Learn more
Your Memberships & Subscriptions
Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.
Read instantly on your browser with Kindle for Web.
Using your mobile phone camera - scan the code below and download the Kindle app.
Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python 1st Edition, Kindle Edition
Publisher's Note: A new second edition, updated completely for pandas 1.x with additional chapters, has now been published. This edition from 2017 is outdated and is based on pandas 0.20.
Key Features
- Use the power of pandas 0.20 to solve most complex scientific computing problems with ease
- Leverage fast, robust data structures in pandas 0.20 to gain useful insights from your data
- Practical, easy to implement recipes for quick solutions to common problems in data using pandas 0.20
Book Description
This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. 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.
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 like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.
Many advanced recipes combine several different features across the pandas 0.20 library to generate results.
What you will learn
- Master the fundamentals of pandas 0.20 to quickly begin exploring any dataset
- Isolate any subset of data by properly selecting and querying the data
- Split data into independent groups before applying aggregations and transformations to each group
- Restructure data into tidy form to make data analysis and visualization easier
- Prepare real-world messy datasets for machine learning
- Combine and merge data from different sources through pandas SQL-like operations
- Utilize pandas unparalleled time series functionality
- Create beautiful and insightful visualizations through pandas 0.20 direct hooks to Matplotlib and Seaborn
- ISBN-13978-1784393878
- Edition1st
- PublisherPackt Publishing
- Publication dateOctober 23, 2017
- LanguageEnglish
- File size39416 KB
Kindle E-Readers
- Kindle Paperwhite
- Kindle Paperwhite (5th Generation)
- Kindle Touch
- Kindle Voyage
- Kindle
- Kindle Oasis
- All new Kindle paperwhite
- Kindle Oasis (9th Generation)
- All New Kindle E-reader
- Kindle Paperwhite (10th Generation)
- Kindle Paperwhite (11th Generation)
- Kindle Scribe (1st Generation)
- All New Kindle E-reader (11th Generation)
- Kindle (10th Generation)
- Kindle Oasis (10th Generation)
Fire Tablets
There is a newer version of this item:
$39.99
(18)
Available for download now
Customers who read this book also read
From the brand
-
Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.
Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.
We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.
-
New Releases
-
Power BI
-
Machine Learning
-
Deep Learning
-
Causality and XAI
-
Finance and Forecasting
-
See Our Full Range
Editorial Reviews
About the Author
Theodore Petrou is a data scientist and the founder of Dunder Data, a professional educational company focusing on exploratory data analysis. He is also the head of Houston Data Science, a meetup group with more than 2,000 members that has the primary goal of getting local data enthusiasts together in the same room to practice data science. Before founding Dunder Data, Ted was a data scientist at Schlumberger, a large oil services company, where he spent the vast majority of his time exploring data.
Some of his projects included using targeted sentiment analysis to discover the root cause of part failure from engineer text, developing customized client/server dashboarding applications, and real-time web services to avoid the mispricing of sales items. Ted received his masters degree in statistics from Rice University, and used his analytical skills to play poker professionally and teach math before becoming a data scientist. Ted is a strong supporter of learning through practice and can often be found answering questions about pandas on Stack Overflow.
Product details
- ASIN : B06W2LXLQK
- Publisher : Packt Publishing; 1st edition (October 23, 2017)
- Publication date : October 23, 2017
- Language : English
- File size : 39416 KB
- Text-to-Speech : Enabled
- Screen Reader : Supported
- Enhanced typesetting : Enabled
- X-Ray : Not Enabled
- Word Wise : Not Enabled
- Print length : 534 pages
- Best Sellers Rank: #1,770,003 in Kindle Store (See Top 100 in Kindle Store)
- #266 in Mathematical & Statistical
- #719 in Mathematical & Statistical Software
- #1,261 in Python Computer Programming
- Customer Reviews:
About the author
My goal as teacher and author is to provide a comprehensive path to mastering the python data science ecosystem so that you can feel confident to produce trusted results. I am the author of the highly rated texts Pandas Cookbook, Master Data Analysis with Python, and Build an Interactive Data Analytics Dashboard with Python. Ted has taught hundreds of students Python and data science during in-person classroom settings. He sees first hand exactly where students struggle and continually upgrades his material to minimize these struggles by providing simple and direct paths forward.
Ted is one of the foremost authorities on using the pandas library to do data analysis. His blog posts have totaled well over 2 million views. He is also a prolific contributor on Stack Overflow having answered over 400 questions.
Ted holds a master's degree in statistics from Rice University and is the founder of Dunder Data (www.dunderdata.com).
Customer reviews
Customer Reviews, including Product Star Ratings help customers to learn more about the product and decide whether it is the right product for them.
To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. It also analyzed reviews to verify trustworthiness.
Learn more how customers reviews work on AmazonTop reviews from the United States
There was a problem filtering reviews right now. Please try again later.
- Reviewed in the United States on October 18, 2024I enjoyed the book and it provided a nice overview of both the Pandas and concept of data frames
- Reviewed in the United States on November 9, 2018This book is over 500 pages, but the layout is outstanding.
