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  2. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    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 table to wide table is generally referred to as "pivoting" in the context of data transformations.

  3. Zero-based numbering - Wikipedia

    en.wikipedia.org/wiki/Zero-based_numbering

    The indexing expression for a 1-based index would then be ′ +. Hence, the efficiency benefit at run time of zero-based indexing is not inherent, but is an artifact of the decision to represent an array with the address of its first element rather than the address of the fictitious zeroth element.

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.

  5. Help:Table - Wikipedia

    en.wikipedia.org/wiki/Help:Table

    tabulate, Python module for converting data structures to wiki table markup; wikitables, Python module for reading wiki table markup; H63: Using the scope attribute to associate header cells and data cells in data tables | Techniques for WCAG 2.0. Tables | Usability & Web Accessibility. Yale University. Tables with Multi-Level Headers.

  6. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Even though the row is indicated by the first index and the column by the second index, no grouping order between the dimensions is implied by this. The choice of how to group and order the indices, either by row-major or column-major methods, is thus a matter of convention. The same terminology can be applied to even higher dimensional arrays.

  7. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").

  8. Counting sort - Wikipedia

    en.wikipedia.org/wiki/Counting_sort

    For data in which the maximum key size is significantly smaller than the number of data items, counting sort may be parallelized by splitting the input into subarrays of approximately equal size, processing each subarray in parallel to generate a separate count array for each subarray, and then merging the count arrays.

  9. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    Davies–Bouldin index: The Davies-Bouldin index is a measure of the how much separation there is between clusters. [32] Lower values of the Davies-Bouldin index indicate a model with better separation. Calinski-Harabasz index: This Index evaluates clusters based on their compactness and separation. The index is calculated using the ratio of ...