- Python - Algorithm Justifications
- Python - Amortized Analysis
- Python - Algorithm Classes
- Python - Big-O Notation
- Python - Algorithm Analysis
- Python - Graph Algorithms
- Python - Searching Algorithms
- Python - Sorting Algorithms
- Python - Backtracking
- Python - Recursion
- Python - Divide and Conquer
- Python - Algorithm Design
- Python - Graphs
- Python - Heaps
- Python - Search Tree
- Python - Binary Tree
- Python - Hash Table
- Python - Advanced Linked list
- Python - Dequeue
- Python - Queue
- Python - Stack
- Python - Linked Lists
- Python - Maps
- Python - Sets
- Python - Matrix
- Python - 2-D Array
- Python - Dictionary
- Python - Tuples
- Python - Lists
- Python - Arrays
- Python - DS Environment
- Python - DS Introduction
- Python - DS Home
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Python - Hash Table
Hash tables are a type of data structure in which the address or the index value of the data element is generated from a hash function. That makes accessing the data faster as the index value behaves as a key for the data value. In other words Hash table stores key-value pairs but the key is generated through a hashing function.
So the search and insertion function of a data element becomes much faster as the key values themselves become the index of the array which stores the data.
In Python, the Dictionary data types represent the implementation of hash tables. The Keys in the dictionary satisfy the following requirements.
The keys of the dictionary are hashable i.e. the are generated by hashing function which generates unique result for each unique value suppped to the hash function.
The order of data elements in a dictionary is not fixed.
So we see the implementation of hash table by using the dictionary data types as below.
Accessing Values in Dictionary
To access dictionary elements, you can use the famipar square brackets along with the key to obtain its value.
Example
# Declare a dictionary dict = { Name : Zara , Age : 7, Class : First } # Accessing the dictionary with its key print ("dict[ Name ]: ", dict[ Name ]) print ("dict[ Age ]: ", dict[ Age ])
Output
When the above code is executed, it produces the following result −
dict[ Name ]: Zara dict[ Age ]: 7
Updating Dictionary
You can update a dictionary by adding a new entry or a key-value pair, modifying an existing entry, or deleting an existing entry as shown below in the simple example −
Example
# Declare a dictionary dict = { Name : Zara , Age : 7, Class : First } dict[ Age ] = 8; # update existing entry dict[ School ] = "DPS School"; # Add new entry print ("dict[ Age ]: ", dict[ Age ]) print ("dict[ School ]: ", dict[ School ])
Output
When the above code is executed, it produces the following result −
dict[ Age ]: 8 dict[ School ]: DPS School
Delete Dictionary Elements
You can either remove inspanidual dictionary elements or clear the entire contents of a dictionary. You can also delete entire dictionary in a single operation.To exppcitly remove an entire dictionary, just use the del statement.
Example
dict = { Name : Zara , Age : 7, Class : First } del dict[ Name ]; # remove entry with key Name dict.clear(); # remove all entries in dict del dict ; # delete entire dictionary print ("dict[ Age ]: ", dict[ Age ]) print ("dict[ School ]: ", dict[ School ])
Output
This produces the following result. Note that an exception is raised because after del dict dictionary does not exist anymore.
dict[ Age ]: dict[ Age ] dict[ School ]: dict[ School ]Advertisements