Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Analysis with Python

You're reading from   Data Analysis with Python A Modern Approach

Arrow left icon
Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950069
Length 490 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
David Taieb David Taieb
Author Profile Icon David Taieb
David Taieb
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Programming and Data Science – A New Toolset FREE CHAPTER 2. Python and Jupyter Notebooks to Power your Data Analysis 3. Accelerate your Data Analysis with Python Libraries 4. Publish your Data Analysis to the Web - the PixieApp Tool 5. Python and PixieDust Best Practices and Advanced Concepts 6. Analytics Study: AI and Image Recognition with TensorFlow 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis 10. The Future of Data Analysis and Where to Develop your Skills A. PixieApp Quick-Reference Other Books You May Enjoy Index

Chapter 1. Programming and Data Science – A New Toolset

"Data is a precious thing and will last longer than the systems themselves."

Tim Berners-Lee, inventor of the World Wide Web

(https://en.wikipedia.org/wiki/Tim_Berners-Lee)

In this introductory chapter, I'll start the conversation by attempting to answer a few fundamental questions that will hopefully provide context and clarity for the rest of this book:

  • What is data science and why it's on the rise
  • Why is data science here to stay
  • Why do developers need to get involved in data science

Using my experience as a developer and recent data science practitioner, I'll then discuss a concrete data pipeline project that I worked on and a data science strategy that derived from this work, which is comprised of three pillars: data, services, and tools. I'll end the chapter by introducing Jupyter Notebooks which are at the center of the solution I'm proposing in this book.

You have been reading a chapter from
Data Analysis with Python
Published in: Dec 2018
Publisher: Packt
ISBN-13: 9781789950069
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image