Mutable Data Structure: Difference between revisions
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** an [[Immutable Data Structure]]. | ** an [[Immutable Data Structure]]. | ||
* <B>See:</B> [[Data Structure Write Operation]]. | * <B>See:</B> [[Data Structure Write Operation]]. | ||
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Latest revision as of 17:25, 21 September 2021
A Mutable Data Structure is a data structure that supports an update data structure operation.s
- Example(s):
- a pandas.DataFrame.
- …
- Counter-Example(s):
- See: Data Structure Write Operation.
References
2013
- http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.html
- Two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure
1993
- http://caml.inria.fr/pub/docs/fpcl/fpcl-07.pdf
- The definition of a sum or product type may be annotated to allow physical (destructive) update on data structures of that type. This is the main feature of the imperative programming style. Writing values into memory locations is the fundamental mechanism of imperative languages such as Pascal. The Lisp language, while mostly functional, also provides the dangerous functions rplaca and rplacd to physically modify lists. Mutable structures are required to implement many efficient algorithms. They are also very convenient to represent the current state of a state machine.