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Pito Salas is a Curaçaoan-American Cambridge, Massachusetts-based software developer.While working with Lotus ' Advanced Technology Group in 1986, Salas invented the pivot table, a "next-generation" spreadsheet concept that was released by Lotus in 1989, as Lotus Improv.
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 ...
The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations. The "pandas" python package provides a "pivot" method which provides for a narrow to wide transformation.
LibreOffice Calc is the spreadsheet component of the LibreOffice software package. [5] [6]After forking from OpenOffice.org in 2010, LibreOffice Calc underwent a massive re-work of external reference handling to fix many defects in formula calculations involving external references, and to boost data caching performance, especially when referencing large data ranges.
Then is called a pivotal quantity (or simply a pivot). Pivotal quantities are commonly used for normalization to allow data from different data sets to be compared. It is relatively easy to construct pivots for location and scale parameters: for the former we form differences so that location cancels, for the latter ratios so that scale cancels.
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Prior to the release of Power Pivot, the engine for Microsoft's Business Intelligence suite was exclusively contained within SQL Server Analysis Services.In 2006, an initiative was launched by Amir Netz of the SQL Server Reporting Services team at Microsoft, codenamed Project Gemini, with the goal of making the analytical features of SSAS available within Excel.
Parametric tests assume that the data follow a particular distribution, typically a normal distribution, while non-parametric tests make no assumptions about the distribution. [7] Non-parametric tests have the advantage of being more resistant to misbehaviour of the data, such as outliers . [ 7 ]