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Such functions are called decomposable aggregation functions [4] or decomposable aggregate functions. The simplest may be referred to as self-decomposable aggregation functions , which are defined as those functions f such that there is a merge operator ⋄ {\displaystyle \diamond } such that
In functional programming, fold (also termed reduce, accumulate, aggregate, compress, or inject) refers to a family of higher-order functions that analyze a recursive data structure and through use of a given combining operation, recombine the results of recursively processing its constituent parts, building up a return value.
Programming languages and libraries suited to work with tabular data contain functions that allow the creation and manipulation of pivot tables. Python data analysis toolkit pandas has the function pivot_table [16] and the xs method useful to obtain sections of pivot tables. [citation needed]
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .
Aggregate function, aggregation function, in database management is a function wherein the values of multiple rows are grouped together to form a single summary value; Aggregate Level Simulation Protocol (ALSP), a protocol and supporting software that enables simulations to interoperate with one another
Aggregate function, a type of function in data processing; Aggregation, a form of object composition in object-oriented programming; Link aggregation, using multiple Ethernet network cables/ports in parallel to increase link speed; Packet aggregation, joining multiple data packets for transmission as a single unit to increase network efficiency
Interactive maps, databases and real-time graphics from The Huffington Post
An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.