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Python Data Science Handbook: Essential Tools for Working with Data

Python Data Science Handbook: Essential Tools for Working with Data

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

Pages : 548 pages
File type : pdf
Downloads: 107
Submitted On: 2020-08-30
License: Text Content: CC-BY-NC-ND; Source Code: MIT License
Author(s): Jake VanderPlas

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This tutorial has been prepared for the beginners to help them understand basic Python Programming. After completing this tutorial you will find yourself at a moderate level of expertise in Python from where you can take yourself to next levels.

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