You are currently viewing Dictionary Python – Nice Studying

Dictionary Python – Nice Studying

Dictionaries in Python come tremendous helpful as they allow you to retailer and arrange information in a versatile approach. Consider it as a real-life dictionary the place you may seek for phrases and discover their meanings. With dictionaries, you may affiliate “keys” with “values.”  The keys are just like the phrases you’re wanting up, and the values are the meanings that go together with these phrases. 

Dictionaries present quick and environment friendly information retrieval based mostly on keys. Python makes use of hashing to rapidly find the worth related to a given key, making dictionaries very best for accessing particular information rapidly. Secondly, dictionaries assist you to arrange and construction your information logically. Moreover, you get a concise and readable solution to signify complicated relationships and mappings between completely different entities. 

Let’s be taught extra about creating, accessing, modifying, and updating dictionaries together with their operations and comprehensions. We’ll additionally find out about nested dictionaries, dictionary manipulation strategies, built-in features and a lot extra.

Creating and Accessing Dictionaries

Let’s dive into creating and accessing dictionaries in Python. 

Dictionary Syntax and Construction

Dictionaries are outlined utilizing curly braces ({}) and include key-value pairs. The important thing-value pairs are separated by colons (:) and particular person pairs are separated by commas. The keys may be any immutable information kind, similar to strings, numbers, or tuples, whereas the values may be any information kind, together with lists, strings, numbers, and even different dictionaries.

Dictionary Creation and Initialization

Let’s say we need to create a dictionary to retailer the ages of various individuals. Right here’s methods to do it:

ages = {"Alice": 25, "Bob": 30, "Charlie": 35}

Right here, we’ve got a dictionary referred to as ages with three key-value pairs. The keys are the names of individuals, and the corresponding values are their ages.

Accessing Values Utilizing Keys

To entry the values in a dictionary, you should utilize the keys because the “index” to retrieve the related values. Let’s proceed with our ages dictionary instance:

print(ages["Alice"])  # Output: 25

print(ages["Bob"])    # Output: 30

print(ages["Charlie"])# Output: 35

By utilizing the respective keys in sq. brackets, we are able to entry the values related to these keys. On this case, we retrieve the ages of Alice, Bob, and Charlie.

Dealing with Lacking Keys and Default Values

Typically, you might must deal with conditions the place a key doesn’t exist in a dictionary. To keep away from errors, you should utilize the get() methodology or conditional statements. The get() methodology lets you specify a default worth to return if the bottom line is not discovered:

print(ages.get(“Dave”, “Unknown”))  # Output: Unknown

Right here, the important thing “Dave” doesn’t exist within the age dictionary. By utilizing get(), we offer a default worth of “Unknown” to be returned as an alternative.

Alternatively, you should utilize conditional statements to test if a key exists in a dictionary earlier than accessing its worth:

if “Alice” in ages:

    print(ages["Alice"])  # Output: 25


    print("Alice's age will not be accessible.")

Right here, we test if the important thing “Alice” is current within the ages dictionary earlier than accessing its worth. If the important thing exists, we print the related age; in any other case, we show a message indicating that the age will not be accessible.

Modifying and Updating Dictionaries

Let’s discover ways to modify and replace dictionaries.

Including and Eradicating Key-Worth Pairs

Dictionaries are mutable, that means you may modify them by including or eradicating key-value pairs. So as to add a brand new key-value pair, you may merely assign a price to a brand new or current key:

scholar = {"identify": "Alice", "age": 25}

scholar["grade"] = "A"

Right here, we’ve got a dictionary referred to as scholar with two key-value pairs. We then add a brand new key referred to as “grade” and assign the worth “A” to it. The dictionary now has three key-value pairs.

To take away a key-value pair, you should utilize the del key phrase adopted by the dictionary identify and the important thing you need to take away:

del scholar["age"]

Right here, we take away the important thing “age” and its related worth from the coed dictionary. After this, the dictionary solely incorporates the “identify” and “grade” key-value pairs.

