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Python Tutorials - Elevate You…
1. Introduction to Python
2. Features of Python
3. How to install python in windows
4. How to Install Python on macOS
5. Install Python on Linux
6. Hello World Program in Python
7. Python Variables
8. Global Variable in Python
9. Python Keywords and Identifiers
10. Assert Keyword in Python
11. Comments in Python
12. Escape Sequence in Python
13. Print In Python
14. Python-if-else-statement
15. Python for Loop
16. Nested for loop in Python
17. While Loop in Python
18. Python’s do-while Loop
19. Break in Python
20. Break Pass and Continue Statement in Python
21. Python Try Except
22. Data Types in Python
23. Float in Python
24. String Methods Python
25. List in Python
26. List Methods in Python
27. Tuples in Python
28. Dictionary in Python
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29. Set in Python
30. Operators in Python
31. Boolean Operators in Python
32. Arithmetic Operators in Python
33. Assignment Operator in Python
34. Bitwise operators in Python
35. Identity Operator in Python
36. Operator Precedence in Python
37. Functions in Python
38. Lambda and Anonymous Function in Python
39. Range Function in Python
40. len() Function in Python
41. How to Use Lambda Functions in Python?
42. Random Function in Python
43. Python __init__() Function
44. String Split function in Python
45. Round function in Python
46. Find Function in Python
47. How to Call a Function in Python?
48. Python Functions Scope
49. Method Overloading in Python
50. Method Overriding in Python
51. Static Method in Python
52. Python List Index Method
53. Python Modules
54. Math Module in Python
55. Module and Package in Python
56. OS module in Python
57. Python Packages
58. OOPs Concepts in Python
59. Class in Python
60. Abstract Class in Python
61. Object in Python
62. Constructor in Python
63. Inheritance in Python
64. Multiple Inheritance in Python
65. Encapsulation in Python
66. Data Abstraction in Python
67. Opening and closing files in Python
68. How to open JSON file in Python
69. Read CSV Files in Python
70. How to Read a File in Python
71. How to Open a File in Python?
72. Python Write to File
73. JSON Python
74. Python JSON – How to Convert a String to JSON
75. Python JSON Encoding and Decoding
76. Exception Handling in Python
77. Recursion in Python
78. Python Decorators
79. Python Threading
80. Multithreading in Python
81. Multiprocеssing in Python
82. Python Regular Expressions
83. Enumerate() in Python
84. Map in Python
85. Filter in Python
86. Eval in Python
87. Difference Between List, Tuple, Set, and Dictionary in Python
88. List to String in Python
89. Linked List in Python
90. Length of list in Python
91. Python List remove() Method
92. How to Add Elements in a List in Python
93. How to Reverse a List in Python?
94. Difference Between List and Tuple in Python
95. List Slicing in Python
96. Sort in Python
97. Merge Sort in Python
98. Selection Sort in Python
99. Sort Array in Python
100. Sort Dictionary by Value in Python
101. Datetime Python
102. Random Number in Python
103. 2D Array in Python
104. Abs in Python
105. Advantages of Python
106. Anagram Program in Python
107. Append in Python
108. Applications of Python
109. Armstrong Number in Python
110. Assert in Python
111. Binary Search in Python
112. Binary to Decimal in Python
113. Bool in Python
114. Calculator Program in Python
115. chr in Python
116. Control Flow Statements in Python
117. Convert String to Datetime Python
118. Count in python
119. Counter in Python
120. Data Visualization in Python
121. Datetime in Python
122. Extend in Python
123. F-string in Python
124. Fibonacci Series in Python
125. Format in Python
126. GCD of Two Numbers in Python
127. How to Become a Python Developer
128. How to Run Python Program
129. In Which Year Was the Python Language Developed?
130. Indentation in Python
131. Index in Python
132. Interface in Python
133. Is Python Case Sensitive?
134. Isalpha in Python
135. Isinstance() in Python
136. Iterator in Python
137. Join in Python
138. Leap Year Program in Python
139. Lexicographical Order in Python
140. Literals in Python
141. Matplotlib
142. Matrix Multiplication in Python
143. Memory Management in Python
144. Modulus in Python
145. Mutable and Immutable in Python
146. Namespace and Scope in Python
147. OpenCV Python
148. Operator Overloading in Python
149. ord in Python
150. Palindrome in Python
151. Pass in Python
152. Pattern Program in Python
153. Perfect Number in Python
154. Permutation and Combination in Python
155. Prime Number Program in Python
156. Python Arrays
157. Python Automation Projects Ideas
158. Python Frameworks
159. Python Graphical User Interface GUI
160. Python IDE
161. Python input and output
162. Python Installation on Windows
163. Python Object-Oriented Programming
164. Python PIP
165. Python Seaborn
166. Python Slicing
167. type() function in Python
168. Queue in Python
169. Replace in Python
170. Reverse a Number in Python
171. Reverse a string in Python
172. Reverse String in Python
