Python for data analysis : data wrangling with pandas, NumPy, and Jupyter
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Bibliographic Information
Python for data analysis : data wrangling with pandas, NumPy, and Jupyter
O'Reilly Media, c2022
3rd ed
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Python for data analysis : data wrangling with pandas, NumPy & Jupyter
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"Revision history for the Third Edition: 2022-08-12: First Release"--T.p. verso
First edition: October 2012
Includes index
Description and Table of Contents
Description
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
Use the Jupyter notebook and IPython shell for exploratory computing
Learn basic and advanced features in NumPy
Get started with data analysis tools in the pandas library
Use flexible tools to load, clean, transform, merge, and reshape data
Create informative visualizations with matplotlib
Apply the pandas groupby facility to slice, dice, and summarize datasets
Analyze and manipulate regular and irregular time series data
Learn how to solve real-world data analysis problems with thorough, detailed examples
by "Nielsen BookData"