Download Pandas for Everyone: Python Data Analysis: Python Data Analysis (Addison-Wesley Data & Analytics Series)
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Pandas for Everyone: Python Data Analysis: Python Data Analysis (Addison-Wesley Data & Analytics Series)
Download Pandas for Everyone: Python Data Analysis: Python Data Analysis (Addison-Wesley Data & Analytics Series)
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About the Author
Daniel Chen is a graduate student in the interdisciplinary PhD program in Genetics, Bioinformatics & Computational Biology (GBCB) at Virginia Tech. He is involved with Software Carpentry as an instructor and lesson maintainer. He completed his master’s degree in public health at Columbia University Mailman School of Public Health in Epidemiology, and currently works at the Social and Decision Analytics Laboratory under the Biocomplexity Institute of Virginia Tech where he is working with data to inform policy decision-making. He is the author of Pandas for Everyone and Pandas Data Analysis with Python Fundamentals LiveLessons.
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Product details
Series: Addison-Wesley Data & Analytics Series
Paperback: 412 pages
Publisher: Addison-Wesley Professional; 1 edition (January 5, 2018)
Language: English
ISBN-10: 0134546938
ISBN-13: 978-0134546933
Product Dimensions:
7 x 1.1 x 9.1 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Average Customer Review:
4.6 out of 5 stars
7 customer reviews
Amazon Best Sellers Rank:
#65,882 in Books (See Top 100 in Books)
I'm more than half way through this book and found it much better as an intro to Pandas than the two other books I began reading: "Pandas Cookbook" by Petrou and "Python for Data Analysis" by Wes McKinney (the creator of Pandas). Both of the latter are fine books but Chen's book is more concise: he explains a method, shows one or two good examples, then moves on. Perfect for the way I learn. (I have 14 years of Python experience.)
I liked Jared Lander's "R for Everyone", the earlier entry in Addison-Wesley's "Data & Analytics" series, so I was looking forward to "Pandas for Everyone" - and mentioned it in my November 2017 review of "Pandas Cookbook" by Ted Petrou, as a just-around-the-corner alternative to wait for. Privately, I wondered if "Pandas Cookbook", a very decent book, was going to be completely eclipsed by "Pandas for Everyone" after just one month on the market.Now, I don’t think that is going to happen. Between the two titles - and the two, along with (of course) Wes McKinney's "Python for Data Analysis", are, in my opinion, the only Pandas titles worth considering - I prefer Petrou's, as a book with more substance and clarity. By all means, "Pandas for Everyone" is a good, original book, but one that is visibly under-edited, which makes its presentation less effective than it could be. There is less Pandas in it than in "Pandas Cookbook" - on the other hand (and this may be a plus for many readers), a couple of chapters are given to illustrations of statistical and machine-learning algorithms. (Applied to Pandas dataframes - that's the Pandas connection).My advice to a Pandas learner would be to get "Pandas Cookbook", "Pandas for Everyone", and "Python for Data Analysis", see whose style you prefer, and leave 1-2 books for further study.
Thank you Daniel! As a student in the midst of completing a Masters in Data Science, I found your book to be indispensable as a reference. Everything outlined in the text is clear and easy to comprehend.
Definitely gives me good overview of Pandas and how to use it but it is far away from complete reference.
I buy other books seam to more deeply and professional ,and need more times to study that isn't my intent.For my purpose is lean Pandas quickly and use to resolution my problem.The books's arrange and deepness is properly for novice.The book Let me quickly master Pandas but not need lean every detail or scientist's relation matter ,like the book's name "for every one".Thanks Daniel Y.
Most python data analysis textbooks start slow and build their way up to Pandas by way of NumPy. In contrast, Pandas for Everyone opens with an extended discussion of the steps involved with reading in and manipulating data. For the most part, chapters are bite sized and self contained. However, the examples are basic and I had to supplement this book with Wes Mckinney's "Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython" and Jake Vanderplas "Python Data Science Handbook" in order to fully understand what was going on under the hood.
The author has a very well organized way to present the concepts of data analysis (i.e. the what) and the tools (i.e. the how to part) without aiming to high in the complexity not boring the reader with the basics of python as many other books about Pandas.Best book in the market bridging the gap between basics and intermediate levels. Very practical, concise, and very engaging reading experience.
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