Top 10 Python Libraries For Data Science for 2022

Top 10 Python Libraries For Data Science for 2022

NumPy

The essential Python module for numerical calculation is called NumPy (Numerical Python), 

Pandas

Pandas

It is widely used for data analysis and cleansing, with almost 17,00 comments on GitHub and an active community of 1,200 contributors. 

TensorFlow

TensorFlow is a library for high-performance numerical computations with around 35,000 comments and a vibrant community of around 1,500 contributors

Matplotlib

Matplotlib

Matplotlib offers robust yet gorgeous visualisations. It's a fairly active community of over 700 contributors and a Python charting library with about 26,000 comments on GitHub.

SciPy

With around 17,00 comments on GitHub and an active community of 1,200 contributors, it is heavily used for data analysis and cleaningAnother free and open-source Python library for data science that is widely used for complex computations is SciPy (Scientific Python). 

Keras

Keras

Large prelabeled datasets are offered by Keras and may be easily imported and loaded. It includes several layers and parameters that have been developed and may be used to build, configure, train, and evaluate neural networks.

Scikit-learn

Scikit-learn, a machine learning library that offers practically all the machine learning algorithms you would require, is one of the data science libraries for Python. NumPy and SciPy can interpolate Scikit-learn data.

PyTorch

One of the most popular deep learning research platforms is PyTorch, which was designed to offer the most flexibility and speed.

Scrapy

Scrapy

One of the most well-liked, quick, open-source Python web crawling frameworks is called Scrapy. Using selectors based on XPath, it is frequently used to extract data from web pages.

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