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  2. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    In order to calculate the average and standard deviation from aggregate data, it is necessary to have available for each group: the total of values (Σx i = SUM(x)), the number of values (N=COUNT(x)) and the total of squares of the values (Σx i 2 =SUM(x 2)) of each groups.

  3. Generator (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Generator_(computer...

    In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop. All generators are also iterators. [1] A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values.

  4. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a user to act as though the index is an array-like sequence of integers, regardless of how it is actually defined. [9]: 110–113 Pandas supports hierarchical indices with multiple values per data point.

  5. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  6. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.

  7. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    The extra cost of eliminating "modulo bias" when generating random integers for a Fisher-Yates shuffle depends on the approach (classic modulo, floating-point multiplication or Lemire's integer multiplication), the size of the array to be shuffled, and the random number generator used. [20]: Benchmarking ...

  8. Aggregate (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Aggregate_(data_warehouse)

    Since dimensional models only gain from aggregates on large data sets, it should be considered at what size of the data sets one should start using aggregates One can also ask oneself if a data warehouse always handles data sets that are too large for direct queries, or if it sometimes is a good idea to omit the aggregate tables when starting a ...

  9. Alternating step generator - Wikipedia

    en.wikipedia.org/wiki/Alternating_step_generator

    In cryptography, an alternating step generator (ASG) is a cryptographic pseudorandom number generator used in stream ciphers, based on three linear-feedback shift registers. Its output is a combination of two LFSRs which are stepped (clocked) in an alternating fashion, depending on the output of a third LFSR.