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Pandas 1.x Cookbook
Pandas 1.x Cookbook

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python , Second Edition

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Profile Icon Matthew Harrison Profile Icon Theodore Petrou
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (28 Ratings)
Paperback Feb 2020 626 pages 2nd Edition
eBook
$63.99
Paperback
$79.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Matthew Harrison Profile Icon Theodore Petrou
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5 (28 Ratings)
Paperback Feb 2020 626 pages 2nd Edition
eBook
$63.99
Paperback
$79.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$63.99
Paperback
$79.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • This is the first book on pandas 1.x
  • Practical, easy to implement recipes for quick solutions to common problems in data using pandas
  • Master the fundamentals of pandas to quickly begin exploring any dataset

Description

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.

Who is this book for?

This book is for Python developers, data scientists, engineers, and analysts. Pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandas.

What you will learn

  • Master data exploration in pandas through dozens of practice problems
  • Group, aggregate, transform, reshape, and filter data
  • Merge data from different sources through pandas SQL-like operations
  • Create visualizations via pandas hooks to matplotlib and seaborn
  • Use pandas, time series functionality to perform powerful analyses
  • Import, clean, and prepare real-world datasets for machine learning
  • Create workflows for processing big data that doesn't fit in memory

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 27, 2020
Length: 626 pages
Edition : 2nd
Language : English
ISBN-13 : 9781839213106
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Product Details

Publication date : Feb 27, 2020
Length: 626 pages
Edition : 2nd
Language : English
ISBN-13 : 9781839213106
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(28 Ratings)
5 star 75%
4 star 7.1%
3 star 7.1%
2 star 10.7%
1 star 0%
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Michael Oct 01, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Libro imprescindible si usas Pandas. Es un libro que me ha resuelto muchos quebraderos de cabeza, llevo usando Pandas varios años y tras leer el libro he dado un paso gigante en el uso de la librería y en las posibilidades que ofrece.Tras leer el libro me puse a indagar un poco más sobre los trabajos de Ted Petrou y su plataforma en Dunderdata (punto com) es totalmente recomendable para poder seguir aprendiendo sobre Data Science, ML, dashboards, etc. con información actualizada que conviene echarle un vistazo si estás interesado en este campo.
Amazon Verified review Amazon
jldo38 Jan 09, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
REFERENCE Tres complete en la matiere. Vaut son prix.
Amazon Verified review Amazon
TR Jul 08, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent structure of topics, complimented with simplified explanations. I'm able to grasp the concepts quickly in a short amount of time (compared to popular Udemy courses, Datacamp, and even Wes McKinney's book!). Many thanks to the authors for creating such a wonderful comprehensive learning guide and giving me the much-needed confidence to work with Pandas on my own. Also, a side note: If you don't own a Kindle/e-book reader, do consider purchasing the hardcopy version, if you can. The book is 600+ pages long and studying from a laptop/desktop isn't a very effective approach! Personally, I feel a hardcopy book always works wonders for retention...happy learning! :-)
Amazon Verified review Amazon
Ezam Mar 07, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is gold if you are trying to learn a new skill or improve basic Python/Pandas skills. I had been looking into multiple books options but this one by far was the best when I read the sample and now that I have the physical book I am really glad I got it
Amazon Verified review Amazon
Peter & Yubia Wilkinson Apr 01, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book as it is a practical how-to that focuses on the different stages of data processing using data frames in Python. The working examples begin with the basics reading in data into python, running row and column operations and transformations, exploring and cleaning process, subsetting, summarizing and finally creating visuals. I do like the numbers visual outputs, and I like the fact that this is a cookbook focus' data manipulation rather than trying also step into modeling as well. There are many nice worked examples, and a good chapter on creating visuals. They chose to have a chapter on Time Series analysis to highlight pandas Timestamp object. This book covers everything you need for data exploration and manipulation with pandas.
Amazon Verified review Amazon
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