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Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter

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Marque : GENERIC
Vendu par HEAVENBOOKS.MA

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, ...

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Description produit

Marque
GENERIC
Titre
Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter
Éditeur
O'Reilly Media
Type de produit
paperback
Présentation du livre
paperback
Date de sortie
9/20/2022 12:00:00 AM
Langue d'origine
English
ISBN
474349314
Dimensions
7 x 1.5 x 9 inches
Nombre de pages
579 pages
Langue
English
Résumé
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 Read more
Auteur
Wes McKinney
Date de parution
9/20/2022 12:00:00 AM