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10 Python Libraries Every Developer Should Know

KDnuggets

In this article, we’ll go over Python libraries for tasks like logging, unit testing, data handling, and more — each with features that can simplify your application development.

Python 198
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Mutable vs Immutable Objects in Python

Analytics Vidhya

Introduction Python is an object-oriented programming language (or OOPs). In my previous article, we explored its versatile nature. Due to this, Python offers a wide variety of data types, which can be broadly classified into mutable and immutable types.

Python 258
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How to Create Publication-Ready Figures and Tables with Python?

Analytics Vidhya

Python, with its robust ecosystem of libraries, offers a wide range of tools to help you generate high-quality, aesthetically pleasing, and customizable visuals for your research papers. Creating publication-ready figures and tables is essential for academic research and data presentation. appeared first on Analytics Vidhya.

Python 168
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Palindrome Number in Python

Analytics Vidhya

This article examines several approaches to Python palindrome number checking, from basic text manipulation to more complex recursive algorithms. Furthermore, […] The post Palindrome Number in Python appeared first on Analytics Vidhya.

Python 277
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Pattern Program in Python

Analytics Vidhya

Introduction In this comprehensive guide, we’ll delve into the world of pattern programming using Python, a fundamental exercise for mastering nested loops and output formatting.

Python 262
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Python String Matching With Pregex

Analytics Vidhya

Introduction String matching in Python can be challenging, but Pregex makes it easy with its simple and efficient pattern-matching capabilities. In this article, we will explore how Pregex can help you find patterns in text effortlessly.

Python 284
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Best Python Tricks in Jupyter Notebook

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Introduction Python is a popular programming language for its simplicity and readability. This article discusses Python tricks in Jupyter Notebook to enhance coding experience, productivity, and understanding. When it is combined with Jupyter Notebook, it offers interactive experimentation, documentation of code and data.

Python 295