Book Image

Hands-On Data Preprocessing in Python

By : Roy Jafari
5 (2)
Book Image

Hands-On Data Preprocessing in Python

5 (2)
By: Roy Jafari

Overview of this book

Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects. With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.
Table of Contents (24 chapters)
1
Part 1:Technical Needs
6
Part 2: Analytic Goals
11
Part 3: The Preprocessing
18
Part 4: Case Studies

Are we analyzing data via computer programming?

To benefit most from the two modules that we will cover in this chapter, we need to understand what they really are and what we are really doing when we use them. I am sure whoever is in the business of content development for data analytics using Python, including me (guilty as charged), would tell you that when you use these modules to manipulate your data, you are analyzing your data using computer programming. However, what you are actually doing is not computer programming. The computer programming part has already been done for the most part. In fact, this has been done by the top-notch programmers who put together these invaluable packages. What you do is use their code made available to you as programming objects and functions under these modules. Well, if I am being completely honest, you are doing a tad bit of computer programming, but just enough to access the good stuff (these modules). Thanks to these modules, you will not experience any difficulty in analyzing data using computer programming.

So, before embarking on your journey in this chapter and this book, remember this: for the most part, our job as data analysts is to connect three things – our business problem, our data, and technology. The technology could be commercial software such as Excel or Tableau, or, in the case of this book, these modules.