Updating Values for Present Keys

If you wish to replace the worth of an current key in a dictionary, you may merely reassign a brand new worth to that key:

scholar["grade"] = "A+"

Right here, we replace the worth of the “grade” key to “A+”. The dictionary is modified to replicate the up to date worth for the important thing.

Merging Dictionaries utilizing the replace() Methodology

You possibly can merge the contents of two dictionaries into one by utilizing the replace() methodology. Let’s say we’ve got two dictionaries, dict1 and dict2, and we need to merge them into a brand new dictionary referred to as merged_dict:

dict1 = {"a": 1, "b": 2}

dict2 = {"c": 3, "d": 4}

merged_dict = {}



Right here, we create an empty dictionary referred to as merged_dict after which use the replace() methodology so as to add the key-value pairs from dict1 and dict2. After executing this code, merged_dict will include all of the key-value pairs from each dict1 and dict2.

Frequent Dictionary Operations and Strategies

By mastering these frequent operations and strategies, you’ll be geared up to work effectively with dictionaries in Python. Whether or not it’s good to iterate over gadgets, test for key existence, extract keys or values, or discover the size of a dictionary, these strategies will show helpful in numerous programming situations.

Iterating over Dictionary Gadgets

It lets you entry each the keys and their corresponding values. You need to use a loop, similar to a for loop, to iterate over the gadgets. Right here’s an instance:

scholar = {"identify": "Alice", "age": 25, "grade": "A"}

for key, worth in scholar.gadgets():

    print(key, worth)

Right here, we iterate over the gadgets of the coed dictionary utilizing the gadgets() methodology. Inside the loop, we entry every key-value pair and print them. This lets you carry out operations on every merchandise or extract particular info from the dictionary.

Checking for the Existence of Keys

Typically, you might must test if a particular key exists in a dictionary. You need to use the in key phrase to carry out this test. Let’s see an instance:

scholar = {"identify": "Alice", "age": 25, "grade": "A"}

if "age" in scholar:

    print("Age exists within the dictionary.")


    print("Age doesn't exist within the dictionary.")

Right here, we test if the important thing “age” exists within the scholar dictionary utilizing the in key phrase. If the bottom line is current, we print a message indicating its existence; in any other case, we print a message indicating its absence.

Getting Keys, Values, or Each from a Dictionary

There are helpful strategies accessible to extract keys, values, or each from a dictionary. Listed here are some examples:

scholar = {"identify": "Alice", "age": 25, "grade": "A"}

keys = scholar.keys()

values = scholar.values()

gadgets = scholar.gadgets()

print(keys)   # Output: dict_keys(['name', 'age', 'grade'])

print(values) # Output: dict_values(['Alice', 25, 'A'])

print(gadgets)  # Output: dict_items([('name', 'Alice'), ('age', 25), ('grade', 'A')])

Right here, we use the keys(), values(), and gadgets() strategies to acquire the keys, values, and key-value pairs as separate objects. These strategies return particular views that assist you to entry the dictionary’s keys, values, or gadgets in a handy approach.

Discovering the Size of a Dictionary

To find out the variety of key-value pairs in a dictionary, you should utilize the len() operate. Right here’s an instance:

scholar = {"identify": "Alice", "age": 25, "grade": "A"}

size = len(scholar)

print(size)  # Output: 3

Right here, we calculate the size of the coed dictionary utilizing the len() operate. The operate returns the variety of key-value pairs within the dictionary.

Dictionary Comprehensions

Dictionary comprehensions are a concise and environment friendly solution to create dictionaries in Python. They observe the same idea to record comprehensions however assist you to create dictionaries with key-value pairs in a single line of code. Dictionary comprehensions present a clear and readable syntax for producing dictionaries based mostly on particular circumstances or transformations.

