Book Image

Python Data Science Essentials

Book Image

Python Data Science Essentials

Overview of this book

The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results. In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
Table of Contents (13 chapters)

Chapter 2. Data Munging

We are just getting into action! In this new chapter, you'll essentially learn how to munge data. What does munging data imply?

The term munge is a technical term coined about half a century ago by the students of the Massachusetts Institute of Technology (MIT). Munging means to change, in a series of well-specified and reversible steps, a piece of original data to a completely different (and hopefully a more useful) one. Deep-rooted in hacker culture, munging is often heard in data science processes in parallel with other almost completely synonymous terms, such as data wrangling and data preparation.

Given such premises, in this chapter, the following topics will be covered:

  • The data science process (so you'll know what is going on and what's next)

  • Uploading data from a file

  • Selecting the data you need

  • Cleaning up missing or wrong data

  • Adding, inserting, and deleting data

  • Grouping and transforming data to obtain new, meaningful information

  • Managing to obtain a dataset matrix...