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Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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, IPython, 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 IPython shell and Jupyter notebook for exploratory computing
- Learn basic and advanced features in NumPy (Numerical Python)
- 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
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Informazioni sull?autore
Wes McKinney is a New York?based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and started building what would later become the pandas project. He's now an active member of the Python data community and is an advocate for the use of Python in data analysis, finance, and statistical computing applications.
Wes was later the co-founder and CEO of DataPad, whose technology assets and team were acquired by Cloudera in 2014. He has since become involved in big data technology, joining the Project Management Committees for the Apache Arrow and Apache Parquet projects in the Apache Software Foundation. In 2016, he joined Two Sigma Investments in New York City, where he continues working to make data analysis faster and easier through open source software.
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Python for Data Analysis : Data Wrangling with Pandas, NumPy, and IPython
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Second edition of the classic Python for data analysis. Condition: New Master the tools and techniques required to effectively manipulate, clean, and process data using Python. Authored by Wes McKinney, the creator of the pandas library, this essential guide is the canonical resource for analysts, data scientists, and anyone looking to leverage Python for practical data wrangling. This fully updated second edition features: Comprehensive Coverage: Get up to speed with the latest versions of pandas, NumPy, and IPython. Data-Centric Focus: Learn robust techniques for loading, transforming, merging, and reshaping data sets?the critical tasks that form the foundation of any data project. Real-World Examples: Apply your skills immediately with clear, practical examples across various domains, including time series analysis and data aggregation. If you want to become proficient in using Python's powerful ecosystem for exploratory data analysis (EDA), this book is your indispensable desk reference. Codice articolo ABE-1760019698156
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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ISBN 10: 1491957662
ISBN 13: 9781491957660
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