173. Stack in Python
174. scikit-learn
175. Selenium with Python
176. Self in Python
177. Sleep in Python
178. Speech Recognition in Python
179. Split in Python
180. Square Root in Python
181. String Comparison in Python
182. String Formatting in Python
183. String Slicing in Python
184. Strip in Python
185. Subprocess in Python
186. Substring in Python
187. Sum of Digits of a Number in Python
188. Sum of n Natural Numbers in Python
189. Sum of Prime Numbers in Python
190. Switch Case in Python
191. Python Program to Transpose a Matrix
192. Type Casting in Python
193. What are Lists in Python?
194. Ways to Define a Block of Code
195. What is Pygame
196. Why Python is Interpreted Language?
197. XOR in Python
198. Yield in Python
199. Zip in Python
In this tutorial, we delve deep into one of Python's most versatile data structures: the dictionary. Dictionary in Python is a foundational component for those upskilling in the field as it offers efficient key-value data storage, proving indispensable for data manipulation, storage, and retrieval tasks.
Dictionary in Python, termed "dict", stands out as dynamic collections of key-value pairs. With their ability to provide rapid and efficient data access, they become an inevitable tool, especially when dealing with voluminous data that needs a structured format for easy access and modification.
Code:
# Creating a dictionary using curly braces {}
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
print(student)
The complexities for creating a dictionary in Python depend on various factors, including the size of the dictionary, the hash function's efficiency, and the implementation details of the Python interpreter. Here are the general complexities:
Time Complexity:
Best Case: O(1) - When creating an empty dictionary or adding the first few elements.
Average Case: O(1) - Constant time for inserting a new key-value pair.
Worst Case: O(n) - In the worst case, when there are hash collisions or frequent resizing, insertion can become linear. Resizing involves rehashing and reinserting elements, which can take time proportional to the size of the dictionary.
Space Complexity:
O(n) - The space complexity for a dictionary depends on the number of key-value pairs it contains.
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Changing the value of an existing key
student["age"] = 21
print(student) # Output: {'name': 'Alice', 'age': 21, 'major': 'Computer Science'}
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Changing the value of an existing key
student["age"] = 21
print(student) # Output: {'name': 'Alice', 'age': 21, 'major': 'Computer Science'}
# Adding a new key-value pair
student["university"] = "ABC University"
print(student) # Output: {'name': 'Alice', 'age': 21, 'major': 'Computer Science', 'university': 'ABC University'}
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Accessing values using keys
name = student["name"]
age = student["age"]
major = student["major"]
print("Name:", name) # Output: Name: Alice
print("Age:", age) # Output: Age: 20
print("Major:", major) # Output: Major: Computer Science
Code:
# Creating a nested dictionary
student = {
"name": "Alice",
"age": 20,
"contact": {
"email": "alice@example.com",
"phone": "123-456-7890"
},
"courses": {
"math": 95,
"history": 85,
"english": 90
}
}
# Accessing elements in the nested dictionary
email = student["contact"]["email"]
math_score = student["courses"]["math"]
print("Email:", email) # Output: Email: alice@example.com
print("Math Score:", math_score) # Output: Math Score: 95
Code:
# Nested dictionary
student = {
"name": "Alice",
"age": 20,
"contact": {
"email": "alice@example.com",
"phone": "123-456-7890"
},
"courses": {
"math": 95,
"history": 85,
"english": 90
}
}
# Accessing a nested element
email = student["contact"]["email"]
math_score = student["courses"]["math"]
print("Email:", email) # Output: Email: alice@example.com
print("Math Score:", math_score) # Output: Math Score: 95
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Deleting a key-value pair
del student["age"]
print(student) # Output: {'name': 'Alice', 'major': 'Computer Science'}
Code:
# Creating a dictionary
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Accessing keys, values, and items
keys = student.keys()
values = student.values()
items = student.items()
print("Keys:", keys) # Output: Keys: dict_keys(['name', 'age', 'major'])
print("Values:", values) # Output: Values: dict_values(['Alice', 20, 'Computer Science'])
print("Items:", items) # Output: Items: dict_items([('name', 'Alice'), ('age', 20), ('major', 'Computer Science')])
# Getting a value by key, with a default value if the key is not present
age = student.get("age", "N/A")
gender = student.get("gender", "N/A")
print("Age:", age) # Output: Age: 20
print("Gender:", gender) # Output: Gender: N/A
# Adding or updating a key-value pair
student["university"] = "ABC University"
print(student) # Output: {'name': 'Alice', 'age': 20, 'major': 'Computer Science', 'university': 'ABC University'}
