Subtitled" Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python", this new updated and revised edition covering Pandas 1.x provides recipes for both fundamental and advanced data manipulation tasks with pandas. Authors Matt Harrison and Theodore Petrou have included some recipes aimed at achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes dive deep into a particular dataset, and many advanced recipes combine several different features across the pandas library to generate results.

<ASIN:1839213108>

Author: Matt Harrison and Theodore Petrou
Publisher: Packt Publishing
Date: February 2020
Pages: 626
ISBN: 978-1839213106
Print: 1839213108
Kindle:  B0851DDM7D
Audience: Python developers interested in pandas
Level: Intermediate
Category: Python

• Master data exploration in pandas through dozens of practice problems
• Group, aggregate, transform, reshape, and filter data
• Merge data from different sources through pandas SQL-like operations
• Create visualizations via pandas hooks to matplotlib and seaborn
• Use pandas, time series functionality to perform powerful analyses
• Import, clean, and prepare real-world datasets for machine learning
• Create workflows for processing big data that doesn't fit in memory

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