Book Image

Python for Data Science For Dummies - Second Edition

By : John Paul Mueller, Luca Massaron
Book Image

Python for Data Science For Dummies - Second Edition

By: John Paul Mueller, Luca Massaron

Overview of this book

Python is a general-purpose programming language created in the late 1980s — and named after Monty Python — that's used by thousands of people to do things from testing microchips at Intel to powering Instagram to building video games with the PyGame library. The book begins by discussing how Python can make data science easy. You’ll learn how to work with the Anaconda tool suite that makes coding in Python easy. You’ll also learn to write code using Google Colab. As you progress, you'll discover how to perform interesting calculations and data manipulations using various Python libraries, such as pandas and NumPy. You’ll learn how to create data visualizations with MatPlotLib. While learning the advanced concepts, you’ll learn how to wrangle data by using techniques, such as hierarchical clustering. Finally, you’ll learn how to work with decision trees and use machine learning to make predictions. By the end of the book, you’ll have the skills and the knowledge that’s needed to write code in Python and extract information from data.
Table of Contents (13 chapters)
Free Chapter
1
Cover
9
Index
10
About the Authors
11
Advertisement Page
12
Connect with Dummies
13
End User License Agreement

Chapter 5

Understanding the Tools

IN THIS CHAPTER

Bullet Working with the Jupyter console

Bullet Working with Jupyter Notebook

Bullet Interacting with multimedia and graphics

Up to this point, the book spends a lot of time working with Python to perform data science tasks without actually engaging the tools provided by Anaconda much. Yes, a good deal of what you do involves typing in code and seeing what happens. However, if you don’t actually know how to use your tools well, you miss opportunities to perform tasks easier and faster. Automation is an essential part of performing data science tasks in Python.

This chapter is about working with the two main Anaconda tools, Jupyter console and Jupyter Notebook. Earlier chapters give you some experience with both tools, but those chapters don’t explore either tool in any detail, and you need to know these tools a lot better for upcoming chapters. The skills you develop in this chapter will help you perform tasks in later chapters with greater...