# Removing a key-value pair and returning its value
removed_major = student.pop("major")
print("Removed Major:", removed_major) # Output: Removed Major: Computer Science
# Removing the last key-value pair and returning it as a tuple
last_item = student.popitem()
print("Last Item:", last_item) # Output: Last Item: ('university', 'ABC University')
# Clearing all items from the dictionary
student.clear()
print(student) # Output: {}
# Copying a dictionary
original_dict = {"a": 1, "b": 2}
copy_dict = original_dict.copy()
print(copy_dict) # Output: {'a': 1, 'b': 2}
Iterating Through Keys:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating through keys using a for loop
for key in student:
print(key)
# Output:
# name
# age
# major
Iterating Through Values:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating through values using a for loop
for value in student.values():
print(value)
# Output:
# Alice
# 20
# Computer Science
Iterating With Key-Value Pairs (Items):
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating with key-value pairs using a for loop
for key, value in student.items():
print(key, ":", value)
# Output:
# name : Alice
# age : 20
# major : Computer Science
Using keys() Method with for loop:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating through keys using keys() method and a for loop
for key in student.keys():
print(key)
# Output:
# name
# age
# major
Using values() Method with for loop:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating through values using values() method and a for loop
for value in student.values():
print(value)
# Output:
# Alice
# 20
# Computer Science
Using items() Method with for Loop:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Iterating with key-value pairs using items() method and a for loop
for key, value in student.items():
print(key, ":", value)
# Output:
# name : Alice
# age : 20
# major : Computer Science
Dictionary keys in Python have certain properties that influence their behavior and usage. Here are some important properties of dictionary keys:
Here's an example demonstrating some of these properties:
Code:
# Immutable keys
dict1 = {1: "one", "two": 2, (3, 4): "tuple_key"}
print(dict1)
# Unique keys
dict2 = {"name": "Alice", "age": 25, "name": "Bob"}
print(dict2) # Output: {'name': 'Bob', 'age': 25}
# Unordered behavior (Python < 3.7)
dict3 = {"a": 1, "b": 2, "c": 3}
print(dict3) # Output may not maintain order
Here's an example showcasing some of these functions and methods:
Code:
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
print(len(student)) # Output: 3
print(student.get("age")) # Output: 20
print(student.keys()) # Output: dict_keys(['name', 'age', 'major'])
print(student.values()) # Output: dict_values(['Alice', 20, 'Computer Science'])
print(student.items()) # Output: dict_items([('name', 'Alice'), ('age', 20), ('major', 'Computer Science')])
# Removing and returning a key-value pair
removed_item = student.popitem()
print(removed_item) # Output: ('major', 'Computer Science')
# Updating the dictionary with new data
new_data = {"university": "ABC University", "age": 21}
student.update(new_data)
print(student) # Output: {'name': 'Alice', 'age': 21, 'university': 'ABC University'}
Here's an example demonstrating how to use some of these built-in dictionary methods:
Code:
# Creating a dictionary
student = {
"name": "Alice",
"age": 20,
"major": "Computer Science"
}
# Using dictionary methods
print(student.keys()) # Output: dict_keys(['name', 'age', 'major'])
print(student.values()) # Output: dict_values(['Alice', 20, 'Computer Science'])
print(student.items()) # Output: dict_items([('name', 'Alice'), ('age', 20), ('major', 'Computer Science')])
# Removing and returning a key-value pair
removed_item = student.popitem()
print(removed_item) # Output: ('major', 'Computer Science')
# Updating the dictionary with new data
new_data = {"university": "ABC University", "age": 21}
student.update(new_data)
print(student) # Output: {'name': 'Alice', 'age': 21, 'university': 'ABC University'}
# Clearing the dictionary
student.clear()
print(student) # Output: {}
Dictionaries in Python are undeniably a pivotal data structure, bridging the gap between data storage needs and efficiency. Their flexible nature, combined with Python's suite of methods tailored for them, ensures their broad application, from simple data manipulations to complex algorithm implementations. For those on the path to Python mastery, understanding dictionaries is paramount. Hungry for more? upGrad offers a variety of courses tailored to nourish your thirst for knowledge in Python.
Dictionaries in Python are mutable, allowing modifications after their creation.
Some common dictionary methods in Python include dict.keys(), dict.values(), and dict.update(). These enhance interactions with dictionaries.
Utilize the for loop with dict.items() for efficient key-value pair iteration.
Employ the sorted() function and specify key=lambda x: x[1].
The method dict.keys() will fetch all keys present in the dictionary.
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