The Python Data Science Handbook provides a reference to the breadth of computational and statistical methods that are central to data-intensive science, research, and discovery. People with a programming background who want to use Python effectively for data science tasks will learn how to face a variety of problems: e.g., how can I read this data format into my script? How can I manipulate, transform, and clean this data? How can I visualize this type of data? How can I use this data to gain insight, answer questions, or to build statistical or machine learning models?
This book is a reference for day-to-day Python-enabled data science, covering both the computational and statistical skills necessary to effectively work with . The discussion is augmented with frequent example applications, showing how the wide breadth of open source Python tools can be used together to analyze, manipulate, visualize, and learn from data.
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Jake VanderPlas is a long-time user and developer of the Python scientific stack. He currently works as an interdisciplinary research director at the University of Washington, conducts his own astronomy research, and spends time advising and consulting with local scientists from a wide range of fields.
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Da: Regno Unito a: U.S.A.
Descrizione libro O'Reilly Media, Inc, USA, United States, 2016. Paperback. Condizione: New. Language: English. Brand new Book. For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you'll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms. Codice articolo BTA9781491912058
Descrizione libro Oand#8242;Reilly, 2016. PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo WO-9781491912058
Descrizione libro O'Reilly Media, 2016. Paperback. Condizione: New. Codice articolo 24304543-n
Descrizione libro O'Reilly Media, Inc, USA, United States, 2016. Paperback. Condizione: New. Language: English. Brand new Book. For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all-IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you'll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms. Codice articolo BTA9781491912058
Descrizione libro Condizione: New. Codice articolo 24304543-n
Descrizione libro O'Reilly Media, 2016. Paperback. Condizione: new. Codice articolo 9781491912058
Descrizione libro O'Reilly Media, 2016. Paperback. Condizione: New. Paperback. For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces o.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 500 pages. 0.666. Codice articolo 9781491912058
Descrizione libro O'Reilly Media, 2016. Condizione: New. A+ Customer service! Satisfaction Guaranteed! Book is in NEW condition. Codice articolo 1491912057-2-1
Descrizione libro O'Reilly Media, 2016. Paperback. Condizione: New. Codice articolo DADAX1491912057
Descrizione libro O'Reilly Media, 2016. Condizione: new. 1. Book is in NEW condition. Satisfaction Guaranteed! Fast Customer Service!!. Codice articolo MBSN1491912057