Top 10 Python Libraries for Data Science in 2024

NumPy

NumPy is the fundamental library for numerical computation in Python. It provides efficient data structures, such as arrays and matrices, and a wide range of functions for numerical operations, such as linear algebra, Fourier transforms, and random number generation.

Pandas

Pandas is a powerful library for data analysis and manipulation. It provides data structures, such as DataFrames and Series, that are designed for working with tabular data. Pandas also provides a wide range of functions for data manipulation, cleaning, and preprocessing.

Matplotlib and Seaborn

Matplotlib is a plotting library that provides a wide range of functions for creating visualizations, such as line charts, bar charts, and histograms. Seaborn is a higher-level library that builds on top of Matplotlib and provides a more user-friendly interface for creating complex visualizations.

scikit-learn

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

TensorFlow and PyTorch

TensorFlow and PyTorch are deep learning libraries that provide a framework for building and training deep learning models. TensorFlow is a more mature library, while PyTorch is a more recent library that is gaining popularity due to its ease of use.

Dask

Dask is a library for parallel and distributed computing in Python. It allows you to scale your computations to multiple cores or machines, which can be useful for working with large datasets.

Statsmodels

Statsmodels is a library for statistical modeling and inference. It provides a wide range of statistical models, such as linear regression, logistic regression, and time series models.

NetworkX

NetworkX is a library for working with networks. It provides data structures and algorithms for creating, manipulating, and analyzing networks.

Beautiful Soup

Beautiful Soup is a library for parsing and extracting data from HTML and XML documents. It is a useful tool for web scraping and data mining.

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