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

Types of databases

Mainly there are four types of databases:

  • Relational databases (or SQL databases)
  • Unstructured databases (NoSQL)
  • Distributed databases
  • Blockchain

The distinctions between these databases are not cut and dried technologically and in practice. For instance, distributed databases are essentially a combination of different types of databases in multiple locations. Here, we will discuss these types of databases to develop a better appreciation for the way databases organize data according to a situation's needs. We will also briefly talk about the differences and similarities, as well as the advantages and disadvantages, of the types of databases.

Why do we need to know the types of databases for data preprocessing?

Each of the four types of databases organizes and stores the data differently. As our data analytics journey always involves locating and collecting data from various databases, knowing different kinds of databases serves...