$43.99 sale price when purchased online
$79.99 list price
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About this item
Highlights
- Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.
- Author(s): Wes McKinney
- 579 Pages
- Computers + Internet, Databases
Description
Book 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
Dimensions (Overall): 6.9 Inches (H) x 9.1 Inches (W) x 1.2 Inches (D)
Weight: 2.07 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 579
Genre: Computers + Internet
Sub-Genre: Databases
Publisher: O'Reilly Media
Format: Paperback
Author: Wes McKinney
Language: English
Street Date: September 20, 2022
TCIN: 86086263
UPC: 9781098104030
Item Number (DPCI): 247-17-2462
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 1.2 inches length x 9.1 inches width x 6.9 inches height
Estimated ship weight: 2.07 pounds
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