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The default behaviour of sorting without a data-sort-value or a sorting template is to use the whole text of the cell for sorting. This means that if before and after are not used and there is no text after the template then there is no reason to use the template.
The ! indicates cells that are header cells. In order for a table to be sortable, the first row(s) of a table need to be entirely made up out of these header cells. You can learn more about the basic table syntax by taking the Introduction to tables for source editing.
This category contains templates used in table rows of sortable tables, often to provide a hidden sort key (marked with the data-sort-value attribute), and/or to force a particular sort mode. The pages listed in this category are templates .
The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.
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The sort criteria can be expressions, including column names, user-defined functions, arithmetic operations, or CASE expressions. The expressions are evaluated and the results are used for the sorting, i.e., the values stored in the column or the results of the function call. ORDER BY is the only way to sort the
More generally, there are d! possible orders for a given array, one for each permutation of dimensions (with row-major and column-order just 2 special cases), although the lists of stride values are not necessarily permutations of each other, e.g., in the 2-by-3 example above, the strides are (3,1) for row-major and (1,2) for column-major.
A pivot table is a table of values which are aggregations of groups of individual values from a more extensive table (such as from a database, spreadsheet, or business intelligence program) within one or more discrete categories. The aggregations or summaries of the groups of the individual terms might include sums, averages, counts, or other ...