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Python Data Analysis

You're reading from   Python Data Analysis An end-to-end guide covering data processing, data manipulation and data visualization

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Product type Paperback
Published in Jul 2026
Publisher Packt
ISBN-13 9781806022878
Length 602 pages
Edition 4th Edition
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Authors (2):
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Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
Cornellius Yudha Wijaya Cornellius Yudha Wijaya
Author Profile Icon Cornellius Yudha Wijaya
Cornellius Yudha Wijaya
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Table of Contents (5) Chapters Close

Data analysis process methodologies

In the last decade, there has been a huge growth in the data analysis field. Lots of efforts are being made to establish the standard methodologies for data analysis and data analysis-based application development. In this section, we will discuss various process methodologies such as KDD, SEMMA, CRISP-DM, and the standard process. These methodologies have few overlapping or similar steps with different objectives.

Knowledge discovery from data (KDD)

Knowledge Discovery from Data is what KDD stands for. Data mining is also known by the term KDD. The practice of discovering and utilizing patterns for knowledge discovery is known as data mining. Finding hidden patterns in the data sources that are provided is the primary objective of the KDD process. There are seven main phases to the KDD process:

  • Data cleaning: In this first stage, we handle the noisy data, missing values, duplicates, and outliers in the given dataset.
  • Data integration: Then, data migration...
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Python Data Analysis
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Python Data Analysis - Fourth Edition
Published in: Jul 2026
Publisher: Packt
ISBN-13: 9781806022878
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