2.80:Table Extraction (Concept) - Revision history

Dgreenwood at 15:13, 5 August 2025

2025-08-05T15:13:04Z

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Randallkinard at 20:15, 23 April 2024

2024-04-23T20:15:23Z

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	[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]		[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]
	<blockquote ~~style="font-size~~:~~14pt">~~
	Table Extraction ~~refers to Grooper's functionality to extract data from cells in tables. This is accomplished by configuring the '''[[Data Table]]''' '''''[[Data Element]]''''' in a '''[[Data Model]]'''.~~		<blockquote>{{#lst:Glossary\|Table Extraction}}</blockquote>
	</blockquote>

	Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.		Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.

	In Grooper, tabular data can be extracted to '''Data Table''' objects using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.		In Grooper, tabular data can be extracted to '''Data Table''' objects using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.
			<br clear=all>
	== What Is a Table? ==		== What Is a Table? ==

	Tables consists of rows and columns. Where those rows and columns intersect are cells. These are the individual units of the table containing individual pieces of data. Each row consists of the same number of columns (although some columns may be empty in a given row). A single column consists of the same type of information. For example, an "Order Date" column will always have dates in the cells below it. The rows themselves are usually (but not always) in some order as well, such as in order of ascending date.		Tables consists of rows and columns. Where those rows and columns intersect are cells. These are the individual units of the table containing individual pieces of data. Each row consists of the same number of columns (although some columns may be empty in a given row). A single column consists of the same type of information. For example, an "Order Date" column will always have dates in the cells below it. The rows themselves are usually (but not always) in some order as well, such as in order of ascending date.

Randallkinard: Randallkinard moved page 2.80:Table Extraction to 2.80:Table Extraction (Concept) without leaving a redirect: new naming convention

2024-04-18T16:39:48Z

Randallkinard moved page 2.80:Table Extraction to 2.80:Table Extraction (Concept) without leaving a redirect: new naming convention

← Older revision	Revision as of 11:39, 18 April 2024
(No difference)

Dgreenwood: Dgreenwood moved page Table Extraction - 2.80 to 2.80:Table Extraction without leaving a redirect

2024-01-03T16:25:31Z

Dgreenwood moved page Table Extraction - 2.80 to 2.80:Table Extraction without leaving a redirect

← Older revision	Revision as of 11:25, 3 January 2024
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Dgreenwood at 16:25, 3 January 2024

2024-01-03T16:25:21Z

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	[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]		[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]
	~~<onlyinclude>~~
	<blockquote style="font-size:14pt">		<blockquote style="font-size:14pt">
	Table Extraction refers to Grooper's functionality to extract data from cells in tables. This is accomplished by configuring the '''[[Data Table]]''' '''''[[Data Element]]''''' in a '''[[Data Model]]'''.		Table Extraction refers to Grooper's functionality to extract data from cells in tables. This is accomplished by configuring the '''[[Data Table]]''' '''''[[Data Element]]''''' in a '''[[Data Model]]'''.
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	In Grooper, tabular data can be extracted to '''Data Table''' objects using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.		In Grooper, tabular data can be extracted to '''Data Table''' objects using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.
	~~</onlyinclude>~~

	== What Is a Table? ==		== What Is a Table? ==
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	''Infer Grid'' excels at table extraction where table lines are present. It also excels at some specialized use cases. Sometimes, text falling in a table's cells use a specialized font not easily read by the main '''OCR profile''' used to grab a document's text data. In these cases, a secondary '''OCR profile''' can be run on the cells in a column to reprocess the raw text data, targeting that specialized font. ''Infer Grid'' also has functionality to easily read checkboxes in a table through OMR detection.		''Infer Grid'' excels at table extraction where table lines are present. It also excels at some specialized use cases. Sometimes, text falling in a table's cells use a specialized font not easily read by the main '''OCR profile''' used to grab a document's text data. In these cases, a secondary '''OCR profile''' can be run on the cells in a column to reprocess the raw text data, targeting that specialized font. ''Infer Grid'' also has functionality to easily read checkboxes in a table through OMR detection.

	~~[[Category:Articles]]~~
	~~[[Category:Version 2.80]]~~

Dgreenwood: Dgreenwood moved page Table Extraction to Table Extraction - 2.80: To be consistent with current naming conventions

2022-12-12T19:14:27Z

Dgreenwood moved page Table Extraction to Table Extraction - 2.80: To be consistent with current naming conventions

← Older revision	Revision as of 14:14, 12 December 2022
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Dgreenwood at 19:14, 12 December 2022

2022-12-12T19:14:16Z

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	[[Category:Articles]]		[[Category:Articles]]
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Dgreenwood at 19:14, 12 December 2022

2022-12-12T19:14:08Z

← Older revision		Revision as of 14:14, 12 December 2022
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	''Infer Grid'' excels at table extraction where table lines are present. It also excels at some specialized use cases. Sometimes, text falling in a table's cells use a specialized font not easily read by the main '''OCR profile''' used to grab a document's text data. In these cases, a secondary '''OCR profile''' can be run on the cells in a column to reprocess the raw text data, targeting that specialized font. ''Infer Grid'' also has functionality to easily read checkboxes in a table through OMR detection.		''Infer Grid'' excels at table extraction where table lines are present. It also excels at some specialized use cases. Sometimes, text falling in a table's cells use a specialized font not easily read by the main '''OCR profile''' used to grab a document's text data. In these cases, a secondary '''OCR profile''' can be run on the cells in a column to reprocess the raw text data, targeting that specialized font. ''Infer Grid'' also has functionality to easily read checkboxes in a table through OMR detection.

			[[Category:Articles]]
			[[Category:2.80]]

Dgreenwood at 15:06, 25 November 2020

2020-11-25T15:06:43Z

← Older revision		Revision as of 10:06, 25 November 2020
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	Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.		Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.

	In Grooper, tabular data can be extracted using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.		In Grooper, tabular data can be extracted to '''Data Table''' objects using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.
	</onlyinclude>		</onlyinclude>

Dgreenwood at 15:05, 25 November 2020

2020-11-25T15:05:48Z

← Older revision		Revision as of 10:05, 25 November 2020
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	[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]		[[File:Table-extraction-simple-table.png\|thumb\|300px\|Data in an Excel spreadsheet is an example of tabular data.]]
			<onlyinclude>
			<blockquote style="font-size:14pt">
			Table Extraction refers to Grooper's functionality to extract data from cells in tables. This is accomplished by configuring the '''[[Data Table]]''' '''''[[Data Element]]''''' in a '''[[Data Model]]'''.
			</blockquote>

	Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.		Tables are one of the most common ways data is organized on documents. Human beings have been writing information into tables before they started writing literature, even before paper was invented. There are examples of tables carved onto the walls of Egyptian temples! They are excellent structures for representing a lot of information with various characteristics in common in a relatively small space (or an Egyptian temple sized space). However, targeting the data inside them presents its own set of challenges. A table’s structure can range from simple and straightforward to more complex (even confounding). Different organizations may organize the same data differently, creating different tables for what, essentially, is the same data.

	In Grooper, tabular data can be extracted using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.		In Grooper, tabular data can be extracted using the ''[[Row Match (Table Extract Method)\|Row Match]]'', ''[[Header-Value (Table Extract Method)\|Header-Value]]'', or ''[[Infer Grid (Table Extract Method)\|Infer Grid]]'' table extraction methods.
			</onlyinclude>

	== What Is a Table? ==		== What Is a Table? ==