Search icon CANCEL
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
Practical Data Analysis Using Jupyter Notebook

You're reading from   Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python

Arrow left icon
Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838826031
Length 322 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Marc Wintjen Marc Wintjen
Author Profile Icon Marc Wintjen
Marc Wintjen
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Analysis Essentials
2. Fundamentals of Data Analysis FREE CHAPTER 3. Overview of Python and Installing Jupyter Notebook 4. Getting Started with NumPy 5. Creating Your First pandas DataFrame 6. Gathering and Loading Data in Python 7. Section 2: Solutions for Data Discovery
8. Visualizing and Working with Time Series Data 9. Exploring, Cleaning, Refining, and Blending Datasets 10. Understanding Joins, Relationships, and Aggregates 11. Plotting, Visualization, and Storytelling 12. Section 3: Working with Unstructured Big Data
13. Exploring Text Data and Unstructured Data 14. Practical Sentiment Analysis 15. Bringing It All Together 16. Works Cited
17. Other Books You May Enjoy

Preparing to work with unstructured data

Today, we are living in a digital age where data is entangled into our lives in ways not technically possible or even imaginable before. From social media to mobile to the Internet of Things (IoT), humanity is living in what is commonly known as the information age. This age is where an exponentially growing of data about you is available to you instantaneously anywhere in the world. What has made this possible has been a combination of people and technology, including contributions from the Evolution of Data Analysis, which was introduced in Chapter 1, Fundamentals of Data Analysis.

It is commonly predicted by multiple sources that 80 percent of all of the data created around the world will be unstructured over the next few years. If you recall from Chapter 1,Fundamentals of Data Analysis., unstructured data is commonly defined as information that does not offer uniformity and pre-defined organization. Examples of unstructured...

lock icon The rest of the chapter is locked
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