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Data can be lost when converting representations from floating-point to integer, as the fractional components of the floating-point values will be truncated (rounded toward zero). Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all ...
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
A record is a value that contains other values, typically in fixed number and sequence and typically indexed by names. The elements of records are usually called fields or members. An object contains a number of data fields, like a record, and also offers a number of subroutines for accessing or modifying them, called methods.
Data conversion is the conversion of computer data from one format to another. Throughout a computer environment, data is encoded in a variety of ways. For example, computer hardware is built on the basis of certain standards, which requires that data contains, for example, parity bit checks.
In computing, data transformation is the process of converting data from one format or structure into another format or structure. It is a fundamental aspect of most data integration [1] and data management tasks such as data wrangling, data warehousing, data integration and application integration.
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 ...
converting a pointer of a base class to a pointer of a non-virtual derived class (downcasting); converting numeric data types such as enums to ints or floats . Although static_cast conversions are checked at compile time to prevent obvious incompatibilities, no run-time type checking is performed that would prevent a cast between incompatible ...
Data can be grouped into objects or "entities" according to preference with little to no consequence. While data-driven design does prevent coupling of data and functionality, in some cases, data-driven programming has been argued to lead to bad object-oriented design , especially when dealing with more abstract data.