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Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Python's built-in dict class can be subclassed to implement autovivificious dictionaries simply by overriding the __missing__() method that was added to the class in Python v2.5. [5]
Any existing mapping is overwritten. The arguments to this operation are the key and the value. Remove or delete remove a (,) pair from the collection, unmapping a given key from its value. The argument to this operation is the key. Lookup, find, or get find the value (if any) that is bound to a given key.
A small phone book as a hash table. In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. [2]
Python dictionaries (a form of associative array) can also be directly iterated over, when the dictionary keys are returned; or the items() method of a dictionary can be iterated over where it yields corresponding key,value pairs as a tuple:
for key, value in some_dict. items (): # Direct iteration on a dict iterates on its keys # Do stuff As for ... in is the only kind of for loop in Python, the equivalent to the "counter" loop found in other languages is...
Python makes a distinction between lists and tuples. Lists are written as [1, 2, 3], are mutable, and cannot be used as the keys of dictionaries (dictionary keys must be immutable in Python). Tuples, written as (1, 2, 3), are immutable and thus can be used as keys of dictionaries, provided all of the tuple's elements are immutable.
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.