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    Hash Tables and Hash Maps in Python

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    Hash Tables and Hash Maps in Python

    Introduction

    There are numerous ways for storing and accessing data and one of the most popular methods is Hash Tables. Python has an in-built data type like a dictionary to implement hash tables. Here we are explaining how to implement hash tables and hashmaps in Python using dictionaries.

    Hash tables and Hashmaps in Python

    Hash tables and hashmaps are data structures used to map keys to their value pairs. It is used in functions for computing an index value that contains the elements to be inserted, removed, or searched. Hash tables are used to access data easily and faster. They store key-value pairs and the key will be generated using a hash function.

    The built-in dictionary data type is used to implement a hash table or hashmap and the keys are created using a hash function. Dictionary data type contains the elements that can be ordered and changed. Consider the following example that explains how a dictionary can map employee names with their employee IDs. 

    Difference between Hash Table and Hashmap
    Factor Hash Table Hashmap
    Type Synchronized Non-Synchronized
    Speed Fast Slow
    Null value Allow one null key and two or more null values Doesn’t allow any null keys or null values.

    Creating Dictionaries in Python

    In Python, there are two ways to create a dictionary as follows

    • Using curly braces – {}
    • Using the dict() function

    Curly Braces for Creating Dictionary

    Following is the example that explains how curly braces are used to create dictionaries in Python

    my_dict = {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    print (my_dict)

    type (my_dict)

    Output

    {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    dict

    The Dict() Function for Creating Dictionary

    Following is the example that explain how dict() in-built function used for creating dictionaries in Python

    new_dict = dict()

    print (new_dict)

    type (new_dict)

    Output

    {} dict

    Here, an empty dictionary is created as no key_value pairs are given as a parameter to the dict() function. Follow the below method to add values to the dictionary

    new_dict = dict{‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    print (new_dict)

    type (new_dict)

    Output

    {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    dict

    Nested Dictionaries

    If the dictionaries that are placed within other dictionaries are known as Nested Dictionaries.

    Example

    emp_details = {‘Employee’: {‘Grace’: { ‘ID’: ‘001’, ‘Salary’: 5000, ‘Position’: ‘Tech Lead’},

    ‘Merlyn’: {‘ID’ ‘002’, ‘Salary’: 8000, ‘Position’: ‘Project Manager’},

    ‘Jerry’: {‘ID’: ‘003’, ‘Salary’: 10000, ‘Position’: ‘General Manager’}}}

    Operations with Hash Tables using Dictionaries

    Following are the various operations that can be performed on hash tables in Python using dictionaries.

    • Accessing Values
    • Updating Values
    • Deleting Element

    Accessing Values

    There are many ways to access the values of a dictionary and some of them are as follows

    • Using key values
    • Using functions
    • Implementing the for loop

    Key Values for accessing dictionary values

    Key values implementation is used to access dictionary values.

    Example

    my_dict = {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    my_dict[‘Grace’]

    Output

    ‘001’

    Functions for accessing dictionary values

    Python has many in-built functions to be used for accessing dictionary values and some of them, get(), keys(), values(), and so on.

    Example

    my_dict = {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    print(my_dict.keys())

    print(my_dict.values())

    print(my_dict.get(‘Grace’))

    Output

    dict_keys([‘Grace’, ‘Merlyn’, ‘Jerry’])

    dict_keys([‘001’,’002’,’003’])

    001

    For loop for accessing the dictionary values

    For loop in Python can be used to access the key-value pairs of dictionaries easily by iterating over them.

    Example

    my_dict = {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    print(“All keys”)

    for x in my_dict:

    print(x)

    print(“All values”)

    for x in my_dict.values():

    print(x)

    print(“All keys and values”

    for x, y in my_dict.items()

    print (x, “:”, y)

    Output

    All keys

    Grace

    Merlyn

    Jerry

    All values

    001

    002

    003

    All keys and values

    Grace: 001

    Merlyn: 002

    Jerry: 003

    Updating values in Dictionaries

    We can modify the dictionary as per the requirement as it is a mutable data type. If we want to update the ID of the employee named grace from ‘001’ to ‘007’ or if we want to add up the employee, they are possible in Python.

    Example

    my_dict = {‘Grace’ : ‘001’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’}

    my_dict[‘Grace] = ‘007’ #updating the value of Grace

    my_dict[‘Freddy’] = ‘004’ #adding the new key-value pair

    print(my_dict)

    Output

    {‘Grace’: ‘007’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’, ‘Freddy’: ‘004’}

    Deleting key-pair values from a dictionary

    Python has some popular functions used to remove items from a dictionary and they are del(), pop(), popitem(), clear(), and so on.

    Example

    my_dict = {‘Grace’ : ‘007’, ‘Merlyn’ : ‘002’, ‘Jerry’: ‘003’, ‘Freddy’: ‘004’}

    del my_dict[‘Grace’] #removes key-value of Grace

    my_dict.pop(‘Merlyn’) #removes the value of Merlyn

    my_dict.popitem() #removes the last added item

    print(my_dict)

    Output

    {‘Jerry’: ‘003’}

    Converting Dictionary into a dataframe

    It is possible to convert the dictionary items into a dataframe in Python programming language using the pandas library. Check out the following example that explains how to convert them into a dataframe. Example import pandas as pan emp_details = {‘Employee’: {‘Grace’: { ‘ID’: ‘001’, ‘Salary’: 5000, ‘Position’: ‘Tech Lead’}, ‘Merlyn’: {‘ID’ ‘002’, ‘Salary’: 8000, ‘Position’: ‘Project Manager’}, ‘Jerry’: {‘ID’: ‘003’, ‘Salary’: 10000, ‘Position’: ‘General Manager’}}} df=pd.DataFrame(emp_details[‘Employee’]) print(df)
    Output
    Employee Grace Merlyn Jerry
    Designation Tech Lead Project Manager General Manager
    ID 001 002 003
    Salary 5000 8000 10000
    Conclusion

    We hope this blog helps you understand about Hash Tables and Hash Maps in Python. Learn the best Python Course at SLA to obtain complete hands-on exposure on python concepts. Become a master in application development, data science process, or scrip writing by enrolling in our Python Training in Chennai.

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