Top 15 Python Libraries for data science in 2024

NumPy: NumPy is a fundamental library for numerical computing in Python. It provides efficient data structures, such as arrays and matrices, for manipulating and analyzing large datasets.

Pandas: Pandas is a powerful data analysis and manipulation library built on NumPy. It provides a comprehensive set of tools for data cleaning, preprocessing, and exploration, making it an essential tool for data scientists.

Matplotlib: Matplotlib is a plotting library that creates static and interactive visualizations of data. It offers a wide range of plotting functionalities, from basic line charts to complex histograms and scatter plots.

Seaborn: Seaborn is a statistical data visualization library built on top of Matplotlib. It provides a higher-level abstraction for creating aesthetically pleasing and informative visualizations with minimal code.

Scikit-learn: Scikit-learn is a machine learning library that provides a wide range of algorithms for supervised and unsupervised learning tasks. It includes classification, regression, clustering, and dimensionality reduction algorithms.

TensorFlow: TensorFlow is an open-source machine learning library for building and deploying artificial intelligence models. It is popular for its flexibility and scalability, making it suitable for deep learning applications.

PyTorch: PyTorch is another open-source machine learning library similar to TensorFlow. It is known for its dynamic computational graph and ease of use, making it a popular choice for research and development.

Keras: Keras is a high-level neural network library that simplifies the process of building and training deep learning models. It provides a user-friendly API and integrates seamlessly with TensorFlow and PyTorch.

Statsmodels: Statsmodels is a statistical modeling library that provides a comprehensive set of statistical functions and tools for building and evaluating statistical models. It is widely used in econometrics and social sciences.

Scikit-image: Scikit-image is a library for image processing and analysis. It provides algorithms for image filtering, segmentation, feature extraction, and morphology.

Plotly: Plotly is an interactive visualization library that creates data visualizations for web browsers. It offers a wide range of interactive chart types and supports various data formats.

Bokeh: Bokeh is another interactive visualization library that creates rich and flexible data visualizations. It is known for its declarative syntax and integration with web frameworks.

NetworkX: NetworkX is a library for network analysis and manipulation. It provides algorithms for network modeling, graph exploration, and community detection.

Beautiful Soup: Beautiful Soup is a web scraping library that parses HTML and extracts data from web pages. It is a valuable tool for collecting data from the web for various data science tasks.

PyPDF2: PyPDF2 is a library for manipulating PDF files. It allows you to read, modify, and create PDF documents, making it useful for data extraction and document processing.