TensorFlow is a high-performance numerical computation library with approximately 35,000 comments and a vibrant community of approximately 1,500 contributors.
SciPy (Scientific Python) is yet another free and open-source Python data science library that is widely used for high-level computations.
It is a general-purpose array-processing package that provides high-performance multidimensional objects known as arrays, as well as tools for working with them.
It is heavily used for data analysis and cleaning, with approximately 17,00 comments on GitHub and an active community of 1,200 contributors.
It's a Python plotting library with over 26,000 comments on GitHub and a thriving community of over 700 contributors.
Keras, like TensorFlow, is a popular library that is widely used for deep learning and neural network modules.
Scikit-learn, a machine learning library that provides almost all of the machine learning algorithms you might need, is next on the list of the best Python libraries for data science.
PyTorch, a Python-based scientific computing package that makes use of the power of graphics processing units, comes next on the list of top python libraries for data science.
Scrapy is the next well-known Python library for data science. Scrapy is one of the most popular, fast, open-source Python web crawling frameworks.
Users can scrape data from websites that lack a proper CSV or API, and BeautifulSoup can assist them in arranging it into the required format.