. Data Science & Machine Learning
NumPy:
Fundamental package for numerical computing and array manipulation.
Pandas:
High-level data structures and data analysis tools for tabular data.
SciPy:
Ecosystem of packages for scientific computing and technical computations.
scikit-learn:
Comprehensive machine learning library with tools for classification, regression, clustering, and more.
TensorFlow:
End-to-end open-source platform for deep learning and neural networks.
PyTorch:
Deep learning framework that offers dynamic computational graphs and a flexible interface.
Keras:
High-level neural networks API that runs on top of TensorFlow or other backends.
Statsmodels:
Provides classes and functions for the estimation of many different statistical models.
XGBoost / LightGBM / CatBoost:
Gradient boosting libraries that offer high performance for predictive modeling.
Matplotlib:
Comprehensive 2D plotting library for creating static, interactive, and animated visualizations.
Seaborn:
Statistical data visualization built on top of Matplotlib with attractive and informative graphics.
Plotly:
Interactive plotting library that can produce web-based dashboards and complex visualizations.
Bokeh:
Provides elegant, concise construction of versatile graphics with high-performance interactivity.
Altair:
Declarative statistical visualization library for quickly generating charts.
Django:
High-level framework that encourages rapid development and clean, pragmatic design for full-stack web applications.
Flask:
Lightweight microframework that is easy to extend and ideal for small to medium-sized projects or APIs.
FastAPI:
Modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard type hints.
Pyramid:
Flexible web framework that scales from simple to complex applications.
NLTK (Natural Language Toolkit):
Comprehensive suite for processing human language data.
spaCy:
Industrial-strength NLP library for tasks such as tokenization, parsing, and named entity recognition.
Gensim:
Library for topic modeling and document similarity analysis using vector space modeling.
TextBlob:
Simplified text processing library for common NLP tasks like sentiment analysis and translation.
BeautifulSoup:
Library for parsing HTML and XML documents, useful for web scraping.
Scrapy:
Powerful framework for extracting data from websites, handling requests, and managing crawling.
Selenium:
Browser automation tool that is often used for testing web applications and scraping dynamic content.
Requests:
Simple and elegant HTTP library for making web requests.
MechanicalSoup:
Combines BeautifulSoup and Requests to simulate a web browser for simple automation tasks.
5. GUI Development
Tkinter:
Standard GUI toolkit for Python that comes bundled with most Python installations.
PyQt / PySide:
Set of Python bindings for the Qt application framework, enabling cross-platform GUI development.
Kivy:
Open-source Python library for developing multitouch applications and cross-platform GUI apps.
wxPython:
Cross-platform GUI toolkit that enables the creation of native user interfaces.
SymPy:
Python library for symbolic mathematics, including algebra, calculus, and equation solving.
Biopython:
Tools for computational biology and bioinformatics, enabling analysis of biological data.
Astropy:
Library for astronomy and astrophysics, designed to handle coordinate transformations, time conversions, and more.
