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35028587
Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights
86% of respondents would recommend this to a friend
Item #:
35028587
TTD 350
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What Stands Out
Modern Techniques
Incorporates cutting-edge methods for data cleaning, ensuring users are equipped with the latest strategies to tackle dirty data challenges effectively.
Comprehensive Tools
Offers an extensive selection of Python tools tailored for data cleaning, enabling users to efficiently extract valuable insights and enhance data quality.
User-Centric Approach
Designed for both beginners and seasoned analysts, providing practical examples and easy-to-follow instructions that simplify complex data cleaning processes.
Product Details
| Publisher | Packt Publishing |
| Publication date | December 11, 2020 |
| Language | English |
| Print length | 436 pages |
| ISBN-10 | 1800565666 |
| ISBN-13 | 978-1800565661 |
| Item Weight | 1.64 pounds (740 grams) |
| Dimensions | 7.5 x 0.99 x 9.25 inches (19.1 x 2.5 x 23.5 cm) |
Who Should Buy?
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Data Analysts
Data analysts looking to enhance their skills in data cleaning using modern Python techniques will find this cookbook invaluable.
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Data Scientists
Data scientists needing effective methods to preprocess datasets for analysis and model training will benefit greatly from this resource.
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Python Beginners
Beginners in Python who seek practical applications of data cleaning will find clear examples and guidance in this cookbook.
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Advanced Users
Advanced data professionals might find the cookbook's content too basic and not suitable for their complex data needs.
Product Description
Python Data Cleaning Cookbook: Modern techniques and Python tools to detect and remove dirty data and extract key insights
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Data Mining Editorial Review
Python Data Cleaning Cookbook provides a comprehensive guide for software developers who need to process, clean and refine their datasets. The cookbook format, where each recipe provides a coding solution to specific problems, is effective in providing a range of techniques to help users extract meaningful insights. The book covers topics like detecting anomalies, visualizing data, and processing it at a macroscopic level. One of the standout features of the book is the author's ability to provide a 'WHY' behind data processing tasks, giving readers a deeper understanding of the concepts. The book is approachable for those new to Python and data processing and provides hands-on examples to help Consolidate information.
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Pros
- Comprehensive guide for processing, cleaning and refining datasets
- Effective cookbook format with each recipe addressing specific problems
- Covers detecting anomalies, visualizing data and processing data at a macroscopic level
- 'WHY' behind data processing tasks provided
- Approachable for beginners
- Provides hands-on examples
Cons
- Some beginners may find it challenging to follow along
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23 October 2026 · via Trustpilot
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