Creating Dictionaries Utilizing Comprehensions

To create a dictionary utilizing a comprehension, it’s good to outline the key-value pairs inside curly braces ({}) and specify the key-value expression. 

squares = {x: x**2 for x in vary(1, 6)}

Right here, we create a dictionary referred to as squares utilizing a comprehension. The expression x: x**2 represents the key-value pairs, the place the bottom line is x and the worth is x**2. We iterate over a variety from 1 to six and generate key-value pairs the place the keys are the numbers and the values are their squares. The ensuing dictionary will seem like this: {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}.

Benefits and Use Circumstances of Dictionary Comprehensions:

Dictionary comprehensions provide a number of benefits and can be utilized in numerous situations, similar to:

  • Concise and Readable Code: Dictionary comprehensions allow you to categorical complicated logic or transformations in a single line of code, bettering code readability and making your intentions clear.
  • Filtering and Transformation: It may be used to filter or modify information. This allows you to create dictionaries based mostly on particular necessities.
  • Environment friendly Knowledge Era: You possibly can generate dictionaries effectively, decreasing the quantity of code and bettering efficiency.
  • Knowledge Restructuring: Dictionary comprehensions are helpful when it’s good to restructure information from one format to a different. You possibly can map current keys to new values and even swap keys and values throughout the comprehension.

Nested Dictionaries

A nested dictionary is a dictionary that incorporates one other dictionary (or dictionaries) as its values. This enables for a hierarchical construction, the place you may arrange and retailer associated information throughout the nested ranges. In different phrases, the values of a dictionary may be dictionaries themselves.

Accessing and Modifying Values in Nested Dictionaries

To entry values in a nested dictionary, you should utilize a number of sq. brackets to specify the keys at every stage. Right here’s an instance:

college students = {

    "Alice": {

        "age": 25,

        "grade": "A"


    "Bob": {

        "age": 30,

        "grade": "B"



print(college students["Alice"]["age"])  # Output: 25

Right here, we’ve got a dictionary referred to as college students, the place every key represents a scholar’s identify, and the corresponding worth is a nested dictionary containing the coed’s age and grade. By utilizing a number of sq. brackets, we are able to entry particular values throughout the nested ranges.

To switch values in a nested dictionary, you may observe the same strategy. For instance:

college students["Alice"]["grade"] = "A+"

Right here, we replace the worth of the “grade” key for the coed named “Alice” to “A+”. This modification applies on to the nested dictionary inside the principle dictionary.

Examples of Nested Dictionary

Nested dictionaries may be helpful in numerous situations. Listed here are just a few examples:

  • Managing Scholar Information: You need to use a nested dictionary construction to retailer scholar info, similar to names, ages, and grades. Every scholar’s particulars may be represented by a nested dictionary inside the principle dictionary.
  • Organizing Stock Knowledge: In case you’re engaged on a list administration system, nested dictionaries may be helpful for organizing product particulars. Every product can have its personal dictionary containing attributes like identify, worth, amount, and many others.
  • Storing Multi-Stage Configuration Settings: When coping with configuration settings, you might have a number of ranges of settings, similar to sections and subsections. A nested dictionary can signify this hierarchical construction, permitting you to entry and modify settings at completely different ranges simply.

Dictionary Manipulation Strategies

Let’s discover some helpful strategies for manipulating dictionaries in Python.

Sorting Dictionaries by Keys or Values

Python gives handy strategies to kind dictionaries based mostly on both their keys or values. Listed here are a few examples:

To kind a dictionary by its keys, you should utilize the sorted() operate together with the keys() methodology. Right here’s an instance:

student_grades = {"Alice": 85, "Bob": 92, "Charlie": 78}

sorted_by_keys = {key: student_grades[key] for key in sorted(student_grades.keys())}

Right here, we create a brand new dictionary referred to as sorted_by_keys by iterating over the keys of the student_grades dictionary in sorted order. This can end in a dictionary with the keys sorted alphabetically: {“Alice”: 85, “Bob”: 92, “Charlie”: 78}.

