Python for data analysis : data wrangling with pandas, NumPy, and Jupyter / Wes McKinney.

By:

McKinney, Wes [author]

Material type:

text
still image

Media type:

unmediated

Carrier type:

volume

ISBN:

9781098104030
109810403X

Subject(s):

DDC classification:

006.312 MCK 23

LOC classification:

QA76.73.P98 M42 2022

Contents:

Preliminaries -- Python language basics IPython, and Jupyter notebooks -- Built-in data structures, functions, and files -- NumPy basics: arrays and vectorized computation -- Getting started with pandas -- Data loading, storage, and file formats -- Data cleaing and preparation -- Data wrangling: join, combine, reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Introduction to modeling libraries in Python -- Data analysis examples -- Advanced NumPy -- More on the IPython system.

Summary: "Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, 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. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing." -- Provided by publisher

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Books	CamTech Library			General Collections	006..312 MCK (Browse shelf(Opens below))				C.1	Available			0000003105

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Previous edition: 2017.

Includes index.

Includes bibliographical references and index.

"Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, 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. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing." -- Provided by publisher

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