Python for data analysis : data wrangling with pandas, NumPy, and IPython / Wes McKinney.Publisher: Sebastopol, CA : O'Reilly Media, Inc., October 2018Copyright date: ©2018Edition: Second edition (2018).Description: xvi, 524 pages : illustrations ; 24 cm.Content type: text | still image Media type: unmediated Carrier type: volumeISBN: 1491957662; 9781491957660.Other title: Data wrangling with pandas, NumPy, and IPython.Subject(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 LOC classification: QA76.73.P98 | M42 2018
|Item type||Current location||Call number||Copy number||Status||Date due||Barcode||Item holds|
|BOOK||NCAR Library Mesa Lab||QA76.73 .P98 M42 2018||1||Checked out||10/01/2021||50583020007955|
|BOOK||NCAR Library Foothills Lab||QA76.73.P98 M42 2018||2||Checked out||10/01/2021||50583020010041|
"Revision history for the Second Edition: 2017-09-25: First Release"--Title page verso.
First edition: October 2012.
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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|Python for data analysis / by McKinney, Wes. ©2013|