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Python for data analysis

by Wes McKinney | 03 November 2017
Synopsis
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 computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
€67.19
201 Reward Points
In stock online
Delivery 5-7 Days
Eligible for free delivery

Any purchases for more than €10 are eligible for free delivery anywhere in the UK or Ireland!

Synopsis
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 computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples
Quantity
Quantity
€67.19
201 Reward Points
In stock online
Delivery 5-7 Days
Eligible for free delivery

Any purchases for more than €10 are eligible for free delivery anywhere in the UK or Ireland!

Quantity
Quantity

Product Details

ISBN - 9781491957660
Format -
Publisher -
Published - 03/11/2017
Categories - All, Books, Business Computers, Computers, Graphical and Media Applications
No. of Pages - 550
Weight - 822
Edition - Second edition
Series - - Not Available
Page Size - 24
Language - en-US
Readership Age - Not Available
Table of Contents - Not Available

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