Tutorial Playlist
200 Lessons1. 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
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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
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. Reverse a List in Python
92. Python List remove() Method
93. How to Add Elements in a List in Python
94. How to Reverse a List in Python?
95. Difference Between List and Tuple in Python
96. List Slicing in Python
97. Sort in Python
98. Merge Sort in Python
99. Selection Sort in Python
100. Sort Array in Python
101. Sort Dictionary by Value in Python
102. Datetime Python
103. Random Number in Python
104. 2D Array in Python
105. Abs in Python
106. Advantages of Python
107. Anagram Program in Python
108. Append in Python
109. Applications of Python
110. Armstrong Number in Python
111. Assert in Python
112. Binary Search in Python
113. Binary to Decimal in Python
114. Bool in Python
115. Calculator Program in Python
116. chr in Python
117. Control Flow Statements in Python
118. Convert String to Datetime Python
119. Count in python
120. Counter in Python
121. Data Visualization in Python
122. Datetime in Python
123. Extend in Python
124. F-string in Python
125. Fibonacci Series in Python
126. Format in Python
127. GCD of Two Numbers in Python
128. How to Become a Python Developer
129. How to Run Python Program
130. In Which Year Was the Python Language Developed?
131. Indentation in Python
132. Index in Python
133. Interface in Python
134. Is Python Case Sensitive?
135. Isalpha in Python
136. Isinstance() in Python
137. Iterator in Python
138. Join in Python
139. Leap Year Program in Python
140. Lexicographical Order in Python
141. Literals in Python
142. Matplotlib
143. Matrix Multiplication in Python
144. Memory Management in Python
145. Modulus in Python
146. Mutable and Immutable in Python
147. Namespace and Scope in Python
148. OpenCV Python
149. Operator Overloading in Python
150. ord in Python
151. Palindrome in Python
152. Pass in Python
153. Pattern Program in Python
154. Perfect Number in Python
155. Permutation and Combination in Python
156. Prime Number Program in Python
157. Python Arrays
158. Python Automation Projects Ideas
159. Python Frameworks
160. Python Graphical User Interface GUI
161. Python IDE
162. Python input and output
163. Python Installation on Windows
164. Python Object-Oriented Programming
165. Python PIP
166. Python Seaborn
167. Python Slicing
168. type() function in Python
169. Queue in Python
170. Replace in Python
171. Reverse a Number in Python
172. Reverse a string in Python
173. Reverse String in Python
174. Stack in Python
175. scikit-learn
176. Selenium with Python
177. Self in Python
178. Sleep in Python
179. Speech Recognition in Python
180. Split in Python
181. Square Root in Python
182. String Comparison in Python
183. String Formatting in Python
184. String Slicing in Python
185. Strip in Python
186. Subprocess in Python
187. Substring in Python
188. Sum of Digits of a Number in Python
189. Sum of n Natural Numbers in Python
190. Sum of Prime Numbers in Python
191. Switch Case in Python
192. Python Program to Transpose a Matrix
193. Type Casting in Python
194. What are Lists in Python?
195. Ways to Define a Block of Code
196. What is Pygame
197. Why Python is Interpreted Language?
198. XOR in Python
199. Yield in Python
200. Zip in Python
A versatile and extensively employed programming language, Python equips developers with a multitude of tools and methods for efficiently managing intricate tasks. Among these tools are nested for loops, which constitute a formidable resource in Python's toolkit. These loops offer a methodical approach to addressing repetitive tasks, particularly when the requirement involves traversing multiple sequences or executing complex operations. This all-encompassing guide will immerse you in the realm of nested for loop in Python, dissecting their syntax, presenting a variety of examples, and illustrating the utilization of break and continue statements within these loop structures.
A nested loop, found within another loop, empowers you to incorporate one or more loops within the parent loop. In Python, this programming construct provides a remarkable level of adaptability, granting you the capacity to effectively address repetitive tasks frequently associated with intricate and multifaceted data structures or sequences. By nesting loops, you can navigate through multidimensional data, perform various operations on each combination of elements, and handle scenarios where you need to work with elements within elements. This versatile approach empowers Python developers to create structured, organized, and powerful code for a wide range of applications, from iterating through matrices to generating intricate patterns and working with nested data structures.
The syntax of a nested loop in Python provides a structured way to work with repetitive tasks that involve multiple sequences or complex data structures. A nested loop consists of one loop encapsulated within another, and it can be represented as follows:
for outer_loop_variable in outer_sequence:
# Outer loop code
for inner_loop_variable in inner_sequence:
# Inner loop code
Outer Loop: The outer loop is defined using the for keyword, followed by an outer_loop_variable, which represents the variable that takes on values from the outer_sequence.
Outer Loop Code: The code specific to the outer loop is indented beneath it. This code executes for each iteration of the outer loop and typically involves actions or decisions related to the elements of the outer_sequence.
Inner Loop: Inside the outer loop, there's another for loop, known as the inner loop. This for loop inside for loop is defined with its own inner_loop_variable, which takes on values from the inner_sequence.
Inner Loop Code: The code associated with the inner loop is indented beneath it. This code executes for each iteration of the inner loop.
