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  2. pandas (software) - Wikipedia

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

    Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values. For example, if s is a Series, s['a'] will return the data point at index a. Unlike dictionary keys, index values are not guaranteed to be unique.

  3. Count-distinct problem - Wikipedia

    en.wikipedia.org/wiki/Count-distinct_problem

    Min/max sketches [2] [3] store only the minimum/maximum hashed values. Examples of known min/max sketch estimators: Chassaing et al. [4] presents max sketch which is the minimum-variance unbiased estimator for the problem. The continuous max sketches estimator [5] is the maximum likelihood estimator.

  4. Array (data type) - Wikipedia

    en.wikipedia.org/wiki/Array_(data_type)

    For example, in the Pascal programming language, the declaration type MyTable = array [1..4,1..2] of integer, defines a new array data type called MyTable. The declaration var A: MyTable then defines a variable A of that type, which is an aggregate of eight elements, each being an integer variable identified by two indices.

  5. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    The data-frame is then used to manipulate data that can be challenging otherwise to do in Excel. Pandas (software) which is a powerful tool that allows for data analysis and manipulation; which makes data visualizations, statistical operations and much more, a lot easier. Many also use the R programming language to do such tasks as well.

  6. Iris flower data set - Wikipedia

    en.wikipedia.org/wiki/Iris_flower_data_set

    The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]

  7. Data transformation (computing) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.

  8. Generator (computer programming) - Wikipedia

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

    In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.

  9. Stochastic dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Stochastic_dynamic_programming

    This is the optimal policy that has been previously illustrated. Note that there are multiple optimal policies leading to the same optimal value () =; for instance, in the first game one may either bet $1 or $2. Python implementation. The one that follows is a complete Python implementation of this example.