Advanced Python Tips
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Advanced Python Tips

A Simple Book on Advanced Python concepts

About the Book

Learning a language is easy. Whenever I start with a new language, I focus on a few things like operations and loops common to every language, and it is a breeze to get started with writing code in any language. 

However, learning to write code in a language and writing a language in an optimized way are two different things.

Every Language has some ingredients which make it unique. Yet, a new programmer to any language will invariably do some forced overfitting.

In this book, I will explain some simple constructs provided by Python, some essential tips, and some use cases I regularly use in my Data Science work. Most of the book is of a practical nature, and you will find it beaming with examples.

And the best thing- It's FREE, and you can choose to pay only if you like it. 

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    • Software
    • Computers and Programming
    • Python
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About the Author

Rahul Agarwal
Rahul Agarwal

I am Rahul Agarwal(MLWhiz), a data scientist consultant, and big data engineer based in London.

Previously, I have worked at startups like Fractal and MyCityWay and conglomerates like Citi, WalmartLabs, and Meta.

I started writing with the purpose to augment my own understanding of new things while helping others learn about them. I also write for publications on Medium like Towards Data Science and HackerNoon

As Feynman said: “I couldn’t do it. I couldn’t reduce it to the freshman level. That means we don’t really understand it”

Personally, I am tool agnostic. I like learning new tools and constantly working to add up new skills as I face new problems that cannot be accomplished with my current set of techniques. But the tools that currently get most of my work done are Python, Hadoop, and Spark.

I also like working with data-intensive problems and am constantly searching for new ideas to work on.

Table of Contents

  • About Me
  • Introduction
  • 1. Minimize For Loop Usage in Python
  • 2. Python's defaultdict and Counter
  • 3. *args, **kwargs, decorators for Data Scientists
  • 4. Use Itertools, Generators, and Generator Expressions
  • 5. How and Why to use f strings in Python3?
  • Afterword

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