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Python Data Science Essentials

You're reading from   Python Data Science Essentials A practitioner's guide covering essential data science principles, tools, and techniques

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789537864
Length 472 pages
Edition 3rd Edition
Languages
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Authors (2):
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Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alberto Boschetti Alberto Boschetti
Author Profile Icon Alberto Boschetti
Alberto Boschetti
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Toc

Table of Contents (11) Chapters Close

Preface 1. First Steps FREE CHAPTER 2. Data Munging 3. The Data Pipeline 4. Machine Learning 5. Visualization, Insights, and Results 6. Social Network Analysis 7. Deep Learning Beyond the Basics 8. Spark for Big Data 9. Strengthen Your Python Foundations 10. Other Books You May Enjoy

Your learning list

Here are the basic Python data structures that you need to learn to be as proficient as a data scientist. Leaving aside the real basics (numbers, arithmetic, strings, Booleans, variable assignments, and comparisons), the list is indeed short. We will briefly deal with it by touching upon only the recurrent structures in data science projects. Remember that the topics are quite challenging, but they are necessary to master if you want to write effective code:

  • Lists
  • Dictionaries
  • Classes, objects, and object-oriented programming
  • Exceptions
  • Iterators and generators
  • Conditionals
  • Comprehensions
  • Functions

Take it as a refresher or a learning list depending on your actual knowledge of the Python language. However, examine all the proposed examples because you will come across them again during the course of this book.

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