Python for Data Analysis 3e
Data Wrangling with pandas, NumPy, and Jupyter
Seiten
2022
|
3rd edition
O'Reilly Media (Verlag)
978-1-0981-0403-0 (ISBN)
O'Reilly Media (Verlag)
978-1-0981-0403-0 (ISBN)
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
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
Wes McKinney is an open source software developer focusing on data analysis tools. He created the Python pandas project and is a co-creator of Apache Arrow, his current development focus. He authored 2 editions of the reference book Python for Data Analysis. Wes is a Member of The Apache Software Foundation and also a PMC member for Apache Parquet. He is the director of Ursa Labs, an not-for-profit development group focused on data science tools for Python and R powered by Apache Arrow, built in partnership with RStudio. Previously, he worked for Two Sigma, Cloudera, and AQR Capital Management, and he was co-founder and CEO of the startup DataPad.
Erscheinungsdatum | 23.08.2022 |
---|---|
Verlagsort | Sebastopol |
Sprache | englisch |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge | |
ISBN-10 | 1-0981-0403-X / 109810403X |
ISBN-13 | 978-1-0981-0403-0 / 9781098104030 |
Zustand | Neuware |
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