Python for Data Analysis: Data Wrangling - Paperback, by McKinney Wes - Good

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Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
Book Title
Python for Data Analysis: Data Wrangling with pandas, NumPy, and
ISBN
9781098104030
Category

About this product

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
109810403X
ISBN-13
9781098104030
eBay Product ID (ePID)
14057247928

Product Key Features

Number of Pages
579 Pages
Language
English
Publication Name
Python for Data Analysis : Data Wrangling with Pandas, Numpy, and Jupyter
Subject
Data Visualization, Data Processing, Databases / Data Mining, Programming Languages / Python
Publication Year
2022
Type
Textbook
Subject Area
Computers
Author
Wes Mckinney
Format
Trade Paperback

Dimensions

Item Height
1.2 in
Item Weight
35.3 Oz
Item Length
9.2 in
Item Width
7.2 in

Additional Product Features

Edition Number
3
LCCN
2023-549174
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.312
Synopsis
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, 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. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the Jupyter notebook and IPython shell for exploratory computing Learn basic and advanced features in NumPy Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
LC Classification Number
QA76.73.P98M42 2022

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