| Book Name: | [PDF] Python Data Science Handbook |
| Category: | Python Programming |
| Language: | English |
| Format: | |
| Free Download: | Available |
Free Download O’Reilly® Python Data Science Handbook: Essential Tools for Working with Data PDF Book
About the book
Python is a great tool for many experts, mostly because it has tools for saving, manipulating, and getting information from data. There are different resources for each part of this data science stack, but the Python Data Science Handbook is the only place you can find them all. This includes IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other tools.
Scientists and data crunchers who know how to read and write Python code will find this comprehensive desk reference very useful for day-to-day tasks like manipulating, transforming, and cleaning data, visualizing different types of data, and using data to build statistical or machine learning models. Simply put, this is the book you must have if you want to use Python for science computing.
IPython and Jupyter provide computational environments for data scientists who use Python. NumPy has the ndarray for efficiently storing and manipulating dense data arrays in Python. Pandas has the DataFrame for efficient Python storage and manipulation of labeled/columnar data. Matplotlib has tools for a wide range of data visualizations in Python.
Use statistical reasoning to find answers to real-world questions
Who Wrote What?
Jake VanderPlas has used and built on the Python science stack for a long time. He works as an interdisciplinary research director at the University of Washington, does his own research in astronomy, and spends time coaching and speaking with local scientists from a wide range of fields.
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