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
Learn Python by Building Data Science Applications

You're reading from   Learn Python by Building Data Science Applications A fun, project-based guide to learning Python 3 while building real-world apps

Arrow left icon
Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Length 482 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Philipp Kats Philipp Kats
Author Profile Icon Philipp Kats
Philipp Kats
David Katz David Katz
Author Profile Icon David Katz
David Katz
Arrow right icon
View More author details
Toc

Table of Contents (26) Chapters Close

Preface 1. Section 1: Getting Started with Python
2. Preparing the Workspace FREE CHAPTER 3. First Steps in Coding - Variables and Data Types 4. Functions 5. Data Structures 6. Loops and Other Compound Statements 7. First Script – Geocoding with Web APIs 8. Scraping Data from the Web with Beautiful Soup 4 9. Simulation with Classes and Inheritance 10. Shell, Git, Conda, and More – at Your Command 11. Section 2: Hands-On with Data
12. Python for Data Applications 13. Data Cleaning and Manipulation 14. Data Exploration and Visualization 15. Training a Machine Learning Model 16. Improving Your Model – Pipelines and Experiments 17. Section 3: Moving to Production
18. Packaging and Testing with Poetry and PyTest 19. Data Pipelines with Luigi 20. Let's Build a Dashboard 21. Serving Models with a RESTful API 22. Serverless API Using Chalice 23. Best Practices and Python Performance 24. Assessments 25. Other Books You May Enjoy

Getting started with pandas

Pandas is the tool for data manipulation in Python—it combines speed and convenience, allowing the rapid processing and manipulation of data. Let's first overview a number of basic operations: pandas is simple and intuitive to use, but it is still a learning curve.

pandas does have two main data structures:

  1. Series is a one-dimensional array of one data type that also has an index. The index could be numeric, categorical, a string, or datetime.
  2. DataFrame is a two-dimensional table consisting of a set of columns—each of one single data type. Dataframe has two indexes—index and columns. Columns of Dataframe can be thought of as Series. Rows can be retrieved as Series but, in this case, data in the cells will likely be converted to one shared data type object (more on that later).

Most of the time, we get our data from external...

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