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 6

Working with Real Data

IN THIS CHAPTER

Bullet Manipulating data streams

Bullet Working with flat and unstructured files

Bullet Interacting with relational databases

Bullet Using NoSQL as a data source

Bullet Interacting with web-based data

Data science applications require data by definition. It would be nice if you could simply go to a data store somewhere, purchase the data you need in an easy-open package, and then write an application to access that data. However, data is messy. It appears in all sorts of places, in many different forms, and you can interpret it in many different ways. Every organization has a different method of viewing data and stores it in a different manner as well. Even when the data management system used by one company is the same as the data management system used by another company, the chances are slim that the data will appear in the same format or even use the same data types. In short, before you can do any data science work, you must discover how to access the data in...