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  2. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. 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 ...

  3. pandas (software) - Wikipedia

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

    By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.

  4. Database index - Wikipedia

    en.wikipedia.org/wiki/Database_index

    Covering indexes are each for a specific table. Queries which JOIN/ access across multiple tables, may potentially consider covering indexes on more than one of these tables. [7] A covering index can dramatically speed up data retrieval but may itself be large due to the additional keys, which slow down data insertion and update.

  5. Join and meet - Wikipedia

    en.wikipedia.org/wiki/Join_and_meet

    Join and meet are dual to one another with respect to order inversion. A partially ordered set in which all pairs have a join is a join-semilattice. Dually, a partially ordered set in which all pairs have a meet is a meet-semilattice. A partially ordered set that is both a join-semilattice and a meet-semilattice is a lattice.

  6. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation .

  7. Data-driven programming - Wikipedia

    en.wikipedia.org/wiki/Data-driven_programming

    If an intersection (in the United States) is represented in data by the zip code (5-digit number) and two street names (strings of text), bugs may appear when a city where streets intersect multiple times is encountered. While this example may be oversimplified, restructuring of data is a fairly common problem in software engineering, either to ...

  8. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Tukey promoted the use of five number summary of numerical data—the two extremes (maximum and minimum), the median, and the quartiles—because these median and quartiles, being functions of the empirical distribution are defined for all distributions, unlike the mean and standard deviation; moreover, the quartiles and median are more robust ...

  9. Conditional entropy - Wikipedia

    en.wikipedia.org/wiki/Conditional_entropy

    Assume that the combined system determined by two random variables and has joint entropy (,), that is, we need (,) bits of information on average to describe its exact state. Now if we first learn the value of X {\displaystyle X} , we have gained H ( X ) {\displaystyle \mathrm {H} (X)} bits of information.