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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
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
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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
If you’re a seasoned coder, you pretty much know about the benefits of using Python. However, if you are a beginner and are searching for opportunities to get to know Python more closely, this is the place to get started.
This tutorial will examine some of the real-life applications of Python while understanding why it is popular. Apart from this, it will determine the uses of web development, and data analysis in understanding the reach of Python’s capabilities. Let’s get started.
This tutorial will provide our readers with a list of 16 tools along with the various uses and applications for each of them. We will also examine why Python is popular and in high demand. Simultaneously, we will weigh both the advantages and disadvantages of Python as a programming language before moving on to the conclusion.
There is no doubt that Python is extensively used throughout the globe to perform some important functions. But why is it so popular? To answer this, we will have to look at Python’s features and their uses. Its easy-to-use platform ensures that the data produced is clear and readable. As a result, it is beginner-friendly as well and is highly versatile in that regard.
For a growing developer, Python is the best tool to work with considering its versatility. Python offers a suite for web development, machine learning, data analysis, and scientific computing depending on the requirements of the developer. Additionally, Python supports a robust community who are equipped to support engineers and developers towards continuous improvement.
To access this, one may simply go over to the frameworks section where various tools and libraries are on display. As it is open-source, any developer can work with the system and put it to their use. Its large community of developers, extensive support, and tool accessibility serve as advantages of Python.
We’re going to list a total of the top 16 Python applications in the real world. In doing so, we give our readers a better insight into the world of Python and its applications.
Some of the popular keywords in Python are listed below:
and | or | not | if | elif |
else | for | while | break | as |
def | lambda | pass | return | True |
False | try | with | assert | class |
continue | del | except | finally | from |
global | import | in | is | none |
nonlocal | raise | yield | async | await |
There are several reasons to opt for Python when talking about server-side development. To initiate, Python serves up a library of frameworks and tools that easily facilitate the development process. For instance, take Django and Flask. Both of these systems have a significant backend function which is carried out using Python.
To sum up, Python’s features are listed below:
One of the reasons why Python is extensively used in data science and scientific computing is the rich ecosystem that Python has to offer to its users. Its libraries of tools such as SciPy and NumPy make it an ideal place to acquire information and put it to work.
Besides, the libraries offer several functions such as numerical computations, statistical analysis, mathematical operations, and the like. Python’s other libraries like Matplotlib offer a place for data visualization, allowing scientists to carry on their research and present more informed findings.
Here are the features of Python in carrying out scientific computing combined with data science -
As it is an emerging field, Python has been able to provide a balance between machine learning and deep learning using its abilities. In the machine learning domain, Python helps by keeping a watch on data validation, scraping, processing, and management.
Here are the top uses of Python in machine learning -
Python has repeatedly shown its potential by offering a wide range of applications for use in various fields. Due to its extensive support in a simple interface, flexibility, and libraries full of open-source content, it is a brilliant source for developers to get on with their work and research.
Furthermore, Python’s ease of use and readability ensure that it is accessible to both beginners and experts, thereby making it a wholesome community. To top that, its constant evolution in terms of industries makes it a powerful tool to access in the modern landscape. There are several Python programming apps for PCs, as a matter of example.
The three primary Python applications include data science and data analysis, web development, and scripting and automation.
Some of the popular Android apps made with Python’s frameworks for their websites include BitTorrent, Dropbox Paper, NASA, Facebook, and Quora. NASA uses Python’s flexibility to access scientific and computational tasks like simulating space missions and analyzing data. Facebook mainly utilizes Python’s algorithm for data processing and user authentication.
Python provides several benefits including flexibility, scalability, and rapid development to its users. Moreover, Python’s extensive tools and libraries offer the developer the benefit of a well-established community with pre-built functionality within the reach of a hand.
Python’s integrated development environment (IDE) is specifically useful when handling a cloud-based server. As it is a beginner-friendly platform, it provides programmers with the ability to write, manage, and run Python code.
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