Package 'orderanalyzer'

Extracting order position tables from PDF-based order documents

Description

This packages provides functions for extracting text and order-position-tables from PDF-based order documents.

Details

Package:	orderanalyzer
Type:	Package
Version:	1.0.0
Date:	2024-12-11
License:	GPL-3
Depends:	R (>= 4.3.0)

Author(s)

Michael Scholz [email protected]

Joerg Bauer [email protected]

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Extract tables from a given words-dataframe

Description

This function extracts order-position-tables from PDF-based order documents. It tries to identify table rows based on a clustering approach and thereafter identifies the column structure. A table row can consist of multiple text rows and the text rows can span different columns. This function furthermore tries to identify the meaning of the columns (position, articleID, description, quantity, quanity unit, unit price, total price, currency, date).

Usage

extractTables(text, minCols = 3, maxDistance = 20, entityNames = NA)

Arguments

text	List including several representations of text extracted from a PDF file. This list is generated by the function extractText.
minCols	Number of columns a table must minimal consist of
maxDistance	Number of text lines that can maximally exist between the start of two table rows
entityNames	A list of four name vectors (currencyUnits, quantityUnits, headerNames, noTableNames). Each vector contains strings that correspond to currency units, quantity units, header names or names of entities not being a table.

Value

List of lists describing the tables. Each sublist includes a data frame (data) which is the identified table, the position of text lines that constitute the table and the position of the significant lines.

Examples

file <- system.file("extdata", "OrderDocument_en.pdf", package = "orderanalyzer")
text <- extractText(file)

# Extracting order tables without any further information
tables <- extractTables(text)
tables[[1]]$data

# Extracting order tables with further information
tables <- extractTables(text,
  entityNames = list(currencyUnits = enc2utf8(c("eur", "euro", "\u20AC")),
                     quantityUnits = enc2utf8(c("pcs", "pcs.")),
                     headerNames = enc2utf8(c("pos", "item", "quantity")),
                     noTableNames = enc2utf8(c("order total", "supplier number")))
)
tables[[1]]$data

# Extracting order tables from a German document
file <- system.file("extdata", "OrderDocument_de.pdf", package = "orderanalyzer")
text <- extractText(file)
tables <- extractTables(text)
tables[[1]]$data

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Extracts the text from a PDF file

Description

This function extracts text from PDF documents and returns the text as a string, as a list of lines and as a list of words. It uses 'pdftools' to extract the content from textual PDF files and 'tesseract' to extract the content from image-based PDF-files.

Usage

extractText(file)

Arguments

file	Path to the PDF file

Value

List including the extracted text, a data table including the lines, a data table including the words, the type and language of the document.

Examples

file <- system.file("extdata", "OrderDocument_en.pdf", package = "orderanalyzer")
text <- extractText(file)
text$words

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Identifies the language of a given text based on frequent trigrams

Description

This function identifies the language of a given string based on the most frequent trigrams in different languages. Supported languages are Czech, Dutch, English, French, German, Spanish, Latvian and Lithuanian.

Usage

identifyLanguage(text)

Arguments

text	String for which the language should be identified

Value

Name of the detected language.

Examples

text <- "The tea in the cup still is hot."
language <- identifyLanguage(text)
language

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