I am the type of person to read 1-3 page of a book each day at least.
The book has chapters, topics, and subsections.
Each subsection is organized the same throughout the ENTIRE book...
Chater 1...
Topic 1
1. Getting ready
2. How to do it.
3. How it works...
4. There's more...
5. See also
Topic 2
1. Getting ready
2. How to do it.
3. How it works...
4. There's more...
5. See also.
etc.
Meaning, that you can pick up from anywhere and learn a little piece at a time with a consistent layout for each topic.
I HIGHLY recommend this book, not because it's easy, but it streamlines the information for you in a consistent manner. You can make a "class" or "course" based on one subsection at a time and do it consisitently, developing your skils. Because we ALL understand simple things get done and consistent actions produce the results in our lives.
Much luck in your decision to purchase this book for yourself. ^__^
- Reviewed in the United States on February 24, 2019I should’ve started with this book. The examples are concise and helpful. If you’re already familiar with Python and just want to get a better understanding of how to manipulate your data with Pandas- this is an excellent resource.
With so many tools and resources out there for data analysis, it’s hard to find something this detailed on just the Pandas library. The book goes beyond the Pandas documentation and provides tips for best practices and links to external resources if you want to dig deeper into a specific topic.
- Reviewed in the United States on March 23, 2018Splitting this review into two parts: 5 for Petrou's content in the recipes themselves, 1 for Packt publisher's cookbook format which severely cripples the content with its lack of relevant indexing & labeling. Packt seems obsessed with cut/paste of non-value-added structure titles (Getting Ready, How to do It, How it works, There's more, See also). Those 5 phases are repeated 98 times in the Table of contents (blowing it up to 15 pages instead of concise 3). The skimpy index adds little value to find the relevant sections, unlike any well designed cookbook. Scanning the book is frustrating because the 98 repetitions of the structure headings are bigger and bolder than any other content. I've actually had to take the time to pencil in useful headings on the top-right corner of the pages and essentially create my own index so I can find what I need. I spent the time because the examples were useful and relevant -- if I could only find them when I need them...
- Reviewed in the United States on January 29, 2019This book has helped me out a lot. I am new to python and pandas but this book has made things much clearer. Good explanations with example of codes. Author also explains how each part of the code works and reinforces material learned in previous chapters. Was intimidated by some of the chapters before i started reading once i got to those parts I was no longer worried if i would understand the subject matter.
- Reviewed in the United States on December 12, 2018This is an excellent book if you want to learn pandas and if you want to understand pandas. It covers all cases, clearly explains what and why pandas do, and the chapters are organized really well and it depends on you if you just want to stay on surface or go deeper.
- Reviewed in the United States on April 11, 2019On Kindle Cloud reader with Firefox (latest), after the first 170 pages, the formatting becomes narrower with each page. Eventually it shows one character per line in a single column. I'm sure Amazon, Firefox, and Packt will put the blame on each other. Packt also disallows downloading the book, so I can't try other options for viewing. Bottom line is I paid for something I can't read.
- Reviewed in the United States on May 24, 2019I wish I could have thumbed through this book before I bought it, but alas the bookstores in my area don't carry many computer books, and few on Pandas. I found this book to be silly in its layout, with the structure of each chapter repeating Getting Ready, How to Do It, How it works, and There's More. The text ends up being needlessly wordy without adding a lot of information. And the index is a mere four pages, so if you don't remember exactly where you read something then you have to thumb through it page by page. I got past about page 100 doing the examples and then quit... I just wasn't learning that much. I now use the Pandas cheat sheets for most tasks and the online reference for details. I think there's still a crying need for a beginners-level Pandas reference text, but this isn't it.
Top reviews from other countries
- Cedric MaltaisReviewed in Canada on February 13, 2020
5.0 out of 5 stars Great book !
Great book ! help me a lot
- bluemarlinReviewed in the United Kingdom on March 10, 2019
2.0 out of 5 stars ok
mainly a rehash of material generally available
One person found this helpfulReport - maroofReviewed in India on November 5, 2018
5.0 out of 5 stars Mustbuy
Best forbeginers
- Arpan SenguptaReviewed in India on June 1, 2019
3.0 out of 5 stars A good book, but not a better one
First of all I hate the binding of this book. The pages just jumps to close the book due to this third rate binding.
Anyways, the book covers lot of concepts and that is why 3 stars. Where the book fails is even after finishing the book you don't feel like you have developed an expertise on Pandas. The author uses so many methods suddenly that it is upto the reader to cram something at each step. A good approach would be to first explain functions and process and then using those methods to solve complex problems. Sudden appearance of unknown methods does not help at all.
Also sometimes the author present simple things in an extremely complex manner.I really don't understand the need of that. Also the datasets are extremely complex many a times and are difficult to obtain over net.
Overall, I learnt many things but I need to revise this once and then go through some online course to claim expertise in Pandas.
- RaphaelReviewed in Canada on April 16, 2018
4.0 out of 5 stars Four Stars
Its a good book. But I could not find a link to the data sets he used. Any pointers?