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Data structure diagram and a data dictionary. A data structure diagram is a diagram type that is used to depict the structure of data elements in the data dictionary. The data structure diagram is a graphical alternative to the composition specifications within such data dictionary entries. [1] The data structure diagrams is a predecessor of ...
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
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.
Array, a sequence of elements of the same type stored contiguously in memory; Record (also called a structure or struct), a collection of fields . Product type (also called a tuple), a record in which the fields are not named
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
It is common to hold shared data in external data structures and pass it to the objects temporarily when they are used. A classic example are the data structures used representing characters in a word processor. Naively, each character in a document might have a glyph object containing its font outline, font metrics, and other formatting data ...
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.
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