9781098104030 - Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter von McKinney, Wes (15 Ergebnisse)

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Zustand: New. &Uumlber den AutorWes McKinney is a Nashville-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 Gre.

Zustand: New. 2022. 3rd ed. Paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Python for Data Analysis | Data Wrangling with Pandas, NumPy, and Jupyter | Wes McKinney | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | O'Reilly Media | EAN 9781098104030 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Neuware -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 examplesLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.

Taschenbuch. Zustand: Neu. Neuware - 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.

Taschenbuch. Zustand: Neu. Neuware -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 Englisch.