Learning the Pandas Library: Python Tools for Data Munging, Analysis, and Visualization

by Matt Harrison, Michael Prentiss (Editor)

Python is one of the top 3 tools that Data Scientists use. One of the tools in their arsenal is the Pandas library. This tool is popular because it gives you so much functionality out of the box. In addition, you can use all the power of Python to make the hard stuff easy! Learning the Pandas Library is designed to bring developers and aspiring data scientists who are anxious to learn Pandas up to speed quickly. It covers the latest version of Pandas. It starts with the fundamentals of the data structures. Then, it covers the essential functionality. It includes many examples, graphics, code samples, and plots from real world examples. The Content * Installation * Data Structures * Series CRUD * Series Indexing * Series Methods * Series Plotting * Series Examples * DataFrame Methods * DataFrame Statistics * Grouping, Pivoting, and Reshaping * Dealing with Missing Data * Joining DataFrames * DataFrame Examples The book uses Python 3 throughout! Preliminary Reviews This is an excellent introduction benefitting from clear writing and simple examples. The pandas documentation itself is large and sometimes assumes too much knowledge, in my opinion. Learning the Pandas Library bridges this gap for new users and even for those with some pandas experience such as me. Garry C. I have finished reading Learning the Pandas Library and I liked it... very useful and helpful tips even for people who use pandas regularly. Tom Z.

Genres: Programming, Computers, Textbooks, Coding, Technical

213 pages, Kindle Edition

Published June 7, 2016

Reviews

[Maru Kun · Rating 4 out of 5]

As of October 2018 Azure allows you to host jupyter notebooks for free which are pretty useful for writing up notes when working through this sort of book. Got to start somewhere!

Overall this was a pretty decent introduction to pandas - at least that's what it seemed like to a dilletante like me. It gave examples of what you could do with pandas and a sense of how it could be used for data cleaning and presentation using a case based on avalanche data, including an example of geographic plotting using folium (nothing detailed - simply one passage of code but interesting to know this could be done in a Jupyter notebook).

On the other hand if I was more confident I could have probably got the same if not more from the docs with respect to how the various methods actually work. although would have missed out seeing some examples in practice which this book can offer.

This video has an example of using pandas .read_html to directly read html table data from the web into a pandas DataFrame.

Series - introduction

Series CRUD and indexing

Series methods

Series methods continued

Series plotting

Data Frames

Plotting with DataFrames

Joining DataFrames

Grouping and pivot tables

Dealing with missing data

Useful reference articles

[Mehrnaz · Rating 4 out of 5]

کتاب خوبیه. ولی به نظرم شاید دونستن این کتابخونه در این سطح جزئیات مخصوصا وقتی که لازمشون نداشته باشید، ضروری نباشه.
یعنی وقتی لازم شد گوگل کردن، کارا تر به نظر میرسه.

[Matt Chan · Rating 3 out of 5]

This book was (self)published in 2016, and as such there are quite a bit of information inside that is obsolete. A good amount of the methods (e.g. .ix(), .set_value()) were deprecated, so there are some confusion to be had while I was working through the book. That said, the gist of the Pandas package was fairly well described, I think between this and the Coursera class I took I'm fairly comfortable in using pandas now. There are two larger projects that the author walk you through step by step here, and that's very helpful. Unfortunately a huge chuck on the code in the last project doesn't really work anymore because a.) The website the author scrapped the data from has been thoroughly updated (although the scrapped data is on his github, so that's fine) and b.) The code for the folium map is completely unusable, so that whole section needed to be skipped. Anyway, it's worth tracking down this book and working through it (took me about a week on-and-off) if you are teaching yourself pandas, just know that you'll definitely have to supplement it with up-to-date docs on Stack Overflow and the pandas docs.

[Ben · Rating 5 out of 5]

An excellent Python resource.

Good library. Endlessly expansive.

I find it pretty simple to grasp quickly.

Would recommend for data scientists, among many other professions.

4.8/5

[russell · Rating 4 out of 5]

With more interactive learning resources available for learning data-related programming (MOOCs in particular), why read a book about it? Reading through Harrison’s problem solving approach with Pandas allows the reader to learn at a different, slower wavelength. It’s an angle and approach to data that I don’t think more interactive media sources provide. He enables the reader to think more critically and with less distraction, and provides experienced intuition to help guide the reader with best practices along with way.

In fact, I was referred to this book by a MOOC (U Michigan Data Science something or other).

[Bangara Raju · Rating 5 out of 5]

- I started reading this book to gain some knowledge on Pandas.
- This is a great book for someone who wants to learn pandas
- It is easy to read with great examples.

[Andrey Andreev · Rating 5 out of 5]

Simple, briefly and on business 📈