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  2. pandas (software) - Wikipedia

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

    Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.

  3. List of data structures - Wikipedia

    en.wikipedia.org/wiki/List_of_data_structures

    This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.

  4. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    The language incorporates built-in data types and structures, control flow mechanisms, first-class functions, and modules for better code reusability and organization. Python also uses English keywords where other languages use punctuation, contributing to its uncluttered visual layout.

  5. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    In contrast to Python's built-in list data structure, these arrays are homogeneously typed: all elements of a single array must be of the same type. Such arrays can also be views into memory buffers allocated by C / C++ , Python , and Fortran extensions to the CPython interpreter without the need to copy data around, giving a degree of ...

  6. Data structure - Wikipedia

    en.wikipedia.org/wiki/Data_structure

    A data structure known as a hash table.. In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. [1] [2] [3] More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, [4] i.e., it is an algebraic structure about data.

  7. Construct (Python library) - Wikipedia

    en.wikipedia.org/wiki/Construct_(Python_library)

    Construct is a Python library for the construction and deconstruction of data structures in a declarative fashion. In this context, construction, or building, refers to the process of converting (serializing) a programmatic object into a binary representation.

  8. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    Trie data structures are commonly used in predictive text or autocomplete dictionaries, and approximate matching algorithms. [11] Tries enable faster searches, occupy less space, especially when the set contains large number of short strings, thus used in spell checking , hyphenation applications and longest prefix match algorithms.

  9. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data_structures

    Here are time complexities [5] of various heap data structures. The abbreviation am. indicates that the given complexity is amortized, otherwise it is a worst-case complexity. For the meaning of "O(f)" and "Θ(f)" see Big O notation. Names of operations assume a max-heap.