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 22

Ten Data Challenges You Should Take

IN THIS CHAPTER

Bullet Locating starting challenges

Bullet Working with specific kinds of data

Bullet Performing analysis, pattern recognition, and classification

Bullet Dealing with huge online datasets

Data science is all about working with data. While working through this book, you have used a number of datasets, including the toy datasets that come with the Scikit-learn library. Of course, these datasets are all great for getting you started, but just as a runner wouldn’t stop after conquering the local fun run, so you need to start training for data science marathons by working with larger datasets.

This chapter introduces you to a number of challenging datasets that can help you become a world-class data scientist. By combining what you discover in this book with these new datasets, you can learn how to do amazing things. In fact, some people may view you as a bit of a magician as you pull seemingly impossible data patterns out of your hat. Each of...