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

Exploring Python packages

Before wrapping up this chapter, let's explore the different Python packages required with data analysis and validate they are available to use in the Jupyter Notebook app. These packages have evolved over time and are open source so programmers can contribute and improve the source code.

The version of the Python packages will increment over time depending on when you install conda or pip (package manager) on your machine. If you receive errors running commands, validate they match the versions used in this book.

We will go into more depth about each individual package as we use their awesome features in future chapters. The focus in this chapter is to verify the specific libraries are available, and there are a few different approaches to use such as inspecting the installation folder for specific files on your workstation or running commands from a Python command line. I find the easiest method is to run a few simple commands in...

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