- ""
tokens$sentiment <- runif(16L)
tif_is_tokens_df(tokens)

ropensci/tif documentation built on Nov. 30, 2023, 7:46 p.m.