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Python for data analysis 2e data wrangling with pandas numpy and ipython


Foto: Python for data analysis 2e data wrangling with pandas numpy and ipython
Rubriek: Textual/Printed/Reference Materials - Boek
Prijs: 45.9 Nu voor: 43.9
Rating: 4.5/5
Verzending:
Uiterlijk 2 december in huis


Inhoudsopgave:

Omschrijving:

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. 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 IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) 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



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Product specificaties:

Taal: en

Bindwijze: Paperback

Oorspronkelijke releasedatum: 21 oktober 2017

Aantal pagina's: 550

Illustraties: Nee

Hoofdauteur: Wes Mckinney

Hoofduitgeverij: Oreilly & Associates Inc

AI-gegenereerd: Nee

Dyslexievriendelijk: Nee

Editie: 2nd New edition

Extra groot lettertype: Nee

Product breedte: 178 mm

Product hoogte: 20 mm

Product lengte: 228 mm

Studieboek: Ja

Verpakking breedte: 179 mm

Verpakking hoogte: 30 mm

Verpakking lengte: 240 mm

Verpakkingsgewicht: 908 g

eWaste: Nee

EAN: 9781491957660