To kind a dictionary by its values, you should utilize the sorted() operate with a lambda operate as the important thing parameter. Right here’s an instance:

student_grades = {"Alice": 85, "Bob": 92, "Charlie": 78}

sorted_by_values = {key: worth for key, worth in sorted(student_grades.gadgets(), key=lambda merchandise: merchandise[1])}

Right here, we create a brand new dictionary referred to as sorted_by_values by sorting the gadgets of the student_grades dictionary based mostly on their values utilizing a lambda operate. The ensuing dictionary will likely be sorted in ascending order by values: {“Charlie”: 78, “Alice”: 85, “Bob”: 92}.

Filtering Dictionaries Based mostly on Sure Standards

You possibly can filter dictionaries based mostly on particular standards utilizing conditional statements and dictionary comprehensions. Right here’s an instance:

student_grades = {"Alice": 85, "Bob": 92, "Charlie": 78}

filtered_grades = {key: worth for key, worth in student_grades.gadgets() if worth >= 80}

Right here, we create a brand new dictionary referred to as filtered_grades by iterating over the gadgets of the student_grades dictionary and together with solely these with values better than or equal to 80. The ensuing dictionary will include solely the key-value pairs that fulfill the given situation: {“Alice”: 85, “Bob”: 92}.

Making a Dictionary from Two Lists utilizing zip()

You possibly can create a dictionary by combining two lists utilizing the zip() operate. Right here’s an instance:

names = ["Alice", "Bob", "Charlie"]

ages = [25, 30, 28]

combined_dict = {identify: age for identify, age in zip(names, ages)}

Right here, we use zip() to mix the names and ages lists, after which create a brand new dictionary referred to as combined_dict. Every identify from the names record turns into key, and every corresponding age from the ages record turns into the respective worth within the dictionary: {“Alice”: 25, “Bob”: 30, “Charlie”: 28}.

Dictionary Strategies and Constructed-in Capabilities

Whether or not it’s good to entry keys, values, or gadgets, retrieve particular values, take away entries, or carry out common operations like discovering the size or most/minimal values, these strategies and features have gotten you lined.

Generally Used Dictionary Strategies

  • keys(): It returns a view object that incorporates all of the keys of a dictionary. This lets you entry and iterate over the keys conveniently.
  • values(): It returns a view object that incorporates all of the values of a dictionary. It gives a solution to entry and iterate over the values saved within the dictionary.
  • gadgets(): It returns a view object that incorporates all of the key-value pairs of a dictionary as tuples. It lets you entry and iterate over the key-value pairs collectively.
  • get(key, default): It retrieves the worth related to a particular key within the dictionary. If the bottom line is not discovered, it returns a default worth as an alternative of elevating an error.
  • pop(key, default): It removes and returns the worth related to a particular key from the dictionary. If the bottom line is not discovered, it returns a default worth or raises a KeyError if no default worth is offered.

Constructed-in Capabilities for Dictionaries

  • len(): It returns the variety of key-value pairs in a dictionary. It’s a handy solution to decide the scale or size of a dictionary.
  • max(): It may be used to search out the utmost key or worth in a dictionary, based mostly on their pure ordering. It’s helpful when it’s good to discover the most important key or worth in a dictionary.
  • min(): It really works equally to max(), however it finds the minimal key or worth in a dictionary based mostly on their pure ordering.

Superior Dictionary Strategies

By understanding these superior strategies, you may increase your dictionary expertise and use dictionaries extra successfully in Python. 

Dealing with Dictionary Collisions and Hash Capabilities

In Python, dictionaries use hash features to map keys to particular areas throughout the underlying information construction. Sometimes, two keys could produce the identical hash worth, leading to a collision. Python handles these collisions routinely, however it’s useful to grasp the ideas.

Hash features are chargeable for producing hash codes, distinctive identifiers related to every key. Python’s built-in hash operate produces these hash codes. When a collision happens, Python makes use of a way referred to as open addressing or chaining to resolve it.

