Isbn: 9781098121228 - python data science handbook: essential tools for working with data (18 Ergebnisse)

Paperback. Zustand: Fair. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of 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. …

Paperback. Zustand: Good. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of 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. …

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Softcover. Zustand: As New. Leichte Kratzer / Abnutzungen / Druckstellen. Python is a first-class tool for many researchers, primarily 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 new edition of 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 the second edition of 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: IPython and Jupyter provide computational environments for scientists using Python NumPy includes the ndarray for efficient storage and manipulation of dense data arrays Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data Matplotlib includes capabilities for a flexible range of data visualizations Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms.…

Zustand: New. In English.

Paperback. Zustand: Brand New. 2nd edition. 550 pages. 9.19x7.00x1.19 inches. In Stock.

Zustand: NEW.

Zustand: New. &Uumlber den AutorJake VanderPlas is a software engineer at Google Research, working on tools that support data-intensive research. He creates and develops Python tools for use in data-intensive science, including packages like Scikit-L.

Zustand: New. 2022. 2nd Edition. Paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Neuware - Python is a first-class tool for many researchers, primarily 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 new edition of 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 the second edition of 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: - IPython and Jupyter provide computational environments for scientists using Python - NumPy includes the ndarray for efficient storage and manipulation of dense data arrays - Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data - Matplotlib includes capabilities for a flexible range of data visualizations - Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms.…

paperback. Zustand: New.

Taschenbuch. Zustand: Neu. Python Data Science Handbook | Essential Tools for Working with Data | Jake Vanderplas | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | O'Reilly Media | EAN 9781098121228 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Neuware -Python is a first-class tool for many researchers, primarily 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 new edition of 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 the second edition of 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: - IPython and Jupyter provide computational environments for scientists using Python - NumPy includes the ndarray for efficient storage and manipulation of dense data arrays - Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data - Matplotlib includes capabilities for a flexible range of data visualizations - Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithmsLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.…

Taschenbuch. Zustand: Neu. Neuware -Python is a first-class tool for many researchers, primarily 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 new edition of 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 the second edition of 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: - IPython and Jupyter provide computational environments for scientists using Python - NumPy includes the ndarray for efficient storage and manipulation of dense data arrays - Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data - Matplotlib includes capabilities for a flexible range of data visualizations - Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms Englisch.…

Zustand: gut. 2023. Python Data Science Handbook: Essential Tools for Working with Data, Second Edition In englischer Sprache. pages.