Python for data analysis : data wrangling with pandas, NumPy, and IPython
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TextPublication details: Sebastopol, CA : O'Reilly Media, Inc., 2018. ©2018Edition: Second editionDescription: xvi, 524 pages : illustrationsISBN: 1491957662; 9781491957660Subject(s): Python (Computer program language) | Programming languages (Electronic computers) | Data mining | Programming languages (Electronic computers) | Data mining | Python (Computer program language) | Python 3.6 | Datenanalyse | Datenmanagement | Data MiningDDC classification: 005.133 | Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Reference Books
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Main Library Reference | Reference | 005.133 MAC (Browse shelf(Opens below)) | Available | 015799 |
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| 005.133 LIS Beginning J2ME : from novice to professional | 005.133 LOU Programming languages: principles and practices | 005.133 MAC Programming in Visual Basic | 005.133 MAC Python for data analysis : data wrangling with pandas, NumPy, and IPython | 005.133 MAL C++ Programming: From Problem Analysis to Program Design | 005.133 MAL C++ programming: Form Problem Analysis to Program Design | 005.133 MAL C++ programming : |
"Revision history for the Second Edition: 2017-09-25: First Release"--Title page verso.
First edition: October 2012.
Includes index.
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 cleaning and preparation -- Data wrangling: join, combine, and reshape -- Plotting and visualization -- Data aggregation and group operations -- Time series -- Advanced pandas -- Introduction to modeling libraies in Python -- Data analysis examples -- Advanced NumPy -- More on the IPython system.
"Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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, IPython, and Jupyter in the process"--Page 4 of cover.
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