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  2. Help:Creating tables - Wikipedia

    en.wikipedia.org/wiki/Help:Creating_tables

    Data cells should normally have plain unbolded text, and a lighter background. In the table below the data cell wikitext is on the same line as the row header wikitext. This causes the data cell backgrounds to be the same shade of gray as the column and row headers. It also makes the data cell text bold. See how to fix this after the table.

  3. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    The listagg function, as defined in the SQL:2016 standard [2] aggregates data from multiple rows into a single concatenated string. In the entity relationship diagram , aggregation is represented as seen in Figure 1 with a rectangle around the relationship and its entities to indicate that it is being treated as an aggregate entity.

  4. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    If just 2 columns are being swapped within 1 table, then cut/paste editing (of those column entries) is typically faster than column-prefixing, sorting and de-prefixing. Another alternative is to copy the entire table from the displayed page, paste the text into a spreadsheet, move the columns as you will.

  5. Name–value pair - Wikipedia

    en.wikipedia.org/wiki/Name–value_pair

    A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.

  6. Entity–attribute–value model - Wikipedia

    en.wikipedia.org/wiki/Entity–attribute–value...

    In an EAV data model, each attribute–value pair is a fact describing an entity, and a row in an EAV table stores a single fact. EAV tables are often described as "long and skinny": "long" refers to the number of rows, "skinny" to the few columns. Data is recorded as three columns: The entity: the item being described.

  7. Regular expression - Wikipedia

    en.wikipedia.org/wiki/Regular_expression

    Regular expressions entered popular use from 1968 in two uses: pattern matching in a text editor [9] and lexical analysis in a compiler. [10] Among the first appearances of regular expressions in program form was when Ken Thompson built Kleene's notation into the editor QED as a means to match patterns in text files.

  8. String-searching algorithm - Wikipedia

    en.wikipedia.org/wiki/String-searching_algorithm

    A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.

  9. Matching wildcards - Wikipedia

    en.wikipedia.org/wiki/Matching_wildcards

    In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]