Now, let's dive into some examples to understand how nested loops work in Python.
python code
# Using nested loops to print a pattern
for i in range(3):
for j in range(3):
print(i, j)
In this example, we have two loops: an outer loop for i in range(3) and an inner loop for j in range(3). The outer loop iterates from 0 to 2, and for each value of i, the inner loop iterates from 0 to 2. As a result, this code prints combinations of i and j.
python code
# Printing the multiplication table of 5
for i in range(1, 11):
for j in range(1, 11):
product = i * j
print(f"{i} x {j} = {product}")
In this example, we use 3 nested for loops Python to print the multiplication table of 5. The outer loop iterates over the numbers from 1 to 10, representing the first factor. The inner loop also iterates from 1 to 10, representing the second factor. The product of i and j gives the result, and it is printed as part of the table.
python code
# Printing patterns using different inner and outer nested loops
for i in range(5):
for j in range(i):
print("*", end=" ")
print()
In this example, we create a pattern using nested loops. The outer loop iterates over the numbers from 0 to 4, controlling the number of asterisks to be printed on each line. The inner loop iterates from 0 to i, printing the asterisks on the same line without moving to the next line. The end=" " parameter in the print function ensures that spaces are used instead of line breaks to separate the asterisks.
In Python, the break statement serves as a valuable instrument, granting you the capability to prematurely exit a loop, thus circumventing any subsequent iterations. This functionality proves exceptionally advantageous, especially in the context of nested loops, as it permits the termination of both the inner and outer loops upon the satisfaction of certain conditions.
Consider the following Python code:
# Using break in nested loops
for i in range(3):
for j in range(3):
if i == 1 and j == 1:
break
print(i, j)
In this code snippet, nested for loops Python lists are employed. The outer loop, defined by for i in range(3):, iterates over a sequence of numbers from 0 to 2. Within this outer loop, we have an inner loop: for j in range(3):, which iterates over the same range of numbers.
Now, the power of the break statement is evident within the inner loop. We've incorporated a conditional statement: if i == 1 and j == 1:. This condition checks whether the values of i and j are both equal to 1. If this condition is satisfied, the break statement is executed.
When the break statement is triggered, it serves as an abrupt exit from the inner loop. It effectively skips any remaining iterations of the inner loop and returns to the outer loop. Importantly, the execution of the outer loop is not affected by the break statement within the inner loop.
Here's how the code behaves step by step:
The outer loop starts with i equal to 0.
The result is that the code prints the following pairs of numbers:
0 0, 0 1, 0 2, 2 0, 2 1, 2 2
The key takeaway is that the break statement is a powerful tool for exiting loops prematurely when specific conditions are met. In the context of nested loops, it helps you control the flow of your program and provides flexibility for handling complex iterations.
In this example, it terminated the inner loop when i and j equaled 1. However, if you had other conditions or requirements in your code, you could use the break statement to tailor the behavior of your loops accordingly.
The continue statement is used to skip the rest of the current iteration of a loop and proceed to the next iteration. It can be beneficial in nested while loop in Python when you want to skip certain iterations while continuing with the remaining iterations. Here's an example:
python code
# Using continue in nested loops
for i in range(3):
for j in range(3):
if i == 1 and j == 1:
continue
print(i, j)
List comprehensions, a powerful and concise feature offered by Python, enable the creation of compact, single-line nested loops to generate lists or other iterables. They come in particularly handy when you're tasked with producing lists derived from combinations or alterations of elements originating from one or multiple sequences.
new_list = [expression for item in iterable]
expression: The expression that specifies how to transform or filter items from the iterable.
item: The variable representing each element in the iterable.
iterable: The sequence from which elements are drawn.
Now, let's dive into the nested loop example you provided:
# Single-line nested loops using list comprehension
nested_list = [(i, j) for i in range(3) for j in range(2)]
print(nested_list)
In this example, you are creating a list of tuples (i, j) using list comprehension. Here's a step-by-step explanation:
[(i, j): This part defines the expression that specifies the elements to include in the resulting list. In this case, you want to create tuples (i, j).
for i in range(3): The first for clause iterates over the values of i in the range from 0 to 2 (inclusive).
for j in range(2): The second for clause is nested inside the first one and iterates over the values of j in the range from 0 to 1 (inclusive).
When you combine these for clauses within the list comprehension, you are effectively generating all combinations of i and j. The resulting nested_list contains the following tuples:
css code
[(0, 0), (0, 1), (1, 0), (1, 1), (2, 0), (2, 1)]
As you can see, this concise one-liner effectively replaces traditional nested loops, making your code more readable and compact while achieving the same result.
Python nested for loops, a powerful feature, enable you to efficiently handle complex data structures and carry out repetitive tasks. Once you grasp their syntax and application, they empower you to craft well-structured and organized code. You've learned how to create basic patterns, print multiplication tables, and use break and continue statements in nested loops. Additionally, we explored single-line nested loops using list comprehensions, providing a more concise way to achieve the same results.
1. What is a Python nested loop?
A nested loop involves one loop contained within another, with the inner loop executed as the outer loop begins its initial iteration. The inner loop will then be triggered again by the outer loop's second run.
2. What is the difference between break and continue in nested loops?
break statement is used to exit the entire loop prematurely and continue is used to skip the rest of the current iteration and proceed to the next iteration of the loop.
3. Can I nest loops of different types in Python?
Yes, you can nest loops of different types, such as for, while, and even mixed types, depending on your requirements.
4. Are nested loops inefficient?
Nested loops can be less efficient for large datasets, as they lead to higher time complexity. It's important to analyze the performance of your code and consider alternative approaches, such as using built-in functions or list comprehensions.
5. What are some practical use cases for nested loops?
Nested loops are commonly used for tasks like searching in multi-dimensional arrays, generating combinations or permutations, and working with nested data structures.
6. What is the Python equivalent of a nested for loop?
Another helpful feature of the itertools module is the chain. If we have many variables and wish to loop over them consecutively as if they were just one iterable, we should use chains rather than nested loops.
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Director of Engineering
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upGrad does not grant credit; credits are granted, accepted or transferred at the sole discretion of the relevant educational institution offering the diploma or degree. We advise you to enquire further regarding the suitability of this program for your academic, professional requirements and job prospects before enr...