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Hands-On Data Preprocessing in Python

Hands-On Data Preprocessing in Python

By : Jafari
5 (20)
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Hands-On Data Preprocessing in Python

Hands-On Data Preprocessing in Python

5 (20)
By: 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)
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1
Part 1:Technical Needs
6
Part 2: Analytic Goals
11
Part 3: The Preprocessing
18
Part 4: Case Studies

What is data?

What is the definition of data? If you ask this question of different professionals in various fields, you will get all kinds of answers. I always ask this at the beginning of my data-related courses, and I always get a wide range of answers. The following are some of the common answers that my students have given when this question was asked:

  • Facts and statistics
  • Collections of records in databases
  • Information
  • Facts, figures, or information that's stored in or used by a computer
  • Numbers, sounds, and images
  • Records and transactions
  • Reports
  • Things that computers operate on

All of the preceding answers are correct, as the term data in different situations could be used to refer to all of the preceding. So, next time someone says we came to XYZ conclusions after analyzing the data, you know what your first question should be, right? Yes, the next question would be to understand exactly what they mean by "data."

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Tech Concepts
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Programming languages
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Hands-On Data Preprocessing in Python
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