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
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
Now Reading
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
Python's slicing capabilities are essential and necessary for data processing and manipulation because they make it simpler to work concisely and effectively with data sequences. This tutorial will go in-depth on how to use the Python slice function, dissecting its syntax, parameters, and use cases. This tutorial aims to offer a complete guide to Python’s slicing functionalities.
Slicing is a fundamental and potent Python feature that makes it simple to work with subsequences and facilitates data manipulation and analysis. It works with strings, tuples, and other iterable types in addition to lists. The Python slice function, a crucial tool for text editing and data translation, serves as the tutorial's focal point.
An index in Python slicing is a numeric position that designates a certain element's location inside a sequence (such as a string, list, or tuple). The unique index for each element in a series starts at 0 for the first element, 1 for the second element, and so on.
Important details regarding indexes in Python slicing:
For example, my_list[0] will access the first element, my_list[-1] will access the last element, and my_list[-2] will access the second last element.
For instance, my_list[2:5] extracts the items at positions 2, 3, and 4, but not the element at position 5.
The process of extracting and manipulating components within sequences like lists, strings, and tuples is made simpler by the powerful feature called "slicing" which is available in the flexible and popular programming language Python. Slicing is a fundamental Python programming idea, and in this introduction, especially for those unfamiliar with Python, we'll examine what it is and how it might be applied.
A sequence can be thought of as a collection of things that are in a specific order, such as a string of letters, a list of numbers, or a tuple of values. You can access particular sections of these sequences using Python's slicing feature instead of having to loop through each element one at a time.
By defining a range of indices, slicing in Python can be used to extract a piece of a sequence (such as a text, list, or tuple). Slicing's basic syntax is as follows:
sequence[start:stop:step]
The meaning of each component of the slicing syntax is explained below:
By counting positions from the end of a sequence and using negative values as indices, cutting with negative indices in Python enables you to remove elements from sequences (such as strings, lists, or tuples). When you need to deal with pieces from the sequence's end but are unsure of their exact length, this capability comes in helpful.
Here are some instances of negative index slicing:
Code:
my_list = [0, 1, 2, 3, 4, 5]
# Accessing elements from the end of the list
last_element_of_the_list = my_list[-1] # 5
second_last_element_of_the_list = my_list[-2] # 4
# Slicing a portion of the list using negative indices
subset = my_list[-3:-1] # [3, 4] (from the third-to-last to the second-to-last element)
In the aforementioned example, my_list[-1] accesses the very last element of the list, followed by my_list[-2] and my_list[-3]. Remember that the starting index is inclusive and the stopping index is exclusive when slicing with negative indices.
When you don't know how long a sequence is but still need to work with pieces near the conclusion, negative indices are especially helpful.
Code:
my_list = [0, 1, 2, 3, 4, 5]
# Slice to get the last three elements
last_three_of_the_list = my_list[-3:] # [3, 4, 5]
# Reverse the list using negative indices
reversed_list = my_list[::-1] # [5, 4, 3, 2, 1, 0]
When working with sequences, especially when you need to work with components at both ends of the series, slicing with negative indices can make your code more flexible and legible.
You can extract elements from a sequence (such as a string, list, or tuple) with a given gap between them by using the advanced capability of specifying the step in slicing. How many places are skipped between each slice element depends on the step value. You use the start:stop:step format to include the step value in the slicing syntax.
To better understand how specifying the step functions, let's look at some examples:
Code:
my_list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
# Slicing with a step of 2 (every second element)
subset = my_list[0::2]
print(subset)
# Result: [0, 2, 4, 6, 8]
# This slice starts from index 0, goes to the end, and selects every second element.
# Slicing with a step of 3 (every third element)
subset = my_list[1::3]
print(subset)
# Result: [1, 4, 7]
# This slice starts from index 1, goes to the end, and selects every third element.
# Slicing with a negative step to reverse the list
reversed_list = my_list[::-1]
print(reversed_list)
# Result: [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
# This slice starts from the end, goes to the beginning, and selects every element with a step of -1.
# Combining start, stop, and step to extract a specific pattern
subset = my_list[2:8:2]
print(subset)
# Result: [2, 4, 6]
# This slice starts from index 2, goes up to index 8 (exclusive), and selects every second element.
By defining the step, you can quickly remove parts from a series at predetermined intervals, skip undesirable elements, or even reverse the order. This function is very helpful for extracting periodic data points from a bigger dataset or filtering data.
