Python for Data Analysis : Data Wrangling with Pandas, NumPy, and Jupyter by Wes
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Python for Data Analysis : Data Wrangling with Pandas, NumPy, and Jupyter by Wes
US $26.39
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Located in: Pollock, Louisiana, United States
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Item specifics
- Condition
- ISBN
- 9781098104030
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
Publication Year
2022
Subject
Data Visualization, Data Processing, Databases / Data Mining, Programming Languages / Python
Type
Textbook
Subject Area
Computers
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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Verified purchase: YesCondition: NewSold by: mimcna-39