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Buy Hands-On Data Analysis with Pandas: Efficiently perform data collection, wrangling, an by Molin, Stefanie online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase. Review: If you are new to Pandas and looking for a way to get up to speed fast this is a great book. Lots of good examples to see how to apply the concepts in real life, which helps a lot to understand how the different dataframe methods work. You can see the author payed a lot of attention to the detail, from the way to breakdown the chapters to the choice of exercises at the end of each chapter. As a Python programmer Learning Pandas I also appreciate a lot the quality of the code. Usually the code you find in data science examples get things done but it’s far from being of good quality. It’s very refreshing to see good examples written in a very pythonic way. I keep this book next to my desk and I have the feeling I will be coming back to use it as a reference a lot in the coming weeks. The only way this could be improved would be to have the author sit next to you every time you need to use Pandas :) Review: Excellent book! If you are looking to sharpen up on pandas and data analysis in python in general (not only pandas) this is a very solid. In my case I needed a strong refresher and this book was a great choice going beyond that. The accompanying notebooks are great too.
| Customer reviews | 4.4 4.4 out of 5 stars (48) |
| Dimensions | 19.05 x 4.24 x 23.5 cm |
| Edition | Standard Edition |
| ISBN-10 | 1789615321 |
| ISBN-13 | 978-1789615326 |
| Item weight | 1.21 Kilograms |
| Language | English |
| Print length | 716 pages |
| Publication date | 26 July 2019 |
| Publisher | Packt Publishing |
F**.
If you are new to Pandas and looking for a way to get up to speed fast this is a great book. Lots of good examples to see how to apply the concepts in real life, which helps a lot to understand how the different dataframe methods work. You can see the author payed a lot of attention to the detail, from the way to breakdown the chapters to the choice of exercises at the end of each chapter. As a Python programmer Learning Pandas I also appreciate a lot the quality of the code. Usually the code you find in data science examples get things done but it’s far from being of good quality. It’s very refreshing to see good examples written in a very pythonic way. I keep this book next to my desk and I have the feeling I will be coming back to use it as a reference a lot in the coming weeks. The only way this could be improved would be to have the author sit next to you every time you need to use Pandas :)
A**D
Excellent book! If you are looking to sharpen up on pandas and data analysis in python in general (not only pandas) this is a very solid. In my case I needed a strong refresher and this book was a great choice going beyond that. The accompanying notebooks are great too.
H**O
É um livro com muito conteúdo, tanto técnico quanto prático. Tem uma pequena introdução sobre Análise de Dados e Revisão de Tópicos de Estatística. E, em seguida, inicia um amplo e detalhado curso de Pandas. Tem teoria, exercícios e exemplos de aplicações práticas.
D**E
Chapters 1-6 were some of the best written I have ever written. But who the heck thought that the best way to bring all that knowledge together in chapter 7 was to condense it all in a single chapter along with very advanced object oriented programming (not mentioned yet in the book before Ch 7), decorators and financial market concepts??? Why would you do that? You don't jump from basic knife usage to advanced neurosurgery in a single chapter. Sure there is a "Further Reading" section where one might be able to eventually puzzle out the meaning of the concepts that the author machine guns at you. But if I was going to do that anyway, why do I need this book? Very frustrating! I guess the chapter is good to show an end point of "You will know you are an advanced python user when you can understand this chapter", but that is a goal and not a plan.
A**M
Amazing read. Very thorough, covering a broad range of topics in the data science space. I would highly recommend starting with this book for anyone interested in building a foundation in Data Science.
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