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 9

Putting What You Know in Action

IN THIS CHAPTER

Bullet Putting data science problems and data into perspective

Bullet Defining and using feature creation to your benefit

Bullet Working with arrays

Previous chapters have all been preparatory in nature. You have discovered how to perform essential data science tasks using Python. In addition, you spent time working with the various tools that Python provides to make data science tasks easier. All this information is essential, but it doesn’t help you see the big picture — where all the pieces go. This chapter shows you how to employ the techniques you discovered in previous chapters to solve real data science problems.

Remember This chapter isn’t the end of the journey — it’s the beginning. Think of previous chapters in the same way as you think about packing your bags, making reservations, and creating an itinerary before you go on a trip. This chapter is the trip to the airport, during which you start to see everything...