As a person, you don’t want to fret an excessive amount of about dealing with collisions or hash features instantly. Python’s dictionary implementation takes care of this complexity behind the scenes, making certain environment friendly key-value lookups and updates.

Working with Dictionaries as Operate Arguments and Return Values

Dictionaries are versatile information constructions that may be handed as arguments to features and returned as operate outcomes. This enables for versatile and dynamic interactions. 

  • Passing Dictionaries as Operate Arguments:

It allows you to present key-value pairs as inputs. That is significantly helpful when you could have a various variety of arguments or need to bundle associated information collectively. Capabilities can then entry and make the most of the dictionary’s contents as wanted.

  • Returning Dictionaries from Capabilities:

Capabilities also can return dictionaries as their outcomes. This lets you encapsulate and supply computed or processed information in a structured method. The calling code can then entry and make the most of the returned dictionary to retrieve the specified info.

Working with dictionaries in operate arguments and return values promotes flexibility and modularity in your code. It permits for simple communication of knowledge between completely different components of your program.

Customizing Dictionaries utilizing OrderedDict and defaultdict

Python gives extra dictionary variants that provide customization past the usual dictionary implementation. Let’s discover two such variants:

The OrderedDict class maintains the order by which key-value pairs are inserted. Commonplace dictionaries don’t assure any particular order. By utilizing OrderedDict, you may iterate over the key-value pairs within the order they have been added. This may be useful when order issues, similar to preserving the order of components in a configuration or processing steps.

The defaultdict class, accessible within the collections module, gives a default worth for keys that don’t exist within the dictionary. This eliminates the necessity for handbook checks to deal with lacking keys. You possibly can specify the default worth when making a defaultdict. That is significantly helpful when working with counters, frequency distributions, or grouping information.

Actual-world Examples and Functions

Let’s discover some real-world examples and functions of dictionaries in Python. 

Knowledge Manipulation

Dictionaries are glorious for organizing and manipulating information. As an example, think about you could have a dataset of scholars with their names, grades, and topics. You need to use dictionaries to signify every scholar, the place the identify is the important thing and the related values include their grade and topics. This lets you simply entry and replace particular person scholar information.

Configuration Settings

Dictionaries are generally used to retailer and handle configuration settings in functions. As an example, you may create a dictionary to carry numerous settings, such because the database connection particulars, file paths, and person preferences. By utilizing key-value pairs, you may simply entry and modify these settings all through your program.

Dictionaries can be highly effective instruments for fixing programming issues. Listed here are just a few examples:

Counting and Frequency Evaluation

Dictionaries are sometimes employed for counting occurrences and performing frequency evaluation. As an example, you should utilize a dictionary to depend the frequency of phrases in a textual content doc or observe the incidence of characters in a string, which may be useful for numerous textual content processing duties.

Grouping and Categorization

Dictionaries are helpful for grouping and categorizing information based mostly on particular standards. As an example, you should utilize dictionaries to group college students by their grades, workers by departments, or merchandise by classes. This enables for environment friendly information group and retrieval.


Memoization is a way used to optimize operate calls by storing the outcomes of high-priced computations. Dictionaries are sometimes employed as a cache to retailer beforehand computed values. By utilizing the enter arguments as keys and the computed outcomes as values, you may keep away from redundant computations and enhance the efficiency of your code.

Concluding Ideas

We’ve lined numerous facets of dictionaries in Python, exploring key ideas and demonstrating their sensible functions. We’ve seen methods to create and entry dictionaries, modify and replace their contents, carry out frequent operations and strategies, make the most of superior strategies, and apply dictionaries to real-world situations and programming issues.

By now, you must have a stable understanding of how dictionaries work and their advantages. Nonetheless, there’s at all times extra to be taught and uncover! Dictionaries provide an unlimited array of prospects, and we encourage you to proceed exploring and experimenting with them. Strive completely different strategies, mix dictionaries with different information constructions, and apply them to unravel numerous challenges.

Leave a Reply