Slicing can be used in Python to reverse the elements of a data structure, such as a list or string. By slicing, you can reorder the elements in a series to produce a new one. The following describes how to reverse items in several data structure types:
Code:
our_list = [1, 2, 3, 4, 5]
reversed_list = our_list[::-1]
print(reversed_list)
# Output: [5, 4, 3, 2, 1]
In this case, our_list[::-1] makes a new list with the components of my_list arranged in the opposite direction.
Code:
our_string = "Hello, let us learn Python!"
reversed_string = our_string[::-1]
print(reversed_string)
# Output: "!nohtyP nrael su tel ,olleH"
Slicing can also be used to reverse the characters in strings.
Because tuples cannot be changed, you must first convert them into another data structure, such as a list, reverse them, and then, if necessary, convert them back into tuples:
Code:
our_tuple = (1, 2, 3, 4, 5, 6)
reversed_list = list(our_tuple)[::-1]
reversed_tuple = tuple(reversed_list)
print(reversed_tuple)
# Output: (6, 5, 4, 3, 2, 1)
When a slice object is created in Python using the slice() function, it can be used to extract a section of a sequence (such as a string, list, or tuple) using the slice notation. Start, Stop, and Step are the three optional inputs that the slice() function accepts. These arguments are equivalent to the sequence[start:stop:step] parameters used in slicing notation.
The slice() function's syntax is as follows:
slice(start, stop, step)
The slice() function can be used as shown in the following examples:
Code:
our_list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
# Create a slice object to represent a slice from index 2 to 5 (exclusive)
our_slice = slice(2, 5)
subset = our_list[our_slice]
print(subset)
# Result: [2, 3, 4]
# Create a slice object to represent a slice from the beginning to index 3 (exclusive)
our_slice = slice(None, 3)
subset = our_list[our_slice]
print(subset)
# Result: [0, 1, 2]
# Create a slice object to represent a slice from index 5 to the end of the list
our_slice = slice(5, None)
subset = our_list[our_slice]
print(subset)
# Result: [5, 6, 7, 8, 9]
# Create a slice object to represent a slice of every second element
our_slice = slice(None, None, 2)
subset = our_list[our_slice]
print(subset)
# Result: [0, 2, 4, 6, 8]
When you want to package a slicing process to reuse it several times or send it as an argument to methods that need a slice object, the slice() function can be helpful.
Code:
our_text = "Hello, World!"
our_slice = slice(7) # Create a slice object for the first 7 characters
substring = our_text[our_slice]
print(substring) # Output: "Hello, "
Code:
our_list = [0, 1, 2, 3, 4, 5, 6]
our_slice = slice(2, 5) # Create a slice object from index 2 to 5 (exclusive)
subset = our_list[our_slice]
print(subset) # Output: [2, 3, 4]
Code:
our_tuple = (10, 20, 30, 40, 50)
our_slice = slice(1, 4) # Create a slice object from index 1 to 4 (exclusive)
subset = our_tuple[our_slice]
print(subset) # Output: (20, 30, 40)
Code:
our_text = "Hello, World!"
our_slice = slice(-6, None) # Create a slice object for the last 6 characters
substring = our_text[our_slice]
print(substring) # Output: "World!"
Code:
our_tuple = (10, 20, 30, 40, 50)
our_slice = slice(-3, None) # Create a slice object for the last 3 elements
subset = our_tuple[our_slice]
print(subset) # Output: (30, 40, 50)
Code:
our_text = "Python Programming"
our_substring = our_text[7:18] # Slice from index 7 to 18 (exclusive)
print(our_substring) # Output: "Programming"
Code:
our_list = [10, 20, 30, 40, 50]
subset = our_list[1:4] # Slice from index 1 to 4 (exclusive)
print(subset) # Output: [20, 30, 40]
Code:
our_list = [0, 1, 2, 3, 4, 5]
# Modify a slice of the list
our_list[2:4] = [9, 8]
print(our_list) # Output: [0, 1, 9, 8, 4, 5]
To sum up, Python slicing is a flexible and strong tool that enables you to extract, modify, and interact with particular parts of sequences like strings, lists, and tuples. It gives you precise control over the elements you can access and change. Python programmers who are proficient in slicing can handle a variety of data sets and tackle a variety of programming problems.
1. What happens if the start or stop of a slice is missed?
Start defaults to 0 (the start of the series) if you omit it. Stop defaults to the length of the sequence (the end of the sequence) if you omit it in Python slicing.
2. How do you cut a sequence in half to get the nth element in Python slicing?
You can set the step parameter to n to obtain a sequence's nth element. The expression my_list[::3] pulls the third element from each row in the list.
3. What occurs when a slice's start index is higher than its stop index?
The slice will produce an empty sequence if the start index is higher than the stop index. My_list[5:2] will, for instance, produce an empty list.
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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...